{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Working with data in Python" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## Lesson preamble\n", "\n", "This 4-hour workshop takes learners through the basics of programming in Python via the Jupyter Lab interface and culminates with exploration and visualization of real-world bicycle count data from the City of Toronto. This material is based on [workshops](https://uoftcoders.github.io/2018-07-12-utoronto/) hosted by [UofT Coders](https://uoftcoders.github.io), inspired by the [Data Carpentry Ecology Python lesson](https://datacarpentry.org/python-ecology-lesson/).\n", "\n", "### Lesson objectives\n", "\n", "#### Part 1: introduction to programming in Python\n", "- Overview of the capabilities of Python and how to use\n", " JupyterLab for exploratory data analyses.\n", "- Learn about some differences between Python and Excel.\n", "- Learn basic Python commands.\n", "- Learn about the Markdown syntax and how to use it within the Jupyter Notebook.\n", "\n", "#### Part 2: working with data in Python\n", "- Describe what a data frame is\n", "- Load external data from a .csv file into a data frame with `pandas`\n", "- Summarize the contents of a data frame with `pandas`.\n", "- Learn to use data frame attributes `loc[]`, `head()`, `info()`, `describe()`, `shape`, `columns`, `index`.\n", "- Understand the split-apply-combine concept for data analysis.\n", "- Use `groupby()`, `sum()`, `agg()` and `size()` to apply this technique.\n", "\n", "#### Part 3: visualizing data\n", "- Produce scatter plots, line plots, and histograms using `seaborn` and `matplotlib`.\n", "- Understand how to graphically explore relationships between variables.\n", "- Apply grids for faceting in `seaborn`.\n", "- Set universal plot settings.\n", "- Use `seaborn` grids with `matplotlib` functions\n", "\n", "### Lesson outline\n", "\n", "- Communicating with computers (5 min)\n", " - Advantages of text-based communication (5 min)\n", " - Speaking Python (5 min)\n", " - Natural and formal languages (5 min)\n", "- The Jupyter Notebook (10 min)\n", "- Data analysis in Python (5 min)\n", " - Packages (5 min)\n", " - How to get help (5 min)\n", "- Manipulating and analyzing data with pandas\n", " - Data set background (10 min)\n", " - What are data frames (15 min)\n", " - Data wrangling with pandas (40 min)\n", "- Split-apply-combine techniques in `pandas`\n", " - Using `sum()` and `mean()` to summarize categorical data (20 min)\n", " - Using `size()` to summarize categorical data (10 min)\n", "- Data visualization with `matplotlib` and `seaborn` (10 min)\n", " - Visualizing one quantitative variable with multiple categorical variables (40 min)\n", " - Visualizing the relationship of two quantitative variable with multiple categorical variables (40min)\n", " - Using any plotting function with `seaborn` grids (10 min)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup\n", "\n", "- Install Python 3 via [Anaconda](https://www.anaconda.com/download/). Anaconda is a distribution of Python that also includes the most commonly used packages as well as some nice tools for working with code. The one we will use today is called [JupyterLab](http://jupyterlab.readthedocs.io/en/stable/index.html) and comes with newer downloads of Anaconda. (Before February 2018, Anaconda came with Jupyter notebook, an older version.)\n", "- **Important:** If you downloaded Anaconda before July 2018, make sure to update the package `seaborn` before beginning:\n", " - Open a terminal window or `anaconda prompt` and type `conda update seaborn` and hit enter. If that doesn't work, try `conda install seaborn`.\n", "- Open **JupyterLab**: \n", " - Open **Anaconda Navigator** and select **JupyterLab**, *or*\n", " - Open a terminal window or `anaconda prompt` and type `jupyter-lab` \n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The aim of this workshop is to teach you basic concepts, skills, and tools for working with data so that you can get more done in less time, while having more fun. You will learn how to use the programming language Python to replace many of the tasks you would normally do in spreadsheet software such as Excel, and also do more advanced analysis.\n", "\n", "## Communicating with computers\n", "\n", "- Computing is about humans communicating with the computer to modulate flows of current in the hardware, in order to get the computer to carry out advanced calculations that we are unable to efficiently compute ourselves. \n", "- Early examples of human-computer communication included actually disconnecting a wire and connecting it again in a different spot. \n", "- Today we usually use graphical user interfaces with menus and buttons. These graphical interfaces can be thought of as a layer or shell around the internal components of your operating system making it easier for us to express our thoughts and for computers to interpret them.\n", "- An example of a graphical user interface is spreadsheet software such as Microsoft Excel or LibreOffice Calc. Here, all the functionality of the program is accessible via hierarchical menus, and clicking buttons sends instructions to the computer, which then responds and sends the results back to your screen.\n", "- Spreadsheet software is great for viewing and entering small data sets and creating simple visualizations fast. However, it can be tricky to design publication-ready figures, create automatic reproducible analysis workflows, perform advanced calculations, and reliably clean data sets. Even when using a spreadsheet program to record data, it is often beneficial to have some some basic programming skills to facilitate the analyses of those data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Advantages of text-based communication\n", "\n", "Today we will communicate with our computers via text rather than graphical point and click. Typing instructions to the computer might at first seem counterintuitive and unnecessarily difficult. While graphical user interfaces can be nice when you are new to something, text-based interfaces are more powerful, faster and actually also easier to use once you get comfortable with them.\n", "\n", "Think about learning a language: in the beginning it's nice to look things up in a dictionary (or a menu in a graphical program), and slowly string together sentences one word at a time. But once we become more proficient in the language and know what we want to say, it is easier to say or type it directly, instead of having to look up every word in the dictionary first.\n", "\n", "Text interfaces are also less resource-intensive than their graphical counterparts and easier to develop programs for since you don't have to code the graphical components. It is also much easier to automate and repeat any task once you have all the instructions written down. This facilitates reproducibility of analysis, not only between studies from different labs, but also between researchers in the same lab: compare being shown how to perform a certain analysis in spreadsheet software, where the instruction will essentially be \"first you click here, then here, then here...\", with being handed the same workflow written down in several lines of codes which you can analyse and understand at your own pace. \n", "\n", "Since text is the easiest way for people who are fluent in computer languages to interact with computers, many powerful programs are written without a graphical user interface (which makes it faster to create these programs) and to use these programs you often need to know how to use a text interface. For example, many of the best data analysis and machine learning packages are written in Python or R, and you need to know these languages to use them. Even if the program or package you want to use is not written in Python, much of the knowledge you gain from understanding one programming language can be transferred to others. In addition, most powerful computers that you can log into remotely might only give you a text interface to work with and there is no way to launch a graphical user interface." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Speaking Python\n", "\n", "To communicate with the computer via Python, we first need an environment that knows how to interpret Python code. We want commands we type to be *interpreted* into machine language so that the computer can understand it. For the entire workshop today, we will work in the **JupyterLab** environment. \n", "\n", "#### Launch JupyterLab\n", "\n", "**Method 1**\n", "On Windows open the `Anaconda Prompt`, on MacOS open `terminal.app`, and on Linux open whichever terminal you prefer (e.g. `gnome-terminal` or `konsole`). Then type in `jupyter-lab` and hit Enter. \n", "\n", "**Method 2**\n", "Open `Anaconda Navigator`, then select `JupyterLab` from the menu.\n", "\n", "You should see something like this:\n", "\n", "![](img/jupyter-start-screen.jpg)\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The Jupyter Notebook\n", "\n", "Jupyter originates from a project called IPython, an effort to make Python development more interactive. Since its inception, the scope of the project expanded to include additional programming languages, such as Julia, Python, and R, so the name was changed to \"Jupyter\" as a reference to these core languages. Today, Jupyter supports many more languages, but we will be using it only for Python code. Specifically, we will be using the notebook from Jupyter, which allows us to easily take notes about our analysis and view plots within the same document where we code. This facilitates sharing and reproducibility of analyses, and the notebook interface is easily accessible through any web browser as well as exportable as a PDF or HTML page.\n", "\n", "In the new browser tab, click the plus sign to the left and select to create a new notebook in the Python language (also `File --> New --> Notebook`).\n", "\n", "Initially the notebook has no name other than \"Untitled\". If you click on \"Untitled\" you will be given the option of changing the name to whatever you want.\n", "\n", "The notebook is divided into cells. Initially there will be a single input cell. You can type Python code directly into the cell. To run the output, press Shift + Enter or click the play button in the toolbar." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "9" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "4 + 5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The sparseness in the input `4 + 5` is much more efficient than typing \"Hello computer, could you please add 4 and 5 for me?\". Formal computer languages also avoid the ambiguity present in natural languages such as English. You can think of Python as a combination of math and a formal, succinct version of English. Since it is designed to reduce ambiguity, Python lacks the edge cases and special rules that can make English so difficult to learn, and there is almost always a logical reason for how the Python language is designed, not only a historical one.\n", "\n", "The syntax for assigning a value to a variable is also similar to how this is written in math." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "a = 4" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "8" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a * 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Learning programming really is similar to learning another language - you will often learn the most from just trying to do something and receiving feedback (from the computer or another person)! When there is something you can't wrap your head around, or if you are actively trying to find a new way of expressing a thought, then look it up, just as you would with a natural language." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "9" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "4 + 5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By default, the code in the current cell is interpreted and the next existing cell is selected or a new empty one is created (you can press Ctrl + Enter to stay on the current cell). You can split the code across several lines as needed. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The little counter on the left of each cell keeps track of in which order the cells were executed, and changing to an `*` when the computer is processing the computation (only noticeable for computation that takes longer time). \n", "\n", "The notebook is saved automatically, but it can also be done manually from the toolbar or by hitting Ctrl + s. Both the input and the output cells are saved so any plots that you make will be present in the notebook next time you open it up without the need to rerun any code. This allows you to create complete documents with both your code and the output of the code in a single place instead of spread across text files for your codes and separate image files for each of your graphs.\n", "\n", "You can also change the cell type from Python code to Markdown using the Cell | Cell Type option. Markdown is a simple formatting system which allows you to create documentation for your code, again all within the same notebook structure. You might already be famliar with markdown if you have typed comments in online forums or use use a chat app like slack or whatsapp. A short example of the syntax:\n", "\n", "```markdown\n", "# Heading level one\n", "\n", "- A bullet point\n", "- *Emphasis in italics*\n", "- **Strong emphasis in bold**\n", "\n", "This is a [link to learn more about markdown](https://guides.github.com/features/mastering-markdown/)\n", "```\n", "\n", "The Notebook itself is stored as a JSON file with an .ipynb extension. These are specially formatted text files, which can be exported and imported into another Jupyter system. This allows you to share your code, results, and documentation with others. You can also export the notebook to HTML, PDF, and many other formats to make sharing even easier! This is done via `File --> Export Notebook As...`\n", "\n", "The data analysis environment provided by the Jupyter Notebook is very powerful and facilitates reproducible analysis. It is possible to write an entire paper in this environment, and it is very handy for reports such as progress updates since you can share your comments on the analysis together with the analysis itself.\n", "\n", "It is also possible to open up other document types in the JupyterLab interface, e.g. text documents and terminals. These can be placed side by side with the notebook through drag and drop, and all running programs can be viewed in the \"Running\" tab to the left. To search among all available commands for the notebook, the \"Commands\" tab can be used. Existing documents can be opened from the \"Files\" tab.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Does JupyterLab require the internet?\n", "\n", "Jupyter runs in your browser, but you can use it without internet access: it's all running offline, on your computer. Notice that the address bar will say something like `localhost:8888/lab`, which means it's being \"served\" from your computer. \n", "\n", "Browsers are programs that display text files that are formatted with HTML. It just so happens that most of the files you want to view are on other computers and so you need internet, but you can also open any old HTML file from your computer in your browser, without the internet." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data analysis in Python\n", "\n", "To access additional functionality in a spreadsheet program, you need to click the menu and select the tool you want to use. All charts are in one menu, text layout tools in another, data analyses tools in a third, and so on. Programming languages such as Python have so many tools and functions so that they would not fit in a menu. Instead of clicking `File -> Open` and chose the file, you would type something similar to `file.open('')` in a programming language. Don't worry if you forget the exact expression, it is often enough to just type the few first letters and then hit Tab, to show the available options. More on that later.\n", "\n", "### Packages\n", "\n", "Since there are so many functions available in Python, it is unnecessary to include all of them with the default installation of the programming language (it would be as if your new phone came with every single app preinstalled). Instead, more advanced functionality is grouped into separate packages, which can be accessed by typing `import ` in Python. You can think of this as that you are telling the program which menu items you want to activate (similar to how Excel hides the `Developer menu` by default since most people rarely use it and you need activate it in the settings if you want to access its functionality). The Anaconda Python distribution essentially bundles the core Python language with many of the most effective Python packages for data analysis, but some packages need to be downloaded before they can be used, just like downloading an addon to a browser or mobile phone.\n", "\n", "Just like in spreadsheet software menus, there are lots of different tools within each Python package. For example, if I want to use numerical Python functions, I can import the **num**erical **py**thon module, `numpy`. I can then access any function by writing `numpy.`." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3.0" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy\n", "\n", "numpy.mean([1, 2, 3, 4, 5])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### How to get help\n", "\n", "Once you start out using Python, you don't know what functions are availble within each package. Luckily, in the Jupyter Notebook, you can type `numpy.`Tab (that is numpy + period + tab-key) and a small menu will pop up that shows you all the available functions in that module. This is analogous to clicking a 'numpy-menu' and then going through the list of functions. As I mentioned earlier, there are plenty of available functions and it can be helpful to filter the menu by typing the initial letters of the function name.\n", "\n", "To get more info on the function you want to use, you can type out the full name and then press Shift + Tab once to bring up a help dialogue and again to expand that dialogue. We can see that to use this function, we need to supply it with the argument `a`, which should be 'array-like'. An array is essentially just a sequence of numbers. We just saw that one way of doing this was to enclose numbers in brackets `[]`, which in Python means that these numbers are in a list, something you will hear more about later. Instead of manually activating the menu every time, the JupyterLab offers a tool called the \"Inspector\" which displays help information automatically. I find this very useful and always have it open next to my Notebook. More help is available via the \"Help\" menu, which links to useful online resources (for example `Help --> Numpy Reference`).\n", "\n", "When you start getting familiar with typing function names, you will notice that this is often faster than looking for functions in menus. However, sometimes you forget and it is useful to get hints via the help system described above.\n", "\n", "It is common to give packages nicknames, so that it is faster to type. This is not necessary, but can save some work in long files and make code less verbose so that it is easier to read:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction to programming in Python" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Operators\n", "\n", "Python can be used as a calculator and mathematical calculations use familiar operators such as `+`, `-`, `/`, and `*`." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "2 + 2 " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "42" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "6 * 7" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.3333333333333333" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "4 / 3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Text prefaced with a `#` is called a \"comment\". These are notes to people reading the code, so they will be ignored by the Python interpreter." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "8" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# `**` means \"to the power of\"\n", "2 ** 3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Values can be given a nickname, this is called assigning values to variables and is handy when the same value will be used multiple times. The assignment operator in Python is `=`." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "10" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a = 5\n", "a * 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A variable can be named almost anything. It is recommended to separate multiple words with underscores and start the variable name with a letter, not a number or symbol." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "new_variable = 4\n", "a - new_variable" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Variables can hold different types of data, not just numbers. For example, a sequence of characters surrounded by single or double quotation marks is called a string. In Python, it is intuitive to append strings by adding them together:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Hellouniverse'" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "b = 'Hello'\n", "c = 'universe'\n", "b + c" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A space can be added to separate the words." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Hello universe'" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "b + ' ' + c" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To find out what type a variable is, the built-in function `type()` can be used. In essence, a function can be passed input values, follows a set of instructions with how to operate on the input, and then outputs the result. This is analogous to following a recipe: the ingredients are the input, the recipe specifies the set of instructions, and the output is the finished dish." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "int" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(a)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`int` stands for \"integer\", which is the type of any number without a decimal component.\n", "\n", "To be reminded of the value of `a`, the variable name can be typed into an empty code cell." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "5" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A code cell will only output its last value. To see more than one value per code cell, the built-in function `print()` can be used. When using Python from an interface that is not interactive like the JupyterLab Notebook, such as when executing a set of Python instructions together as a script, the function `print()` is often the preferred way of displaying output." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "5\n" ] }, { "data": { "text/plain": [ "int" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print(a)\n", "type(a)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Numbers with a decimal component are referred to as floats" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "float" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(3.14)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Text is of the type `str`, which stands for \"string\". Strings hold sequences of characters, which can be letters, numbers, punctuation or more exotic forms of text (even emoji!)." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "data": { "text/plain": [ "'Hello'" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print(type(b))\n", "b" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The output from `type()` is formatted slightly differently when it is printed." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Python also allows comparison and logic operators (`<`, `>`, `==`, `!=`, `<=`, `>=`, `and`, `or`, `not`), which will return either `True` or `False`." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "3 > 4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`not` reverses the outcome from a comparison." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "not 3 > 4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`and` checks if both comparisons are `True`." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "3 > 4 and 5 > 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`or` checks if *at least* one of the comparisons are `True`." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "3 > 4 or 5 > 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The type of the resulting `True` or `False` value is called \"boolean\"." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "bool" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Boolean comparison like these are important when extracting specific values from a larger set of values. This use case will be explored in detail later in this material.\n", "\n", "Another common use of boolean comparison is with a *conditional* statement, where the code after the comparison only is executed if the comparison is `True`." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a is not 4\n" ] } ], "source": [ "if a == 4: # if a is equal to 4\n", " print('a is 4')\n", "else: # if a is not equal to 4\n", " print('a is not 4')" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "5" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that the second line in the example above is indented. Indentation is very important in Python, and the Python interpreter uses it to understand that the code in the indented block will only be exectuted if the conditional statement above is `True`.\n", "\n", "> Challenge 1\n", "> 1. Assign `a*2` to the variable name `two_a`.\n", "> 2. Change the value of `a` to `3`. What is the value of `two_a` now, `6` or `10`?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Array-like Python types\n", "\n", "### Lists\n", "\n", " **Lists** are a common data structure to hold an ordered sequence of elements. Each element can be accessed by an index. Note that Python indexes start with 0 instead of 1." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Earth'" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "planets = ['Earth', 'Mars', 'Venus']\n", "planets[0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can index from the end of the list by prefixing with a minus sign" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Venus'" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "planets[-1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Multiple elements can be selected via slicing." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Earth', 'Mars']" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "planets[0:2]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Slicing is inclusive of the start of the range and exclusive of the end, so `0:2` returns list elements `0` and `1`.\n", "\n", "Either the start or the end number of the range can be excluded to include all items to the beginning or end of the list, respectively." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Earth', 'Mars']" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "planets[:2]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To add items to the list, the addition operator can be used together with a list of the items to be added." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Earth', 'Mars', 'Venus', 'Neptune']" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "planets = planets + ['Neptune']\n", "planets" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A loop can be used to access the elements in a list or other Python data structure one at a time, and then do something with each element. Loops are an important part of programming - they make automation of repetitive tasks possible." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Earth\n", "Mars\n", "Venus\n", "Neptune\n" ] } ], "source": [ "for planet in planets:\n", " print(planet)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The variable `planet` is recreated for every iteration in the loop until the list `planets` has been exhausted. \n", "\n", "Operations can be performed on elements inside loops." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "I live on Earth\n", "I live on Mars\n", "I live on Venus\n", "I live on Neptune\n" ] } ], "source": [ "for planet in planets:\n", " print('I live on ' + planet)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Tuples\n", "\n", "A tuple is similar to a list in that it's an ordered sequence of elements. However, tuples can't be changed once created (they are \"immutable\"). Tuples are created by separating values with a comma (and for clarity these are commonly surrounded by parentheses). " ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "a_tuple = (1, 2, 3)\n", "another_tuple = ('blue', 'green', 'red')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> ## Challenge - Tuples\n", "> 1. Type `type(a_tuple)` into Python - what is the object type?\n", "> 2. What happens when you type `a_tuple[2] = 5` vs `planets[1] = 5` ?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Dictionaries\n", "\n", "A **dictionary** is a container that holds pairs of objects: keys and values." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'banana': 'yellow', 'strawberry': 'red'}" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fruit_colors = {'banana': 'yellow', 'strawberry': 'red'}\n", "fruit_colors" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Dictionaries work a lot like lists - except that they are indexed with *keys*. Think about a key as a unique identifier for a set of values in the dictionary. Keys can only have particular types - they have to be \"hashable\". Strings and numeric types are acceptable, but lists aren't." ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'yellow'" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fruit_colors['banana']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To add an item to the dictionary, a value is assigned to a new dictionary key." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'banana': 'yellow', 'strawberry': 'red', 'apple': 'green'}" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fruit_colors['apple'] = 'green'\n", "fruit_colors" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using loops with dictionaries iterates over the keys by default." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "banana yellow\n", "strawberry red\n", "apple green\n" ] } ], "source": [ "for fruit in fruit_colors:\n", " print(fruit, fruit_colors[fruit])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Trying to use a non-existing key, e.g. from typo, throws an error message." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`fruit_colors['bannana']`\n", "\n", "```\n", "---------------------------------------------------------------------------\n", "KeyError Traceback (most recent call last)\n", " in ()\n", "----> 1 fruit_colors['bannana']\n", "\n", "KeyError: 'bannana'\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "An error message is commonly referred to as a \"traceback\". This message pinpoints what line in the code cell resulted in an error when it was executed, by pointing at it with an arrow (`---->`). This is helpful in figuring out what went wrong, especially when many lines of code are executed simultaneously." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> ## Challenge - Can you do reassignment in a dictionary?\n", ">\n", "> 1. In the `fruit_colors` dictionary, change the color of `apple` to `'red'`.\n", "> 2. Loop through the `fruit_colors` dictionary and print the key only **if** the value of that key points to in the dictionary is `'red'`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Functions\n", "\n", "Defining a section of code as a function in Python is done using the `def`\n", "keyword. For example, let's create a function that takes two arguments and returns their sum:" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "42" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def add_function(a, b):\n", " \"\"\"This function adds two values together\"\"\"\n", " result = a + b\n", " return result\n", "\n", "z = add_function(20, 22)\n", "z" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There's already a built-in `sum()` function in Python so `add_function` isn't all that useful, but functions can be created to do many custom things. In general, if you find yourself doing the same steps over and over, it might be a good idea to make a function." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Just as previously, the `?` can be used to get help for the function." ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "\u001b[0;31mSignature:\u001b[0m \u001b[0madd_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mDocstring:\u001b[0m This function adds two values together\n", "\u001b[0;31mFile:\u001b[0m ~/Documents/GitHub/python-workshop/\n", "\u001b[0;31mType:\u001b[0m function\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "?add_function" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The string between the `\"\"\"` is called the docstring and is shown in the help message, so it is important to write a clear description of the function here. It is possible to see the entire source code of the function by using double `?` (this can be quite complex for complicated functions)." ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\u001b[0;31mSignature:\u001b[0m \u001b[0madd_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mSource:\u001b[0m \n", "\u001b[0;32mdef\u001b[0m \u001b[0madd_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0;34m\"\"\"This function adds two values together\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mFile:\u001b[0m ~/Documents/GitHub/python-workshop/\n", "\u001b[0;31mType:\u001b[0m function\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "??add_function" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Much of the power from languages such as Python and R comes from community contributed functions written by talented people and shared openly so that anyone can use them for their own research instead of reinventing the wheel. These community contributions are often packaged together in so called packages, libraries, or modules, which often consists of a set of related functions that are helpful to carry out a particular task. Packages will be covered more in detail later." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Part 2: working with data\n", "\n", "Now that we've seen some Python commands and syntax, let's work with some real data. For the rest of the workshop, we'll be going through an example analysis and visualization pipeline with some data on bicycle counts from the City of Toronto." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We won't talk too much about spreadsheets specifically, but Python isn't necessarily a replacement for spreadsheets - they are still useful, especially for entering data. If you'd like more information and guidelines about best practices for using spreadsheets, there's short Data Carpentry module that covers this: https://datacarpentry.org/spreadsheet-ecology-lesson/. \n", "\n", "There are a few data organization principles for spreadsheets that make it much easier to use data programatically with a tool like Python. From the [Data Carpentry spreadsheets lesson](https://datacarpentry.org/spreadsheet-ecology-lesson/), here are the cardinal rules of using spreadsheet programs for data:\n", "\n", "1. Put all your variables in columns - the thing you’re measuring, like ‘weight’ or ‘temperature’.\n", "2. Put each observation in its own row. \n", "**Columns = variables, rows = observations, cells = data values.**\n", "3. Don’t combine multiple pieces of information in one cell. Sometimes it just seems like one thing, but think if that’s the only way you’ll want to be able to use or sort that data.\n", "4. Leave the raw data raw - don’t change it!\n", "5. Export the cleaned data to a text-based format like CSV (comma-separated values) format. This ensures that anyone can use the data, and is required by most data repositories." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Dataset background\n", "\n", "We will be using data from the City of Toronto [Open Data Catalogue](https://www.toronto.ca/city-government/data-research-maps/open-data/open-data-catalogue/), a great resource with lots of publicly available data. Specifically, we will be analyzing [counts of bicycles](https://www.toronto.ca/city-government/data-research-maps/open-data/open-data-catalogue/#7e3a3b94-92d8-2932-2c59-2c88a6cc0f3f) from the College St. bikelanes in September 2010 and September 2017. \n", "\n", "Here's what the data looked like when I downloaded it from the City. Can anyone see any violations of the principles we just discussed? How should the data have been formatted differently when it was entered and saved?\n", "\n", "![](img/college_spadina_excel_screenshot.bmp)\n", "\n", "Because the original data looked like this and would have been tricky to analyze in an automated way, I made a [new file](https://bit.ly/2KiOHxV) in which each count observation had its own row.\n", "\n", "The data can be downloaded directly at this link: https://bit.ly/2Cs1Mq1 or https://gist.githubusercontent.com/mbonsma/be7482639d7a2d5cfc52505aadb9b53e/raw/1f68fce4a127fdd3b2313728dd84cf21e86e7df3/college_spadina_2010_2017.csv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Data format\n", "\n", "We are studying the number of cyclists counted each hour on a series \n", "of dates in September 2010 and September 2017. The dataset is stored \n", "as a comma separated value (CSV) file. Each row\n", "holds information for a single hour of counts, and the columns are described below.\n", "\n", "| Column | Description |\n", "|------------------|--------------------------------------------------------------|\n", "| date | date of the count |\n", "| day_of_week | day of the week, i.e. Saturday |\n", "| temperature | temperature (C) |\n", "| weather | amount of rain |\n", "| direction | direction of travel of bicycle (Eastbound or Westbound) |\n", "| position | recording position, if given |\n", "| hour | start time of hour-long counting block |\n", "| bikes | number of bicycles counted |\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To read the data into Python, we are going to use a function called `read_csv`. This function is contained in a Python package called [`pandas`](https://pandas.pydata.org/). As mentioned previously, Python packages are a bit like browser extensions: they are not essential, but can provide nifty functionality. To use a package, it first needs to be imported." ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "# pandas is commonly given the nickname `pd`\n", "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`pandas` can read CSV-files saved on the computer or directly from an URL." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "bike_counts = pd.read_csv(\"https://bit.ly/2Cs1Mq1\")\n", "# you can also read a file that's already on your computer: \n", "# bike_counts = pd.read_csv(\"college_spadina_2010_2017.csv\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To view the result, type `bike_counts` in a cell and run it, just as when viewing the content of any variable in Python." ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikes
09/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.12:00:00 AM70
19/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.1:00:00 AM27
29/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM23
39/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM8
49/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM10
59/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.5:00:00 AM3
69/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.6:00:00 AM3
79/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.7:00:00 AM16
89/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.8:00:00 AM28
99/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.9:00:00 AM28
109/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.10:00:00 AM43
119/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.11:00:00 AM75
129/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.12:00:00 PM77
139/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.1:00:00 PM105
149/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.2:00:00 PM85
159/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 PM109
169/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 PM106
179/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.5:00:00 PM123
189/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.6:00:00 PM103
199/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.7:00:00 PM74
209/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.8:00:00 PM78
219/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.9:00:00 PM43
229/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.10:00:00 PM37
239/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.11:00:00 PM64
249/18/10Saturday21No RainEastboundBike lane just west of Spadina Ave.12:00:00 AM34
259/18/10Saturday21No RainEastboundBike lane just west of Spadina Ave.1:00:00 AM38
269/18/10Saturday21No RainEastboundBike lane just west of Spadina Ave.2:00:00 AM16
279/18/10Saturday21No RainEastboundBike lane just west of Spadina Ave.3:00:00 AM19
289/18/10Saturday21No RainEastboundBike lane just west of Spadina Ave.4:00:00 AM7
299/18/10Saturday21No RainEastboundBike lane just west of Spadina Ave.5:00:00 AM6
...........................
5942017-09-30Saturday15No RainEastboundNaN6:00 PM90
5952017-09-30Saturday15No RainEastboundNaN7:00 PM90
5962017-09-30Saturday15No RainEastboundNaN8:00 PM77
5972017-09-30Saturday15No RainEastboundNaN9:00 PM79
5982017-09-30Saturday15No RainEastboundNaN10:00 PM85
5992017-09-30Saturday15No RainEastboundNaN11:00 PM58
6002017-09-30Saturday15No RainWestboundNaN12:00 AM33
6012017-09-30Saturday15No RainWestboundNaN1:00 AM13
6022017-09-30Saturday15No RainWestboundNaN2:00 AM11
6032017-09-30Saturday15No RainWestboundNaN3:00 AM6
6042017-09-30Saturday15No RainWestboundNaN4:00 AM4
6052017-09-30Saturday15No RainWestboundNaN5:00 AM7
6062017-09-30Saturday15No RainWestboundNaN6:00 AM6
6072017-09-30Saturday15No RainWestboundNaN7:00 AM14
6082017-09-30Saturday15No RainWestboundNaN8:00 AM22
6092017-09-30Saturday15No RainWestboundNaN9:00 AM37
6102017-09-30Saturday15No RainWestboundNaN10:00 AM48
6112017-09-30Saturday15No RainWestboundNaN11:00 AM89
6122017-09-30Saturday15No RainWestboundNaN12:00 PM100
6132017-09-30Saturday15No RainWestboundNaN1:00 PM96
6142017-09-30Saturday15No RainWestboundNaN2:00 PM109
6152017-09-30Saturday15No RainWestboundNaN3:00 PM114
6162017-09-30Saturday15No RainWestboundNaN4:00 PM132
6172017-09-30Saturday15No RainWestboundNaN5:00 PM136
6182017-09-30Saturday15No RainWestboundNaN6:00 PM120
6192017-09-30Saturday15No RainWestboundNaN7:00 PM98
6202017-09-30Saturday15No RainWestboundNaN8:00 PM79
6212017-09-30Saturday15No RainWestboundNaN9:00 PM62
6222017-09-30Saturday15No RainWestboundNaN10:00 PM80
6232017-09-30Saturday15No RainWestboundNaN11:00 PM82
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624 rows × 8 columns

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" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "0 9/18/10 Saturday 21 No Rain Westbound \n", "1 9/18/10 Saturday 21 No Rain Westbound \n", "2 9/18/10 Saturday 21 No Rain Westbound \n", "3 9/18/10 Saturday 21 No Rain Westbound \n", "4 9/18/10 Saturday 21 No Rain Westbound \n", "5 9/18/10 Saturday 21 No Rain Westbound \n", "6 9/18/10 Saturday 21 No Rain Westbound \n", "7 9/18/10 Saturday 21 No Rain Westbound \n", "8 9/18/10 Saturday 21 No Rain Westbound \n", "9 9/18/10 Saturday 21 No Rain Westbound \n", "10 9/18/10 Saturday 21 No Rain Westbound \n", "11 9/18/10 Saturday 21 No Rain Westbound \n", "12 9/18/10 Saturday 21 No Rain Westbound \n", "13 9/18/10 Saturday 21 No Rain Westbound \n", "14 9/18/10 Saturday 21 No Rain Westbound \n", "15 9/18/10 Saturday 21 No Rain Westbound \n", "16 9/18/10 Saturday 21 No Rain Westbound \n", "17 9/18/10 Saturday 21 No Rain Westbound \n", "18 9/18/10 Saturday 21 No Rain Westbound \n", "19 9/18/10 Saturday 21 No Rain Westbound \n", "20 9/18/10 Saturday 21 No Rain Westbound \n", "21 9/18/10 Saturday 21 No Rain Westbound \n", "22 9/18/10 Saturday 21 No Rain Westbound \n", "23 9/18/10 Saturday 21 No Rain Westbound \n", "24 9/18/10 Saturday 21 No Rain Eastbound \n", "25 9/18/10 Saturday 21 No Rain Eastbound \n", "26 9/18/10 Saturday 21 No Rain Eastbound \n", "27 9/18/10 Saturday 21 No Rain Eastbound \n", "28 9/18/10 Saturday 21 No Rain Eastbound \n", "29 9/18/10 Saturday 21 No Rain Eastbound \n", ".. ... ... ... ... ... \n", "594 2017-09-30 Saturday 15 No Rain Eastbound \n", "595 2017-09-30 Saturday 15 No Rain Eastbound \n", "596 2017-09-30 Saturday 15 No Rain Eastbound \n", "597 2017-09-30 Saturday 15 No Rain Eastbound \n", "598 2017-09-30 Saturday 15 No Rain Eastbound \n", "599 2017-09-30 Saturday 15 No Rain Eastbound \n", "600 2017-09-30 Saturday 15 No Rain Westbound \n", "601 2017-09-30 Saturday 15 No Rain Westbound \n", "602 2017-09-30 Saturday 15 No Rain Westbound \n", "603 2017-09-30 Saturday 15 No Rain Westbound \n", "604 2017-09-30 Saturday 15 No Rain Westbound \n", "605 2017-09-30 Saturday 15 No Rain Westbound \n", "606 2017-09-30 Saturday 15 No Rain Westbound \n", "607 2017-09-30 Saturday 15 No Rain Westbound \n", "608 2017-09-30 Saturday 15 No Rain Westbound \n", "609 2017-09-30 Saturday 15 No Rain Westbound \n", "610 2017-09-30 Saturday 15 No Rain Westbound \n", "611 2017-09-30 Saturday 15 No Rain Westbound \n", "612 2017-09-30 Saturday 15 No Rain Westbound \n", "613 2017-09-30 Saturday 15 No Rain Westbound \n", "614 2017-09-30 Saturday 15 No Rain Westbound \n", "615 2017-09-30 Saturday 15 No Rain Westbound \n", "616 2017-09-30 Saturday 15 No Rain Westbound \n", "617 2017-09-30 Saturday 15 No Rain Westbound \n", "618 2017-09-30 Saturday 15 No Rain Westbound \n", "619 2017-09-30 Saturday 15 No Rain Westbound \n", "620 2017-09-30 Saturday 15 No Rain Westbound \n", "621 2017-09-30 Saturday 15 No Rain Westbound \n", "622 2017-09-30 Saturday 15 No Rain Westbound \n", "623 2017-09-30 Saturday 15 No Rain Westbound \n", "\n", " position hour bikes \n", "0 Bike lane just east of Spadina Ave. 12:00:00 AM 70 \n", "1 Bike lane just east of Spadina Ave. 1:00:00 AM 27 \n", "2 Bike lane just east of Spadina Ave. 2:00:00 AM 23 \n", "3 Bike lane just east of Spadina Ave. 3:00:00 AM 8 \n", "4 Bike lane just east of Spadina Ave. 4:00:00 AM 10 \n", "5 Bike lane just east of Spadina Ave. 5:00:00 AM 3 \n", "6 Bike lane just east of Spadina Ave. 6:00:00 AM 3 \n", "7 Bike lane just east of Spadina Ave. 7:00:00 AM 16 \n", "8 Bike lane just east of Spadina Ave. 8:00:00 AM 28 \n", "9 Bike lane just east of Spadina Ave. 9:00:00 AM 28 \n", "10 Bike lane just east of Spadina Ave. 10:00:00 AM 43 \n", "11 Bike lane just east of Spadina Ave. 11:00:00 AM 75 \n", "12 Bike lane just east of Spadina Ave. 12:00:00 PM 77 \n", "13 Bike lane just east of Spadina Ave. 1:00:00 PM 105 \n", "14 Bike lane just east of Spadina Ave. 2:00:00 PM 85 \n", "15 Bike lane just east of Spadina Ave. 3:00:00 PM 109 \n", "16 Bike lane just east of Spadina Ave. 4:00:00 PM 106 \n", "17 Bike lane just east of Spadina Ave. 5:00:00 PM 123 \n", "18 Bike lane just east of Spadina Ave. 6:00:00 PM 103 \n", "19 Bike lane just east of Spadina Ave. 7:00:00 PM 74 \n", "20 Bike lane just east of Spadina Ave. 8:00:00 PM 78 \n", "21 Bike lane just east of Spadina Ave. 9:00:00 PM 43 \n", "22 Bike lane just east of Spadina Ave. 10:00:00 PM 37 \n", "23 Bike lane just east of Spadina Ave. 11:00:00 PM 64 \n", "24 Bike lane just west of Spadina Ave. 12:00:00 AM 34 \n", "25 Bike lane just west of Spadina Ave. 1:00:00 AM 38 \n", "26 Bike lane just west of Spadina Ave. 2:00:00 AM 16 \n", "27 Bike lane just west of Spadina Ave. 3:00:00 AM 19 \n", "28 Bike lane just west of Spadina Ave. 4:00:00 AM 7 \n", "29 Bike lane just west of Spadina Ave. 5:00:00 AM 6 \n", ".. ... ... ... \n", "594 NaN 6:00 PM 90 \n", "595 NaN 7:00 PM 90 \n", "596 NaN 8:00 PM 77 \n", "597 NaN 9:00 PM 79 \n", "598 NaN 10:00 PM 85 \n", "599 NaN 11:00 PM 58 \n", "600 NaN 12:00 AM 33 \n", "601 NaN 1:00 AM 13 \n", "602 NaN 2:00 AM 11 \n", "603 NaN 3:00 AM 6 \n", "604 NaN 4:00 AM 4 \n", "605 NaN 5:00 AM 7 \n", "606 NaN 6:00 AM 6 \n", "607 NaN 7:00 AM 14 \n", "608 NaN 8:00 AM 22 \n", "609 NaN 9:00 AM 37 \n", "610 NaN 10:00 AM 48 \n", "611 NaN 11:00 AM 89 \n", "612 NaN 12:00 PM 100 \n", "613 NaN 1:00 PM 96 \n", "614 NaN 2:00 PM 109 \n", "615 NaN 3:00 PM 114 \n", "616 NaN 4:00 PM 132 \n", "617 NaN 5:00 PM 136 \n", "618 NaN 6:00 PM 120 \n", "619 NaN 7:00 PM 98 \n", "620 NaN 8:00 PM 79 \n", "621 NaN 9:00 PM 62 \n", "622 NaN 10:00 PM 80 \n", "623 NaN 11:00 PM 82 \n", "\n", "[624 rows x 8 columns]" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is how a data frame is displayed in the JupyterLab Notebook. Although the data frame itself just consists of the values, the Notebook knows that this is a data frame and displays it in a nice tabular format (by adding HTML decorators), and adds some cosmetic conveniences such as the bold font type for the column and row names, the alternating grey and white zebra stripes for the rows and highlights the row the mouse pointer moves over. The increasing numbers on the far left is the data frame's index, which was added by `pandas` to easily distinguish between the rows.\n", "\n", "## What are data frames?\n", "\n", "A data frame is the representation of data in a tabular format, similar to how data is often arranged in spreadsheets. The data is rectangular, meaning that all rows have the same amount of columns and all columns have the same amount of rows. Data frames are the *de facto* data structure for most tabular data, and what we use for statistics and plotting. A data frame can be created by hand, but most commonly they are generated by an input function, such as `read_csv()`. In other words, when importing spreadsheets from your hard drive (or the web).\n", "\n", "As can be seen above, the default is to display the first and last 30 rows and truncate everything in between, as indicated by the ellipsis (`...`). Although it is truncated, this output is still quite space consuming. To glance at how the data frame looks, it is sufficient to display only the top (the first 5 lines) using the `head()` method.\n" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikes
09/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.12:00:00 AM70
19/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.1:00:00 AM27
29/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM23
39/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM8
49/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM10
\n", "
" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "0 9/18/10 Saturday 21 No Rain Westbound \n", "1 9/18/10 Saturday 21 No Rain Westbound \n", "2 9/18/10 Saturday 21 No Rain Westbound \n", "3 9/18/10 Saturday 21 No Rain Westbound \n", "4 9/18/10 Saturday 21 No Rain Westbound \n", "\n", " position hour bikes \n", "0 Bike lane just east of Spadina Ave. 12:00:00 AM 70 \n", "1 Bike lane just east of Spadina Ave. 1:00:00 AM 27 \n", "2 Bike lane just east of Spadina Ave. 2:00:00 AM 23 \n", "3 Bike lane just east of Spadina Ave. 3:00:00 AM 8 \n", "4 Bike lane just east of Spadina Ave. 4:00:00 AM 10 " ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Methods are very similar to functions; the main difference is that they belong to an object (above, the method `head()` belongs to the data frame `bike_counts`). Methods operate on the object they belong to, that's why we can call the method with an empty parenthesis without any arguments. Compare this with the function `type()` that was introduced previously." ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.frame.DataFrame" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(bike_counts)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here, the `bike_counts` variable is explicitly passed as an argument to `type()`. An immediately tangible advantage with methods is that they simplify tab completion. Just type the name of the dataframe, a period, and then hit tab to see all the relevant methods for that data frame instead of fumbling around with all the available functions in Python (there's quite a few!) and figuring out which ones operate on data frames and which do not. Methods also facilitates readability when chaining many operations together, which will be shown in detail later.\n", "\n", "The columns in a data frame can contain data of different types, e.g. integers, floats, and objects (which includes strings, lists, dictionaries, and more)). General information about the data frame (including the column data types) can be obtained with the `info()` method." ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 624 entries, 0 to 623\n", "Data columns (total 8 columns):\n", "date 624 non-null object\n", "day_of_week 624 non-null object\n", "temperature 624 non-null int64\n", "weather 624 non-null object\n", "direction 624 non-null object\n", "position 432 non-null object\n", "hour 624 non-null object\n", "bikes 624 non-null int64\n", "dtypes: int64(2), object(6)\n", "memory usage: 39.1+ KB\n" ] } ], "source": [ "bike_counts.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The information includes the total number of rows and columns, the number of non-null observations, the column data types, and the memory (RAM) usage. The number of non-null observation is not the same for all columns, which means that some columns contain null (or NA) values representing that there is missing information. The column data type is often indicative of which type of data is stored in that column, and approximately corresponds to the following\n", "\n", "- **Qualitative/Categorical**\n", " - Nominal (labels, e.g. 'red', 'green', 'blue')\n", " - `object`, `category`\n", " - Ordinal (labels with order, e.g. 'Jan', 'Feb', 'Mar')\n", " - `object`, `category`, `int`\n", " - Binary (only two outcomes, e.g. True or False)\n", " - `bool`\n", "- **Quantitative/Numerical**\n", " - Discrete (whole numbers, often counting, e.g. number of children)\n", " - `int`\n", " - Continuous (measured values with decimals, e.g. weight)\n", " - `float`\n", " \n", "Note that an `object` could contain different types, e.g. `str` or `list`. Also note that there can be exceptions to the schema above, but it is still a useful rough guide.\n", "\n", "After reading in the data into a data frame, `head()` and `info()` are two of the most useful methods to get an idea of the structure of this data frame. There are many additional methods that can facilitate the understanding of what a data frame contains:\n", "\n", "- Size:\n", " - `bike_counts.shape` - a tuple with the number of rows in the first element\n", " and the number of columns as the second element\n", " - `bike_counts.shape[0]` - the number of rows\n", " - `bike_counts.shape[1]`- the number of columns\n", "\n", "- Content:\n", " - `bike_counts.head()` - shows the first 5 rows\n", " - `bike_counts.tail()` - shows the last 5 rows\n", "\n", "- Names:\n", " - `bike_counts.columns` - returns the names of the columns (also called variable names) \n", " objects)\n", " - `bike_counts.index` - returns the names of the rows (referred to as the index in pandas)\n", "\n", "- Summary:\n", " - `bike_counts.info()` - column names and data types, number of observations, memory consumptions\n", " length, and content of each column\n", " - `bike_counts.describe()` - summary statistics for each column\n", "\n", "These belong to a data frame and are commonly referred to as *attributes* of the data frame. All attributes are accessed with the dot-syntax (`.`), which returns the attribute's value. If the attribute is a method, parentheses can be appended to the name to carry out the method's operation on the data frame. Attributes that are not methods often hold a value that has been precomputed because it is commonly accessed and it saves time to store the value in an attribute instead of recomputing it every time it is needed. For example, every time `pandas` creates a data frame, the number of rows and columns is computed and stored in the `shape` attribute." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">\n", ">Based on the output of `bike_counts.info()`, can you answer the following questions?\n", ">\n", ">* What is the class of the object `bike_counts`?\n", ">* How many rows and how many columns are in this object?\n", ">* Why is there not the same number of rows (observations) for each column?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Saving data frames locally\n", "\n", "It is good practice to keep a copy of the data stored locally on your computer in case you want to do offline analyses, the online version of the file changes, or the file is taken down. For this, the data could be downloaded manually or the current `bike_counts` data frame could be saved to disk as a CSV-file with `to_csv()`." ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": [ "bike_counts.to_csv('bike_counts.csv', index=False)\n", "# `index=False` because the index (the row names) was generated automatically when pandas opened\n", "# the file and this information is not needed to be saved" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since the data is now saved locally, the next time this Notebook is opened, it could be loaded from the local path instead of downloading it from the URL." ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikes
09/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.12:00:00 AM70
19/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.1:00:00 AM27
29/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM23
39/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM8
49/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM10
\n", "
" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "0 9/18/10 Saturday 21 No Rain Westbound \n", "1 9/18/10 Saturday 21 No Rain Westbound \n", "2 9/18/10 Saturday 21 No Rain Westbound \n", "3 9/18/10 Saturday 21 No Rain Westbound \n", "4 9/18/10 Saturday 21 No Rain Westbound \n", "\n", " position hour bikes \n", "0 Bike lane just east of Spadina Ave. 12:00:00 AM 70 \n", "1 Bike lane just east of Spadina Ave. 1:00:00 AM 27 \n", "2 Bike lane just east of Spadina Ave. 2:00:00 AM 23 \n", "3 Bike lane just east of Spadina Ave. 3:00:00 AM 8 \n", "4 Bike lane just east of Spadina Ave. 4:00:00 AM 10 " ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts = pd.read_csv('bike_counts.csv')\n", "bike_counts.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Indexing and subsetting data frames\n", "\n", "The bike counts data frame has rows and columns (it has 2 dimensions). To extract specific data from it (also referred to as \"subsetting\"), columns can be selected by their name.The JupyterLab Notebook (technically, the underlying IPython interpreter) knows about the columns in the data frame, so tab autocompletion can be used to get the correct column name. " ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 No Rain\n", "1 No Rain\n", "2 No Rain\n", "3 No Rain\n", "4 No Rain\n", "Name: weather, dtype: object" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts['weather'].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The name of the column is not shown, since there is only one. Remember that the numbers on the left is just the index of the data frame, which was added by `pandas` upon importing the data.\n", "\n", "Another syntax that is often used to specify column names is `.`." ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 No Rain\n", "1 No Rain\n", "2 No Rain\n", "3 No Rain\n", "4 No Rain\n", "Name: weather, dtype: object" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.weather.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using brackets is clearer and also alows for passing multiple columns as a list, so this tutorial will stick to that." ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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09/18/10No Rain
19/18/10No Rain
29/18/10No Rain
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" ], "text/plain": [ " date weather\n", "0 9/18/10 No Rain\n", "1 9/18/10 No Rain\n", "2 9/18/10 No Rain\n", "3 9/18/10 No Rain\n", "4 9/18/10 No Rain" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts[['date', 'weather']].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The output is displayed a bit differently this time. The reason is that in the last cell where the returned data frame only had one column (\"weather\"), `pandas` technically returned a `Series`, not a `Dataframe`. This can be confirmed by using `type` as previously." ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.series.Series" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(bike_counts['weather'].head())" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.frame.DataFrame" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(bike_counts[['date', 'weather']].head())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, every individual column is actually a `Series` and together they constitue a `Dataframe`. This introductory tutorial will not make any further distinction between a `Series` and a `Dataframe`, and many of the analysis techniques used here will apply to both series and data frames." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Selecting with single brackets (`[]`) is a shortcut to common operations, such as selecting columns by labels as above. For more flexible and robust row and column selection the more verbose `loc[, ]` (location) syntax is used." ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateweather
09/18/10No Rain
29/18/10No Rain
49/18/10No Rain
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" ], "text/plain": [ " date weather\n", "0 9/18/10 No Rain\n", "2 9/18/10 No Rain\n", "4 9/18/10 No Rain" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[[0, 2, 4], ['date', 'weather']]\n", "# Although methods usually have trailing parenthesis, square brackets are used with `loc[]` to stay\n", "# consistent with the indexing with square brackets in general in Python (e.g. lists and Numpy arrays)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A single number can be selected, which returns that value (here, an integer) rather than a data frame or series with just one value." ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Saturday'" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[4, 'day_of_week']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If the column argument is is left out, all columns are selected." ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikes
39/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM8
49/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM10
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" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "3 9/18/10 Saturday 21 No Rain Westbound \n", "4 9/18/10 Saturday 21 No Rain Westbound \n", "\n", " position hour bikes \n", "3 Bike lane just east of Spadina Ave. 3:00:00 AM 8 \n", "4 Bike lane just east of Spadina Ave. 4:00:00 AM 10 " ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[[3, 4]]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To select all rows, but only a subset of columns, the colon character (`:`) can be used." ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(624, 2)" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[:, ['date', 'day_of_week']].shape # show the size of the data frame" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is also possible to select slices of rows and column labels." ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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day_of_weektemperatureweatherdirectionposition
2Saturday21No RainWestboundBike lane just east of Spadina Ave.
3Saturday21No RainWestboundBike lane just east of Spadina Ave.
4Saturday21No RainWestboundBike lane just east of Spadina Ave.
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" ], "text/plain": [ " day_of_week temperature weather direction \\\n", "2 Saturday 21 No Rain Westbound \n", "3 Saturday 21 No Rain Westbound \n", "4 Saturday 21 No Rain Westbound \n", "\n", " position \n", "2 Bike lane just east of Spadina Ave. \n", "3 Bike lane just east of Spadina Ave. \n", "4 Bike lane just east of Spadina Ave. " ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[2:4, 'day_of_week':'position']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is important to realize that `loc[]` selects rows and columns by their *labels*. To instead select by row or column *position*, use `iloc[]` (integer location)." ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperature
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" ], "text/plain": [ " date day_of_week temperature\n", "2 9/18/10 Saturday 21\n", "3 9/18/10 Saturday 21\n", "4 9/18/10 Saturday 21" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.iloc[[2, 3, 4], [0, 1, 2]]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The index of `surveys` consists of consecutive integers so in this case selecting from the index by labels or position will look the same. An index could also consist of text names just like the columns.\n", "\n", "While selecting a slice by label is inclusive of the start and end, selecting a slice by position is inclusive of the start by exclusive of the end position, just like when slicing in lists." ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperature
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" ], "text/plain": [ " date day_of_week temperature\n", "2 9/18/10 Saturday 21\n", "3 9/18/10 Saturday 21\n", "4 9/18/10 Saturday 21" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.iloc[2:5, :3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Selecting slices of row positions is a common operation, and has thus been given a shortcut syntax with single brackets." ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikes
29/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM23
39/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM8
49/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM10
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" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "2 9/18/10 Saturday 21 No Rain Westbound \n", "3 9/18/10 Saturday 21 No Rain Westbound \n", "4 9/18/10 Saturday 21 No Rain Westbound \n", "\n", " position hour bikes \n", "2 Bike lane just east of Spadina Ave. 2:00:00 AM 23 \n", "3 Bike lane just east of Spadina Ave. 3:00:00 AM 8 \n", "4 Bike lane just east of Spadina Ave. 4:00:00 AM 10 " ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts[2:5]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">\n", ">1. Extract the 200th and 201st row of the `bike_counts` dataset and assign the resulting data frame to a new variable name (`bike_counts_200_201`). Remember that Python indexing starts at 0!\n", ">\n", ">2. How can you get the same result as from `bike_counts.head()` by using row slices instead of the `head()` method?\n", ">\n", ">3. There are at least three distinct ways to extract the last row of the data frame. How many can you come up with?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `describe()` method was mentioned above as a way of retrieving summary statistics of a data frame. Together with `info()` and `head()` this is often a good place to start exploratory data analysis as it gives a nice overview of the numeric valuables the data set. It's a good way to check things such as if the max and min values make sense for a particular column." ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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temperaturebikes
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mean21.07692381.134615
std4.51789978.900314
min15.0000000.000000
25%18.00000021.000000
50%19.00000066.000000
75%23.000000113.000000
max30.000000511.000000
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" ], "text/plain": [ " temperature bikes\n", "count 624.000000 624.000000\n", "mean 21.076923 81.134615\n", "std 4.517899 78.900314\n", "min 15.000000 0.000000\n", "25% 18.000000 21.000000\n", "50% 19.000000 66.000000\n", "75% 23.000000 113.000000\n", "max 30.000000 511.000000" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A common next step would be to plot the data to explore relationships between different variables, but before getting into plotting, it is beneficial to elaborate on the data frame object and several of its common operations.\n", "\n", "An often desired outcome is to select a subset of rows matching a criteria, e.g. which observations have a bike count under 5. To do this, the \"less than\" comparison operator that was introduced previously can be used." ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 False\n", "1 False\n", "2 False\n", "3 False\n", "4 False\n", "5 True\n", "6 True\n", "7 False\n", "8 False\n", "9 False\n", "10 False\n", "11 False\n", "12 False\n", "13 False\n", "14 False\n", "15 False\n", "16 False\n", "17 False\n", "18 False\n", "19 False\n", "20 False\n", "21 False\n", "22 False\n", "23 False\n", "24 False\n", "25 False\n", "26 False\n", "27 False\n", "28 False\n", "29 False\n", " ... \n", "594 False\n", "595 False\n", "596 False\n", "597 False\n", "598 False\n", "599 False\n", "600 False\n", "601 False\n", "602 False\n", "603 False\n", "604 True\n", "605 False\n", "606 False\n", "607 False\n", "608 False\n", "609 False\n", "610 False\n", "611 False\n", "612 False\n", "613 False\n", "614 False\n", "615 False\n", "616 False\n", "617 False\n", "618 False\n", "619 False\n", "620 False\n", "621 False\n", "622 False\n", "623 False\n", "Name: bikes, Length: 624, dtype: bool" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts['bikes'] < 5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The result is a boolean array with one value for every row in the data frame indicating whether it is `True` or `False` that this row has a value below 5 in the bikes column. This boolean array can be used to select only those rows from the data frame that meet the specified condition." ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikes
59/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.5:00:00 AM3
69/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.6:00:00 AM3
539/25/10Saturday18No RainWestboundBike lane just east of Spadina Ave.5:00:00 AM3
549/25/10Saturday18No RainWestboundBike lane just east of Spadina Ave.6:00:00 AM3
1019/19/10Sunday20No RainWestboundBike lane just east of Spadina Ave.5:00:00 AM4
1259/19/10Sunday20No RainEastboundBike lane just west of Spadina Ave.5:00:00 AM3
1739/26/10Sunday17No RainEastboundBike lane just west of Spadina Ave.5:00:00 AM2
1919/26/10Sunday17No RainEastboundBike lane just west of Spadina Ave.11:00:00 PM4
1949/20/10Monday19No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM3
1959/20/10Monday19No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM2
1969/20/10Monday19No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM3
1979/20/10Monday19No RainWestboundBike lane just east of Spadina Ave.5:00:00 AM4
2189/20/10Monday19No RainEastboundBike lane just west of Spadina Ave.2:00:00 AM1
2199/20/10Monday19No RainEastboundBike lane just west of Spadina Ave.3:00:00 AM3
2209/20/10Monday19No RainEastboundBike lane just west of Spadina Ave.4:00:00 AM4
2429/21/10Tuesday25No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM3
2439/21/10Tuesday25No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM2
2449/21/10Tuesday25No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM0
2669/21/10Tuesday25No RainEastboundBike lane just west of Spadina Ave.2:00:00 AM3
2679/21/10Tuesday25No RainEastboundBike lane just west of Spadina Ave.3:00:00 AM2
2689/21/10Tuesday25No RainEastboundBike lane just west of Spadina Ave.4:00:00 AM4
2909/22/10Wednesday23Rain 6mmWestboundBike lane just east of Spadina Ave.2:00:00 AM3
2919/22/10Wednesday23Rain 6mmWestboundBike lane just east of Spadina Ave.3:00:00 AM3
2929/22/10Wednesday23Rain 6mmWestboundBike lane just east of Spadina Ave.4:00:00 AM0
2939/22/10Wednesday23Rain 6mmWestboundBike lane just east of Spadina Ave.5:00:00 AM4
3159/22/10Wednesday23Rain 6mmEastboundBike lane just west of Spadina Ave.3:00:00 AM4
3169/22/10Wednesday23Rain 6mmEastboundBike lane just west of Spadina Ave.4:00:00 AM4
3409/23/10Thursday19No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM0
3419/23/10Thursday19No RainWestboundBike lane just east of Spadina Ave.5:00:00 AM3
3649/23/10Thursday19No RainEastboundBike lane just west of Spadina Ave.4:00:00 AM4
3879/24/10Friday30No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM2
3889/24/10Friday30No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM1
4352017-09-27Wednesday30No RainEastboundNaN3:00 AM4
4592017-09-27Wednesday30No RainWestboundNaN3:00 AM2
4832017-09-28Thursday19No RainEastboundNaN3:00 AM3
5082017-09-28Thursday19No RainWestboundNaN4:00 AM4
5092017-09-28Thursday19No RainWestboundNaN5:00 AM2
5312017-09-29Friday18Rain 4mmEastboundNaN3:00 AM3
5562017-09-29Friday18Rain 4mmWestboundNaN4:00 AM4
5802017-09-30Saturday15No RainEastboundNaN4:00 AM2
6042017-09-30Saturday15No RainWestboundNaN4:00 AM4
\n", "
" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "5 9/18/10 Saturday 21 No Rain Westbound \n", "6 9/18/10 Saturday 21 No Rain Westbound \n", "53 9/25/10 Saturday 18 No Rain Westbound \n", "54 9/25/10 Saturday 18 No Rain Westbound \n", "101 9/19/10 Sunday 20 No Rain Westbound \n", "125 9/19/10 Sunday 20 No Rain Eastbound \n", "173 9/26/10 Sunday 17 No Rain Eastbound \n", "191 9/26/10 Sunday 17 No Rain Eastbound \n", "194 9/20/10 Monday 19 No Rain Westbound \n", "195 9/20/10 Monday 19 No Rain Westbound \n", "196 9/20/10 Monday 19 No Rain Westbound \n", "197 9/20/10 Monday 19 No Rain Westbound \n", "218 9/20/10 Monday 19 No Rain Eastbound \n", "219 9/20/10 Monday 19 No Rain Eastbound \n", "220 9/20/10 Monday 19 No Rain Eastbound \n", "242 9/21/10 Tuesday 25 No Rain Westbound \n", "243 9/21/10 Tuesday 25 No Rain Westbound \n", "244 9/21/10 Tuesday 25 No Rain Westbound \n", "266 9/21/10 Tuesday 25 No Rain Eastbound \n", "267 9/21/10 Tuesday 25 No Rain Eastbound \n", "268 9/21/10 Tuesday 25 No Rain Eastbound \n", "290 9/22/10 Wednesday 23 Rain 6mm Westbound \n", "291 9/22/10 Wednesday 23 Rain 6mm Westbound \n", "292 9/22/10 Wednesday 23 Rain 6mm Westbound \n", "293 9/22/10 Wednesday 23 Rain 6mm Westbound \n", "315 9/22/10 Wednesday 23 Rain 6mm Eastbound \n", "316 9/22/10 Wednesday 23 Rain 6mm Eastbound \n", "340 9/23/10 Thursday 19 No Rain Westbound \n", "341 9/23/10 Thursday 19 No Rain Westbound \n", "364 9/23/10 Thursday 19 No Rain Eastbound \n", "387 9/24/10 Friday 30 No Rain Westbound \n", "388 9/24/10 Friday 30 No Rain Westbound \n", "435 2017-09-27 Wednesday 30 No Rain Eastbound \n", "459 2017-09-27 Wednesday 30 No Rain Westbound \n", "483 2017-09-28 Thursday 19 No Rain Eastbound \n", "508 2017-09-28 Thursday 19 No Rain Westbound \n", "509 2017-09-28 Thursday 19 No Rain Westbound \n", "531 2017-09-29 Friday 18 Rain 4mm Eastbound \n", "556 2017-09-29 Friday 18 Rain 4mm Westbound \n", "580 2017-09-30 Saturday 15 No Rain Eastbound \n", "604 2017-09-30 Saturday 15 No Rain Westbound \n", "\n", " position hour bikes \n", "5 Bike lane just east of Spadina Ave. 5:00:00 AM 3 \n", "6 Bike lane just east of Spadina Ave. 6:00:00 AM 3 \n", "53 Bike lane just east of Spadina Ave. 5:00:00 AM 3 \n", "54 Bike lane just east of Spadina Ave. 6:00:00 AM 3 \n", "101 Bike lane just east of Spadina Ave. 5:00:00 AM 4 \n", "125 Bike lane just west of Spadina Ave. 5:00:00 AM 3 \n", "173 Bike lane just west of Spadina Ave. 5:00:00 AM 2 \n", "191 Bike lane just west of Spadina Ave. 11:00:00 PM 4 \n", "194 Bike lane just east of Spadina Ave. 2:00:00 AM 3 \n", "195 Bike lane just east of Spadina Ave. 3:00:00 AM 2 \n", "196 Bike lane just east of Spadina Ave. 4:00:00 AM 3 \n", "197 Bike lane just east of Spadina Ave. 5:00:00 AM 4 \n", "218 Bike lane just west of Spadina Ave. 2:00:00 AM 1 \n", "219 Bike lane just west of Spadina Ave. 3:00:00 AM 3 \n", "220 Bike lane just west of Spadina Ave. 4:00:00 AM 4 \n", "242 Bike lane just east of Spadina Ave. 2:00:00 AM 3 \n", "243 Bike lane just east of Spadina Ave. 3:00:00 AM 2 \n", "244 Bike lane just east of Spadina Ave. 4:00:00 AM 0 \n", "266 Bike lane just west of Spadina Ave. 2:00:00 AM 3 \n", "267 Bike lane just west of Spadina Ave. 3:00:00 AM 2 \n", "268 Bike lane just west of Spadina Ave. 4:00:00 AM 4 \n", "290 Bike lane just east of Spadina Ave. 2:00:00 AM 3 \n", "291 Bike lane just east of Spadina Ave. 3:00:00 AM 3 \n", "292 Bike lane just east of Spadina Ave. 4:00:00 AM 0 \n", "293 Bike lane just east of Spadina Ave. 5:00:00 AM 4 \n", "315 Bike lane just west of Spadina Ave. 3:00:00 AM 4 \n", "316 Bike lane just west of Spadina Ave. 4:00:00 AM 4 \n", "340 Bike lane just east of Spadina Ave. 4:00:00 AM 0 \n", "341 Bike lane just east of Spadina Ave. 5:00:00 AM 3 \n", "364 Bike lane just west of Spadina Ave. 4:00:00 AM 4 \n", "387 Bike lane just east of Spadina Ave. 3:00:00 AM 2 \n", "388 Bike lane just east of Spadina Ave. 4:00:00 AM 1 \n", "435 NaN 3:00 AM 4 \n", "459 NaN 3:00 AM 2 \n", "483 NaN 3:00 AM 3 \n", "508 NaN 4:00 AM 4 \n", "509 NaN 5:00 AM 2 \n", "531 NaN 3:00 AM 3 \n", "556 NaN 4:00 AM 4 \n", "580 NaN 4:00 AM 2 \n", "604 NaN 4:00 AM 4 " ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts[bike_counts['bikes'] < 5]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As before, this can be combined with selection of a particular set of columns." ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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hourbikes
55:00:00 AM3
66:00:00 AM3
535:00:00 AM3
546:00:00 AM3
1015:00:00 AM4
1255:00:00 AM3
1735:00:00 AM2
19111:00:00 PM4
1942:00:00 AM3
1953:00:00 AM2
1964:00:00 AM3
1975:00:00 AM4
2182:00:00 AM1
2193:00:00 AM3
2204:00:00 AM4
2422:00:00 AM3
2433:00:00 AM2
2444:00:00 AM0
2662:00:00 AM3
2673:00:00 AM2
2684:00:00 AM4
2902:00:00 AM3
2913:00:00 AM3
2924:00:00 AM0
2935:00:00 AM4
3153:00:00 AM4
3164:00:00 AM4
3404:00:00 AM0
3415:00:00 AM3
3644:00:00 AM4
3873:00:00 AM2
3884:00:00 AM1
4353:00 AM4
4593:00 AM2
4833:00 AM3
5084:00 AM4
5095:00 AM2
5313:00 AM3
5564:00 AM4
5804:00 AM2
6044:00 AM4
\n", "
" ], "text/plain": [ " hour bikes\n", "5 5:00:00 AM 3\n", "6 6:00:00 AM 3\n", "53 5:00:00 AM 3\n", "54 6:00:00 AM 3\n", "101 5:00:00 AM 4\n", "125 5:00:00 AM 3\n", "173 5:00:00 AM 2\n", "191 11:00:00 PM 4\n", "194 2:00:00 AM 3\n", "195 3:00:00 AM 2\n", "196 4:00:00 AM 3\n", "197 5:00:00 AM 4\n", "218 2:00:00 AM 1\n", "219 3:00:00 AM 3\n", "220 4:00:00 AM 4\n", "242 2:00:00 AM 3\n", "243 3:00:00 AM 2\n", "244 4:00:00 AM 0\n", "266 2:00:00 AM 3\n", "267 3:00:00 AM 2\n", "268 4:00:00 AM 4\n", "290 2:00:00 AM 3\n", "291 3:00:00 AM 3\n", "292 4:00:00 AM 0\n", "293 5:00:00 AM 4\n", "315 3:00:00 AM 4\n", "316 4:00:00 AM 4\n", "340 4:00:00 AM 0\n", "341 5:00:00 AM 3\n", "364 4:00:00 AM 4\n", "387 3:00:00 AM 2\n", "388 4:00:00 AM 1\n", "435 3:00 AM 4\n", "459 3:00 AM 2\n", "483 3:00 AM 3\n", "508 4:00 AM 4\n", "509 5:00 AM 2\n", "531 3:00 AM 3\n", "556 4:00 AM 4\n", "580 4:00 AM 2\n", "604 4:00 AM 4" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[bike_counts['bikes'] < 5, ['hour', 'bikes']]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "All of the bike counts that are less than 5 happened at night, between 11 PM and 6 AM." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A single expression can also be used to filter for several criteria, either matching *all* criteria (`&`) or *any* criteria (`|`). These special operators are used instead of `and` and `or` to make sure that the comparison occurs for each row in the data frame. Parentheses are added to indicate the priority of the comparisons." ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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day_of_weekdirection
24SaturdayEastbound
25SaturdayEastbound
26SaturdayEastbound
27SaturdayEastbound
28SaturdayEastbound
\n", "
" ], "text/plain": [ " day_of_week direction\n", "24 Saturday Eastbound\n", "25 Saturday Eastbound\n", "26 Saturday Eastbound\n", "27 Saturday Eastbound\n", "28 Saturday Eastbound" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# AND = &\n", "bike_counts.loc[(bike_counts['day_of_week'] == 'Saturday') & \n", " (bike_counts['direction'] == 'Eastbound'), ['day_of_week', 'direction']].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To increase readability, these statements can be put on multiple rows. Anything that is within a parameter or bracket in Python can be continued on the next row. When inside a bracket or parenthesis, the indentation is not significant to the Python interpreter, but it is still recommended to include it in order to make the code more readable." ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " day_of_week direction\n", "24 Saturday Eastbound\n", "25 Saturday Eastbound\n", "26 Saturday Eastbound\n", "27 Saturday Eastbound\n", "28 Saturday Eastbound" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.loc[(bike_counts['day_of_week'] == 'Saturday') & \n", " (bike_counts['direction'] == 'Eastbound'), \n", " ['day_of_week', 'direction']].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With the `|` operator, rows matching either of the supplied criteria are returned." ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 Saturday\n", "1 Saturday\n", "2 Saturday\n", "3 Saturday\n", "4 Saturday\n", "5 Saturday\n", "6 Saturday\n", "7 Saturday\n", "8 Saturday\n", "9 Saturday\n", "10 Saturday\n", "11 Saturday\n", "12 Saturday\n", "13 Saturday\n", "14 Saturday\n", "15 Saturday\n", "16 Saturday\n", "17 Saturday\n", "18 Saturday\n", "19 Saturday\n", "20 Saturday\n", "21 Saturday\n", "22 Saturday\n", "23 Saturday\n", "24 Saturday\n", "25 Saturday\n", "26 Saturday\n", "27 Saturday\n", "28 Saturday\n", "29 Saturday\n", " ... \n", "594 Saturday\n", "595 Saturday\n", "596 Saturday\n", "597 Saturday\n", "598 Saturday\n", "599 Saturday\n", "600 Saturday\n", "601 Saturday\n", "602 Saturday\n", "603 Saturday\n", "604 Saturday\n", "605 Saturday\n", "606 Saturday\n", "607 Saturday\n", "608 Saturday\n", "609 Saturday\n", "610 Saturday\n", "611 Saturday\n", "612 Saturday\n", "613 Saturday\n", "614 Saturday\n", "615 Saturday\n", "616 Saturday\n", "617 Saturday\n", "618 Saturday\n", "619 Saturday\n", "620 Saturday\n", "621 Saturday\n", "622 Saturday\n", "623 Saturday\n", "Name: day_of_week, Length: 240, dtype: object" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# OR = |\n", "bike_counts.loc[(bike_counts['day_of_week'] == 'Saturday') |\n", " (bike_counts['day_of_week'] == 'Sunday'),\n", " 'day_of_week']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">\n", ">Subset the `bike_counts` data to include counts collected only\n", ">on weekdays and retain only the columns 'date', 'day_of_week', and 'bikes'. \n", ">There are multiple ways this could be done." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Creating new columns and the `pandas` datetime object\n", "\n", "A frequent operation when working with data is to create new columns based on the values in existing columns, for example to do unit conversions or find the ratio of values in two columns. You might have noticed that the `hour` column had two different formats; this happened because the data was entered a bit differently in 2010 and 2017. The same thing happened with the `date` column. To clean this up, let's make new columns for the date and hour that are formatted better." ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " date hour\n", "0 9/18/10 12:00:00 AM\n", "1 9/18/10 1:00:00 AM\n", "2 9/18/10 2:00:00 AM\n", "3 9/18/10 3:00:00 AM\n", "4 9/18/10 4:00:00 AM" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts[['date', 'hour']].head()" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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6202017-09-308:00 PM
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" ], "text/plain": [ " date hour\n", "619 2017-09-30 7:00 PM\n", "620 2017-09-30 8:00 PM\n", "621 2017-09-30 9:00 PM\n", "622 2017-09-30 10:00 PM\n", "623 2017-09-30 11:00 PM" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts[['date', 'hour']].tail()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`pandas` has a function called `to_datetime` which takes things that are time-like and creates a very flexible object that stores the date and time. We'll use this on both the 'date' and 'hour' columns to make new columns. \n", "\n", "First, let's see what `to_datetime` does:" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 2010-09-18\n", "1 2010-09-18\n", "2 2010-09-18\n", "3 2010-09-18\n", "4 2010-09-18\n", "5 2010-09-18\n", "6 2010-09-18\n", "7 2010-09-18\n", "8 2010-09-18\n", "9 2010-09-18\n", "10 2010-09-18\n", "11 2010-09-18\n", "12 2010-09-18\n", "13 2010-09-18\n", "14 2010-09-18\n", "15 2010-09-18\n", "16 2010-09-18\n", "17 2010-09-18\n", "18 2010-09-18\n", "19 2010-09-18\n", "20 2010-09-18\n", "21 2010-09-18\n", "22 2010-09-18\n", "23 2010-09-18\n", "24 2010-09-18\n", "25 2010-09-18\n", "26 2010-09-18\n", "27 2010-09-18\n", "28 2010-09-18\n", "29 2010-09-18\n", " ... \n", "594 2017-09-30\n", "595 2017-09-30\n", "596 2017-09-30\n", "597 2017-09-30\n", "598 2017-09-30\n", "599 2017-09-30\n", "600 2017-09-30\n", "601 2017-09-30\n", "602 2017-09-30\n", "603 2017-09-30\n", "604 2017-09-30\n", "605 2017-09-30\n", "606 2017-09-30\n", "607 2017-09-30\n", "608 2017-09-30\n", "609 2017-09-30\n", "610 2017-09-30\n", "611 2017-09-30\n", "612 2017-09-30\n", "613 2017-09-30\n", "614 2017-09-30\n", "615 2017-09-30\n", "616 2017-09-30\n", "617 2017-09-30\n", "618 2017-09-30\n", "619 2017-09-30\n", "620 2017-09-30\n", "621 2017-09-30\n", "622 2017-09-30\n", "623 2017-09-30\n", "Name: date, Length: 624, dtype: datetime64[ns]" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.to_datetime(bike_counts['date'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That looks good: now all the dates are in the same YYYY-MM-DD format. Let's save that result in a new column called 'date_dt' for \"date as datetime\"." ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "bike_counts['date_dt'] = pd.to_datetime(bike_counts['date'])" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['date', 'day_of_week', 'temperature', 'weather', 'direction',\n", " 'position', 'hour', 'bikes', 'date_dt'],\n", " dtype='object')" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# check to see that our new column was created\n", "bike_counts.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The really handy thing about `datetime` is it allows you to access certain parts of the date only. Let's say you only want the year:" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "619 2017\n", "620 2017\n", "621 2017\n", "622 2017\n", "623 2017\n", "Name: date_dt, dtype: int64" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts['date_dt'].dt.year.tail()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`.year` is called a `.dt accessor`, and there are [lots](https://pandas.pydata.org/pandas-docs/stable/basics.html#basics-dt-accessors), including `.month`, `.day`, `.hour`, `.minute`, `.second`, etc. Try them out yourself!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, let's make a column for the hours that just stores the hours as an integer value between 0 and 23. " ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "bike_counts['hour_dt'] = pd.to_datetime(bike_counts['hour']).dt.hour" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we combined a `.dt accessor` and the `to_datetime` function to go straight to the integer value of the hour." ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikesdate_dthour_dt
09/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.12:00:00 AM702010-09-180
19/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.1:00:00 AM272010-09-181
29/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.2:00:00 AM232010-09-182
39/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.3:00:00 AM82010-09-183
49/18/10Saturday21No RainWestboundBike lane just east of Spadina Ave.4:00:00 AM102010-09-184
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" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "0 9/18/10 Saturday 21 No Rain Westbound \n", "1 9/18/10 Saturday 21 No Rain Westbound \n", "2 9/18/10 Saturday 21 No Rain Westbound \n", "3 9/18/10 Saturday 21 No Rain Westbound \n", "4 9/18/10 Saturday 21 No Rain Westbound \n", "\n", " position hour bikes date_dt hour_dt \n", "0 Bike lane just east of Spadina Ave. 12:00:00 AM 70 2010-09-18 0 \n", "1 Bike lane just east of Spadina Ave. 1:00:00 AM 27 2010-09-18 1 \n", "2 Bike lane just east of Spadina Ave. 2:00:00 AM 23 2010-09-18 2 \n", "3 Bike lane just east of Spadina Ave. 3:00:00 AM 8 2010-09-18 3 \n", "4 Bike lane just east of Spadina Ave. 4:00:00 AM 10 2010-09-18 4 " ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`surveys.info()` showed that the 'position' column was missing some values. The function `dropna()` can be used to remove all records with missing data. The missing values occured because the 2017 data didn't have position information." ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikesdate_dthour_dt
6142017-09-30Saturday15No RainWestboundNaN2:00 PM1092017-09-3014
6152017-09-30Saturday15No RainWestboundNaN3:00 PM1142017-09-3015
6162017-09-30Saturday15No RainWestboundNaN4:00 PM1322017-09-3016
6172017-09-30Saturday15No RainWestboundNaN5:00 PM1362017-09-3017
6182017-09-30Saturday15No RainWestboundNaN6:00 PM1202017-09-3018
6192017-09-30Saturday15No RainWestboundNaN7:00 PM982017-09-3019
6202017-09-30Saturday15No RainWestboundNaN8:00 PM792017-09-3020
6212017-09-30Saturday15No RainWestboundNaN9:00 PM622017-09-3021
6222017-09-30Saturday15No RainWestboundNaN10:00 PM802017-09-3022
6232017-09-30Saturday15No RainWestboundNaN11:00 PM822017-09-3023
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" ], "text/plain": [ " date day_of_week temperature weather direction position \\\n", "614 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "615 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "616 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "617 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "618 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "619 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "620 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "621 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "622 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "623 2017-09-30 Saturday 15 No Rain Westbound NaN \n", "\n", " hour bikes date_dt hour_dt \n", "614 2:00 PM 109 2017-09-30 14 \n", "615 3:00 PM 114 2017-09-30 15 \n", "616 4:00 PM 132 2017-09-30 16 \n", "617 5:00 PM 136 2017-09-30 17 \n", "618 6:00 PM 120 2017-09-30 18 \n", "619 7:00 PM 98 2017-09-30 19 \n", "620 8:00 PM 79 2017-09-30 20 \n", "621 9:00 PM 62 2017-09-30 21 \n", "622 10:00 PM 80 2017-09-30 22 \n", "623 11:00 PM 82 2017-09-30 23 " ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.tail(10)" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateday_of_weektemperatureweatherdirectionpositionhourbikesdate_dthour_dt
4229/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.2:00:00 PM1022010-09-2414
4239/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.3:00:00 PM1262010-09-2415
4249/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.4:00:00 PM722010-09-2416
4259/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.5:00:00 PM892010-09-2417
4269/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.6:00:00 PM612010-09-2418
4279/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.7:00:00 PM812010-09-2419
4289/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.8:00:00 PM522010-09-2420
4299/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.9:00:00 PM512010-09-2421
4309/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.10:00:00 PM412010-09-2422
4319/24/10Friday30No RainEastboundBike lane just west of Spadina Ave.11:00:00 PM332010-09-2423
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" ], "text/plain": [ " date day_of_week temperature weather direction \\\n", "422 9/24/10 Friday 30 No Rain Eastbound \n", "423 9/24/10 Friday 30 No Rain Eastbound \n", "424 9/24/10 Friday 30 No Rain Eastbound \n", "425 9/24/10 Friday 30 No Rain Eastbound \n", "426 9/24/10 Friday 30 No Rain Eastbound \n", "427 9/24/10 Friday 30 No Rain Eastbound \n", "428 9/24/10 Friday 30 No Rain Eastbound \n", "429 9/24/10 Friday 30 No Rain Eastbound \n", "430 9/24/10 Friday 30 No Rain Eastbound \n", "431 9/24/10 Friday 30 No Rain Eastbound \n", "\n", " position hour bikes date_dt \\\n", "422 Bike lane just west of Spadina Ave. 2:00:00 PM 102 2010-09-24 \n", "423 Bike lane just west of Spadina Ave. 3:00:00 PM 126 2010-09-24 \n", "424 Bike lane just west of Spadina Ave. 4:00:00 PM 72 2010-09-24 \n", "425 Bike lane just west of Spadina Ave. 5:00:00 PM 89 2010-09-24 \n", "426 Bike lane just west of Spadina Ave. 6:00:00 PM 61 2010-09-24 \n", "427 Bike lane just west of Spadina Ave. 7:00:00 PM 81 2010-09-24 \n", "428 Bike lane just west of Spadina Ave. 8:00:00 PM 52 2010-09-24 \n", "429 Bike lane just west of Spadina Ave. 9:00:00 PM 51 2010-09-24 \n", "430 Bike lane just west of Spadina Ave. 10:00:00 PM 41 2010-09-24 \n", "431 Bike lane just west of Spadina Ave. 11:00:00 PM 33 2010-09-24 \n", "\n", " hour_dt \n", "422 14 \n", "423 15 \n", "424 16 \n", "425 17 \n", "426 18 \n", "427 19 \n", "428 20 \n", "429 21 \n", "430 22 \n", "431 23 " ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.dropna().tail(10)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "-" } }, "source": [ "By default, `.dropna()` removes all rows that have an NA value in any of the columns. There are parameters for `dropna()` that can specify how the rows are dropped and which columns should be searched for NAs.\n", "\n", "A common alternative to removing rows containing `NA` values is to fill out the values with somethine else, for example the mean of all observations or the previous non-NA value. This can be done with the `fillna()` method." ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "619 NaN\n", "620 NaN\n", "621 NaN\n", "622 NaN\n", "623 NaN\n", "Name: position, dtype: object" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts['position'].tail()" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "619 Bike lane\n", "620 Bike lane\n", "621 Bike lane\n", "622 Bike lane\n", "623 Bike lane\n", "Name: position, dtype: object" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Fill a particular value\n", "fill_value = \"Bike lane\"\n", "bike_counts['position'].fillna(fill_value).tail()" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "619 Bike lane just west of Spadina Ave.\n", "620 Bike lane just west of Spadina Ave.\n", "621 Bike lane just west of Spadina Ave.\n", "622 Bike lane just west of Spadina Ave.\n", "623 Bike lane just west of Spadina Ave.\n", "Name: position, dtype: object" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Fill with previous non-null value - ffill stands for \"forward fill\"\n", "bike_counts['position'].fillna(method='ffill').tail()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that in both of these examples we haven't changed the data frame permanently. Unless we *reassign* the result to that column, the result is returned instead of being stored. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Whether to use `dropna()` or `fillna()` depends on the data set and the purpose of the analysis." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "-" } }, "source": [ ">#### Challenge\n", ">\n", ">1. Create a new data frame from the `bike_counts` data that contains only the `date` and `bikes` columns.\n", ">2. Add a column to this new data frame called `year`, which contains just the year from the `date` column. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Split-apply-combine techniques in pandas\n", "\n", "Many data analysis tasks can be approached using the *split-apply-combine* paradigm: split the data into groups, apply some analysis to each group, and then combine the results.\n", "\n", "`pandas` facilitates this workflow through the use of `groupby()` to split data, and summary/aggregation functions such as `mean()`, which collapses each group into a single-row summary of that group. The arguments to `groupby()` are the column names that contain the *categorical* variables by which summary statistics should be calculated. To start, compute the total number of bikes counted, grouped by date.\n", "\n", "![Image credit Jake VanderPlas](img/split-apply-combine.png)\n", "\n", "*Image credit Jake VanderPlas*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `.sum()` method can be used to calculate the sum of each group. When the sum is computed, the default behavior is to ignore NA values, so they only need to be dropped if they are to be excluded from the visual output." ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt\n", "2010-09-18 2531\n", "2010-09-19 2669\n", "2010-09-20 4734\n", "2010-09-21 4814\n", "2010-09-22 3812\n", "2010-09-23 4746\n", "2010-09-24 4373\n", "2010-09-25 2515\n", "2010-09-26 2575\n", "2017-09-27 5667\n", "2017-09-28 5426\n", "2017-09-29 3778\n", "2017-09-30 2988\n", "Name: bikes, dtype: int64" ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.groupby(['date_dt'])['bikes'].sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The output here is a series that is indexed with the grouped variable (the date) and the single column contains the result of the aggregation (the sum of counts)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Individual entries can be selected from the resulting series using `loc[]`, just as previously." ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt\n", "2010-09-18 2531\n", "2010-09-19 2669\n", "2010-09-20 4734\n", "2010-09-21 4814\n", "2010-09-22 3812\n", "2010-09-23 4746\n", "2010-09-24 4373\n", "2010-09-25 2515\n", "2010-09-26 2575\n", "Name: bikes, dtype: int64" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_summed = bike_counts.groupby(['date_dt'])['bikes'].sum()\n", "bike_counts_summed.loc['2010-09-18':'2010-09-26']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Groups can also be created from multiple columns, e.g. it could be interesting to see the difference for the same day of the week between years." ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['date', 'day_of_week', 'temperature', 'weather', 'direction',\n", " 'position', 'hour', 'bikes', 'date_dt', 'hour_dt'],\n", " dtype='object')" ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.columns" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": [ "bike_counts_date_weekday = bike_counts.groupby(['day_of_week', 'date_dt'])['bikes'].sum()" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "day_of_week date_dt \n", "Friday 2010-09-24 4373\n", " 2017-09-29 3778\n", "Monday 2010-09-20 4734\n", "Saturday 2010-09-18 2531\n", " 2010-09-25 2515\n", " 2017-09-30 2988\n", "Sunday 2010-09-19 2669\n", " 2010-09-26 2575\n", "Thursday 2010-09-23 4746\n", " 2017-09-28 5426\n", "Tuesday 2010-09-21 4814\n", "Wednesday 2010-09-22 3812\n", " 2017-09-27 5667\n", "Name: bikes, dtype: int64" ] }, "execution_count": 86, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_date_weekday" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The returned series has an index that is a combination of the columns `day_of_week` and `date_dt`, and referred to as a `MultiIndex`. The same syntax as previously can be used to select rows on the day-of-week-level." ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "day_of_week date_dt \n", "Sunday 2010-09-19 2669\n", " 2010-09-26 2575\n", "Thursday 2010-09-23 4746\n", " 2017-09-28 5426\n", "Name: bikes, dtype: int64" ] }, "execution_count": 87, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_date_weekday.loc[['Sunday', 'Thursday']]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To select specific values from both levels of the `MultiIndex`, a tuple or list of tuples can be passed to `loc[]`. Datetime objects are a bit different, and passing a list might not work. " ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2988" ] }, "execution_count": 88, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_date_weekday.loc[('Saturday', '2017-09-30')]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The names and values of the index levels can be seen by inspecting the index object." ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "MultiIndex(levels=[['Friday', 'Monday', 'Saturday', 'Sunday', 'Thursday', 'Tuesday', 'Wednesday'], [2010-09-18 00:00:00, 2010-09-19 00:00:00, 2010-09-20 00:00:00, 2010-09-21 00:00:00, 2010-09-22 00:00:00, 2010-09-23 00:00:00, 2010-09-24 00:00:00, 2010-09-25 00:00:00, 2010-09-26 00:00:00, 2017-09-27 00:00:00, 2017-09-28 00:00:00, 2017-09-29 00:00:00, 2017-09-30 00:00:00]],\n", " labels=[[0, 0, 1, 2, 2, 2, 3, 3, 4, 4, 5, 6, 6], [6, 11, 2, 0, 7, 12, 1, 8, 5, 10, 3, 4, 9]],\n", " names=['day_of_week', 'date_dt'])" ] }, "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_date_weekday.index" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Although MultiIndexes offer succinct and fast ways to access data, they also requires memorization of additional syntax and are strictly speaking not essential unless speed is of particular concern. It can therefore be easier to reset the index, so that all values are stored in columns." ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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day_of_weekdate_dtbikes
0Friday2010-09-244373
1Friday2017-09-293778
2Monday2010-09-204734
3Saturday2010-09-182531
4Saturday2010-09-252515
5Saturday2017-09-302988
6Sunday2010-09-192669
7Sunday2010-09-262575
8Thursday2010-09-234746
9Thursday2017-09-285426
10Tuesday2010-09-214814
11Wednesday2010-09-223812
12Wednesday2017-09-275667
\n", "
" ], "text/plain": [ " day_of_week date_dt bikes\n", "0 Friday 2010-09-24 4373\n", "1 Friday 2017-09-29 3778\n", "2 Monday 2010-09-20 4734\n", "3 Saturday 2010-09-18 2531\n", "4 Saturday 2010-09-25 2515\n", "5 Saturday 2017-09-30 2988\n", "6 Sunday 2010-09-19 2669\n", "7 Sunday 2010-09-26 2575\n", "8 Thursday 2010-09-23 4746\n", "9 Thursday 2017-09-28 5426\n", "10 Tuesday 2010-09-21 4814\n", "11 Wednesday 2010-09-22 3812\n", "12 Wednesday 2017-09-27 5667" ] }, "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_date_weekday_res = bike_counts_date_weekday.reset_index()\n", "bike_counts_date_weekday_res" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "After resetting the index, the same comparison syntax introduced earlier can be used instead of passing lists of tuples to `loc[]`." ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
day_of_weekdate_dtbikes
3Saturday2010-09-182531
4Saturday2010-09-252515
5Saturday2017-09-302988
\n", "
" ], "text/plain": [ " day_of_week date_dt bikes\n", "3 Saturday 2010-09-18 2531\n", "4 Saturday 2010-09-25 2515\n", "5 Saturday 2017-09-30 2988" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "saturday_counts = bike_counts_date_weekday_res.loc[bike_counts_date_weekday_res['day_of_week'] == 'Saturday']\n", "saturday_counts" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`reset_index()` grants the freedom of not having to work with indexes, but it is still worth keeping in mind that selecting on an index level can be orders of magnitude faster than using boolean comparisons (on large data frames).\n", "\n", "The opposite operation (to create an index) can be performed with `set_index()` on any column (or combination of columns) that creates an index with unique values." ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
bikes
day_of_weekdate_dt
Saturday2010-09-182531
2010-09-252515
2017-09-302988
\n", "
" ], "text/plain": [ " bikes\n", "day_of_week date_dt \n", "Saturday 2010-09-18 2531\n", " 2010-09-25 2515\n", " 2017-09-30 2988" ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "saturday_counts.set_index(['day_of_week', 'date_dt'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Multiple aggregations on grouped data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since the bike counts are split into two directions, let's use `groupby` to create a new dataframe with the total summed across eastbound and westbound directions. Each column we want to keep is included in the list passed to `groupby`, even though some of them don't actually result in new groups. For example, if `hour_dt` wasn't included in the list, the sum at the end would add up all the counts across the entire day, when what we want is to keep the counts separate for each hour and only sum over the two directions. The only columns not kept are \"position\", \"date\", and \"hour\"." ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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date_dtday_of_weektemperatureweatherhour_dtbikes
02010-09-18Saturday21No Rain0104
12010-09-18Saturday21No Rain165
22010-09-18Saturday21No Rain239
32010-09-18Saturday21No Rain327
42010-09-18Saturday21No Rain417
52010-09-18Saturday21No Rain59
62010-09-18Saturday21No Rain614
72010-09-18Saturday21No Rain746
82010-09-18Saturday21No Rain868
92010-09-18Saturday21No Rain985
102010-09-18Saturday21No Rain10114
112010-09-18Saturday21No Rain11171
122010-09-18Saturday21No Rain12163
132010-09-18Saturday21No Rain13190
142010-09-18Saturday21No Rain14198
152010-09-18Saturday21No Rain15149
162010-09-18Saturday21No Rain16211
172010-09-18Saturday21No Rain17206
182010-09-18Saturday21No Rain18170
192010-09-18Saturday21No Rain19125
202010-09-18Saturday21No Rain20132
212010-09-18Saturday21No Rain2168
222010-09-18Saturday21No Rain2270
232010-09-18Saturday21No Rain2390
242010-09-19Sunday20No Rain073
252010-09-19Sunday20No Rain142
262010-09-19Sunday20No Rain225
272010-09-19Sunday20No Rain324
282010-09-19Sunday20No Rain413
292010-09-19Sunday20No Rain57
.....................
2822017-09-29Friday18Rain 4mm18322
2832017-09-29Friday18Rain 4mm19197
2842017-09-29Friday18Rain 4mm20131
2852017-09-29Friday18Rain 4mm21104
2862017-09-29Friday18Rain 4mm2272
2872017-09-29Friday18Rain 4mm2363
2882017-09-30Saturday15No Rain063
2892017-09-30Saturday15No Rain131
2902017-09-30Saturday15No Rain216
2912017-09-30Saturday15No Rain315
2922017-09-30Saturday15No Rain46
2932017-09-30Saturday15No Rain514
2942017-09-30Saturday15No Rain625
2952017-09-30Saturday15No Rain735
2962017-09-30Saturday15No Rain881
2972017-09-30Saturday15No Rain9102
2982017-09-30Saturday15No Rain10108
2992017-09-30Saturday15No Rain11177
3002017-09-30Saturday15No Rain12202
3012017-09-30Saturday15No Rain13200
3022017-09-30Saturday15No Rain14209
3032017-09-30Saturday15No Rain15229
3042017-09-30Saturday15No Rain16233
3052017-09-30Saturday15No Rain17242
3062017-09-30Saturday15No Rain18210
3072017-09-30Saturday15No Rain19188
3082017-09-30Saturday15No Rain20156
3092017-09-30Saturday15No Rain21141
3102017-09-30Saturday15No Rain22165
3112017-09-30Saturday15No Rain23140
\n", "

312 rows × 6 columns

\n", "
" ], "text/plain": [ " date_dt day_of_week temperature weather hour_dt bikes\n", "0 2010-09-18 Saturday 21 No Rain 0 104\n", "1 2010-09-18 Saturday 21 No Rain 1 65\n", "2 2010-09-18 Saturday 21 No Rain 2 39\n", "3 2010-09-18 Saturday 21 No Rain 3 27\n", "4 2010-09-18 Saturday 21 No Rain 4 17\n", "5 2010-09-18 Saturday 21 No Rain 5 9\n", "6 2010-09-18 Saturday 21 No Rain 6 14\n", "7 2010-09-18 Saturday 21 No Rain 7 46\n", "8 2010-09-18 Saturday 21 No Rain 8 68\n", "9 2010-09-18 Saturday 21 No Rain 9 85\n", "10 2010-09-18 Saturday 21 No Rain 10 114\n", "11 2010-09-18 Saturday 21 No Rain 11 171\n", "12 2010-09-18 Saturday 21 No Rain 12 163\n", "13 2010-09-18 Saturday 21 No Rain 13 190\n", "14 2010-09-18 Saturday 21 No Rain 14 198\n", "15 2010-09-18 Saturday 21 No Rain 15 149\n", "16 2010-09-18 Saturday 21 No Rain 16 211\n", "17 2010-09-18 Saturday 21 No Rain 17 206\n", "18 2010-09-18 Saturday 21 No Rain 18 170\n", "19 2010-09-18 Saturday 21 No Rain 19 125\n", "20 2010-09-18 Saturday 21 No Rain 20 132\n", "21 2010-09-18 Saturday 21 No Rain 21 68\n", "22 2010-09-18 Saturday 21 No Rain 22 70\n", "23 2010-09-18 Saturday 21 No Rain 23 90\n", "24 2010-09-19 Sunday 20 No Rain 0 73\n", "25 2010-09-19 Sunday 20 No Rain 1 42\n", "26 2010-09-19 Sunday 20 No Rain 2 25\n", "27 2010-09-19 Sunday 20 No Rain 3 24\n", "28 2010-09-19 Sunday 20 No Rain 4 13\n", "29 2010-09-19 Sunday 20 No Rain 5 7\n", ".. ... ... ... ... ... ...\n", "282 2017-09-29 Friday 18 Rain 4mm 18 322\n", "283 2017-09-29 Friday 18 Rain 4mm 19 197\n", "284 2017-09-29 Friday 18 Rain 4mm 20 131\n", "285 2017-09-29 Friday 18 Rain 4mm 21 104\n", "286 2017-09-29 Friday 18 Rain 4mm 22 72\n", "287 2017-09-29 Friday 18 Rain 4mm 23 63\n", "288 2017-09-30 Saturday 15 No Rain 0 63\n", "289 2017-09-30 Saturday 15 No Rain 1 31\n", "290 2017-09-30 Saturday 15 No Rain 2 16\n", "291 2017-09-30 Saturday 15 No Rain 3 15\n", "292 2017-09-30 Saturday 15 No Rain 4 6\n", "293 2017-09-30 Saturday 15 No Rain 5 14\n", "294 2017-09-30 Saturday 15 No Rain 6 25\n", "295 2017-09-30 Saturday 15 No Rain 7 35\n", "296 2017-09-30 Saturday 15 No Rain 8 81\n", "297 2017-09-30 Saturday 15 No Rain 9 102\n", "298 2017-09-30 Saturday 15 No Rain 10 108\n", "299 2017-09-30 Saturday 15 No Rain 11 177\n", "300 2017-09-30 Saturday 15 No Rain 12 202\n", "301 2017-09-30 Saturday 15 No Rain 13 200\n", "302 2017-09-30 Saturday 15 No Rain 14 209\n", "303 2017-09-30 Saturday 15 No Rain 15 229\n", "304 2017-09-30 Saturday 15 No Rain 16 233\n", "305 2017-09-30 Saturday 15 No Rain 17 242\n", "306 2017-09-30 Saturday 15 No Rain 18 210\n", "307 2017-09-30 Saturday 15 No Rain 19 188\n", "308 2017-09-30 Saturday 15 No Rain 20 156\n", "309 2017-09-30 Saturday 15 No Rain 21 141\n", "310 2017-09-30 Saturday 15 No Rain 22 165\n", "311 2017-09-30 Saturday 15 No Rain 23 140\n", "\n", "[312 rows x 6 columns]" ] }, "execution_count": 93, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total =(bike_counts.groupby(['date_dt', 'day_of_week', 'temperature', 'weather', 'hour_dt'])['bikes']\n", " .sum()\n", " .reset_index())\n", "bike_counts_total" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since the same grouped data frame will be used in multiple code chunks below, this can be assigned to a new variable instead of typing out the grouping expression each time." ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt day_of_week weather \n", "2010-09-18 Saturday No Rain 2531\n", "2010-09-19 Sunday No Rain 2669\n", "2010-09-20 Monday No Rain 4734\n", "2010-09-21 Tuesday No Rain 4814\n", "2010-09-22 Wednesday Rain 6mm 3812\n", "2010-09-23 Thursday No Rain 4746\n", "2010-09-24 Friday No Rain 4373\n", "2010-09-25 Saturday No Rain 2515\n", "2010-09-26 Sunday No Rain 2575\n", "2017-09-27 Wednesday No Rain 5667\n", "2017-09-28 Thursday No Rain 5426\n", "2017-09-29 Friday Rain 4mm 3778\n", "2017-09-30 Saturday No Rain 2988\n", "Name: bikes, dtype: int64" ] }, "execution_count": 94, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_bike_counts = bike_counts_total.groupby(['date_dt', 'day_of_week', 'weather'])\n", "grouped_bike_counts['bikes'].sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Other aggregation methods, such as the standard deviation, are called with the same syntax." ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt day_of_week weather \n", "2010-09-18 Saturday No Rain 65.191343\n", "2010-09-19 Sunday No Rain 79.652495\n", "2010-09-20 Monday No Rain 159.863597\n", "2010-09-21 Tuesday No Rain 149.924885\n", "2010-09-22 Wednesday Rain 6mm 110.727895\n", "2010-09-23 Thursday No Rain 143.297274\n", "2010-09-24 Friday No Rain 122.429387\n", "2010-09-25 Saturday No Rain 58.832836\n", "2010-09-26 Sunday No Rain 77.870282\n", "2017-09-27 Wednesday No Rain 182.103724\n", "2017-09-28 Thursday No Rain 170.290523\n", "2017-09-29 Friday Rain 4mm 137.304459\n", "2017-09-30 Saturday No Rain 82.280010\n", "Name: bikes, dtype: float64" ] }, "execution_count": 95, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_bike_counts['bikes'].std()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that it is important to remember the structure of the data to make sure that the computations you're doing make sense. For example, be careful with an operation like `bike_counts_total.groupby('day_of_week')['bikes'].mean()`. This result is actually the mean *per hour* and not the mean for the entire day." ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "day_of_week\n", "Friday 169.812500\n", "Monday 197.250000\n", "Saturday 111.583333\n", "Sunday 109.250000\n", "Thursday 211.916667\n", "Tuesday 200.583333\n", "Wednesday 197.479167\n", "Name: bikes, dtype: float64" ] }, "execution_count": 96, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.groupby('day_of_week')['bikes'].mean()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Instead of using the `sum()` method, the more general `agg()` method could be called to aggregate (or summarize) by *any* existing aggregation functions. The equivalent to the `sum()` method would be to call `agg()` and specify `'sum'`." ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt day_of_week weather \n", "2010-09-18 Saturday No Rain 2531\n", "2010-09-19 Sunday No Rain 2669\n", "2010-09-20 Monday No Rain 4734\n", "2010-09-21 Tuesday No Rain 4814\n", "2010-09-22 Wednesday Rain 6mm 3812\n", "2010-09-23 Thursday No Rain 4746\n", "2010-09-24 Friday No Rain 4373\n", "2010-09-25 Saturday No Rain 2515\n", "2010-09-26 Sunday No Rain 2575\n", "2017-09-27 Wednesday No Rain 5667\n", "2017-09-28 Thursday No Rain 5426\n", "2017-09-29 Friday Rain 4mm 3778\n", "2017-09-30 Saturday No Rain 2988\n", "Name: bikes, dtype: int64" ] }, "execution_count": 97, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_bike_counts['bikes'].agg('sum')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This general approach is more flexible and powerful since multiple aggregation functions can be applied in the same line of code by passing them as a list to `agg()`. For instance, the standard deviation and mean could be computed in the same call by passing them in a list." ] }, { "cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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maxsum
date_dtday_of_weekweather
2010-09-18SaturdayNo Rain2112531
2010-09-19SundayNo Rain2352669
2010-09-20MondayNo Rain5184734
2010-09-21TuesdayNo Rain5254814
2010-09-22WednesdayRain 6mm3833812
2010-09-23ThursdayNo Rain4934746
2010-09-24FridayNo Rain3794373
2010-09-25SaturdayNo Rain1862515
2010-09-26SundayNo Rain2362575
2017-09-27WednesdayNo Rain6115667
2017-09-28ThursdayNo Rain5625426
2017-09-29FridayRain 4mm4663778
2017-09-30SaturdayNo Rain2422988
\n", "
" ], "text/plain": [ " max sum\n", "date_dt day_of_week weather \n", "2010-09-18 Saturday No Rain 211 2531\n", "2010-09-19 Sunday No Rain 235 2669\n", "2010-09-20 Monday No Rain 518 4734\n", "2010-09-21 Tuesday No Rain 525 4814\n", "2010-09-22 Wednesday Rain 6mm 383 3812\n", "2010-09-23 Thursday No Rain 493 4746\n", "2010-09-24 Friday No Rain 379 4373\n", "2010-09-25 Saturday No Rain 186 2515\n", "2010-09-26 Sunday No Rain 236 2575\n", "2017-09-27 Wednesday No Rain 611 5667\n", "2017-09-28 Thursday No Rain 562 5426\n", "2017-09-29 Friday Rain 4mm 466 3778\n", "2017-09-30 Saturday No Rain 242 2988" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_bike_counts['bikes'].agg(['max', 'sum'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The returned output is in this case a data frame and the `MultiIndex` is indicated in bold font.\n", "\n", "By passing a dictionary to `.agg()` it is possible to apply different aggregations to the different columns. Long code statements can be broken down into multiple lines if they are enclosed by parentheses, brackets or braces, something that will be described in detail later." ] }, { "cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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temperaturebikes
meanminmaxsum
date_dtday_of_weekweather
2010-09-18SaturdayNo Rain2192112531
2010-09-19SundayNo Rain2072352669
2010-09-20MondayNo Rain1945184734
2010-09-21TuesdayNo Rain2545254814
2010-09-22WednesdayRain 6mm2343833812
2010-09-23ThursdayNo Rain1944934746
2010-09-24FridayNo Rain3063794373
2010-09-25SaturdayNo Rain18111862515
2010-09-26SundayNo Rain1792362575
2017-09-27WednesdayNo Rain3066115667
2017-09-28ThursdayNo Rain19115625426
2017-09-29FridayRain 4mm1884663778
2017-09-30SaturdayNo Rain1562422988
\n", "
" ], "text/plain": [ " temperature bikes \n", " mean min max sum\n", "date_dt day_of_week weather \n", "2010-09-18 Saturday No Rain 21 9 211 2531\n", "2010-09-19 Sunday No Rain 20 7 235 2669\n", "2010-09-20 Monday No Rain 19 4 518 4734\n", "2010-09-21 Tuesday No Rain 25 4 525 4814\n", "2010-09-22 Wednesday Rain 6mm 23 4 383 3812\n", "2010-09-23 Thursday No Rain 19 4 493 4746\n", "2010-09-24 Friday No Rain 30 6 379 4373\n", "2010-09-25 Saturday No Rain 18 11 186 2515\n", "2010-09-26 Sunday No Rain 17 9 236 2575\n", "2017-09-27 Wednesday No Rain 30 6 611 5667\n", "2017-09-28 Thursday No Rain 19 11 562 5426\n", "2017-09-29 Friday Rain 4mm 18 8 466 3778\n", "2017-09-30 Saturday No Rain 15 6 242 2988" ] }, "execution_count": 99, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_bike_counts[['temperature', 'bikes']].agg(\n", " {'temperature': 'mean',\n", " 'bikes': ['min', 'max', 'sum']\n", " }\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are plenty of aggregation methods available in pandas (e.g. `sem`, `mad`, `sum`, all of which can be found using tab-complete on the grouped data frame." ] }, { "cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [], "source": [ "# Tab completion might only work like this:\n", "# find_agg_methods = grouped_bike_counts['temperature']\n", "# find_agg_methods." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Even if a function is not part of the `pandas` library, it can be passed to `agg()`." ] }, { "cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt day_of_week weather \n", "2010-09-18 Saturday No Rain 21\n", "2010-09-19 Sunday No Rain 20\n", "2010-09-20 Monday No Rain 19\n", "2010-09-21 Tuesday No Rain 25\n", "2010-09-22 Wednesday Rain 6mm 23\n", "2010-09-23 Thursday No Rain 19\n", "2010-09-24 Friday No Rain 30\n", "2010-09-25 Saturday No Rain 18\n", "2010-09-26 Sunday No Rain 17\n", "2017-09-27 Wednesday No Rain 30\n", "2017-09-28 Thursday No Rain 19\n", "2017-09-29 Friday Rain 4mm 18\n", "2017-09-30 Saturday No Rain 15\n", "Name: temperature, dtype: int64" ] }, "execution_count": 101, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", "\n", "grouped_bike_counts['temperature'].agg(np.mean)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Any function can be passed like this, including user-created functions. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> #### Challenge\n", "> \n", "> 1. Use `groupby()` and `agg()` with the `bike_counts_total` data frame\n", "> to find the mean, min, and max bike counts\n", "> per hourly time interval across all the measurement days.\n", "> \n", "> 2. What was the largest bike count for each day? Return the columns `date_dt`,\n", "> `day_of_week`, `hour_dt`, `weather`, and `bikes`. *Hint* Look into the `idxmax()` method.\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Using `size()` to summarize categorical data \n", "\n", "When working with data, it is common to want to know the number of observations present for each categorical variable. For this, `pandas` provides the `size()` method. For example, to group by 'weather' and find the number of observations for each weather condition:" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "weather\n", " No Rain 264\n", " Rain 6mm 24\n", "Rain 4mm 24\n", "dtype: int64" ] }, "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.groupby('weather').size()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`size()` can also be used when grouping on multiple variables." ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "temperature weather \n", "15 No Rain 48\n", "17 No Rain 48\n", "18 No Rain 48\n", " Rain 4mm 48\n", "19 No Rain 144\n", "20 No Rain 48\n", "21 No Rain 48\n", "23 Rain 6mm 48\n", "25 No Rain 48\n", "30 No Rain 96\n", "dtype: int64" ] }, "execution_count": 103, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts.groupby(['temperature', 'weather']).size()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If there are many groups, `size()` is not that useful on its own. For example, it is difficult to quickly find the most commonly observed temperature among the observations." ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "temperature\n", "15 24\n", "17 24\n", "18 48\n", "19 72\n", "20 24\n", "21 24\n", "23 24\n", "25 24\n", "30 48\n", "dtype: int64" ] }, "execution_count": 104, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.groupby('temperature').size()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It would be beneficial to sort the table values and display the most commonly observed temperature first. This is easy to do with the `sort_values()` method." ] }, { "cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "temperature\n", "15 24\n", "17 24\n", "20 24\n", "21 24\n", "23 24\n", "25 24\n", "18 48\n", "30 48\n", "19 72\n", "dtype: int64" ] }, "execution_count": 105, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.groupby('temperature').size().sort_values()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's better, but it could be helpful to display the most common temperature at the top of the list. In other words, the output should be arranged in descending order." ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "temperature\n", "19 72\n", "30 48\n", "18 48\n", "25 24\n", "23 24\n", "dtype: int64" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.groupby('temperature').size().sort_values(ascending=False).head(5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looks good! By now, the code statement has grown quite long because many methods have been *chained* together. It can be tricky to keep track of what is going on in long method chains. To make the code more readable, it can be broken up multiple lines by adding a surrounding parenthesis." ] }, { "cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "temperature\n", "19 72\n", "30 48\n", "18 48\n", "25 24\n", "23 24\n", "dtype: int64" ] }, "execution_count": 107, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(bike_counts_total\n", " .groupby('temperature')\n", " .size()\n", " .sort_values(ascending=False)\n", " .head(5)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This looks neater and makes long method chains easier to reads. There is no absolute rule for when to break code into multiple line, but always try to write code that is easy for collaborators (your most common collaborator is a future version of yourself!) to understand.\n", "\n", "`pandas` actually has a convenience function for returning the top five results, so the values don't need to be sorted explicitly." ] }, { "cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "temperature\n", "19 72\n", "18 48\n", "30 48\n", "15 24\n", "17 24\n", "dtype: int64" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(bike_counts_total\n", " .groupby('temperature')\n", " .size()\n", " .nlargest() # the default is 5\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Using `nunique()` to count number of unique observations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The command `.size()` gives the number of observations for each unique value a particular column or set of columns. The command `nunique()` is similar, but it counts just the number of unique entries. It can be used on an entire dataframe, or a subset of columns." ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "date_dt 13\n", "day_of_week 7\n", "temperature 9\n", "weather 3\n", "hour_dt 24\n", "bikes 212\n", "dtype: int64" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.nunique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">\n", ">1. How many different count days are in the `bike_counts_total` dataset?\n", ">\n", ">2. Create a new dataframe called `weather_df` by grouping by `date_dt` and `weather` and calculating the size. Use the new dataframe to calculate how many of the count days had no rain.\n", ">\n", ">Optional challenge: Which day of the week was counted on the most separate occasions? Hint: modify `weather_df` to include the `day_of_week` column.\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Part 3 - Visualizing Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data visualization in `matplotlib` and `seaborn`\n", "\n", "There are many plotting packages in Python, making it possible to create diverse visualizations such as interactive web graphics, 3D animations, statistical visualizations, and map-based plots. A Google search for \"[Python graph gallery](https://python-graph-gallery.com/all-charts/)\" or \"[Seaborn graph gallery](https://seaborn.pydata.org/examples/)\" will turn up lots of examples of the diversity of plots that can be made.\n", "\n", "Here, we will focus on two of the most useful for researchers: `matplotlib`, which is a robust, detail-oriented, low level plotting interface, and `seaborn`, which provides high level functions on top of `matplotlib` and allows the plotting calls to be expressed more in terms what is being explored in the underlying data rather than what graphical elements to add to the plot.\n", "\n", "Instead of instructing the computer to \"go through a data frame and plot any observations of eastbound cyclists in blue, any observations of westbound cyclists in red, etc\", the `seaborn` syntax is more similar to saying \"color the data by direction\". Thanks to this functional way of interfacing with data, only minimal changes are required if the underlying data change or to switch the type of plot used for the visualization. It provides a language that facilitates thinking about data in ways that are conducive for exploratory analysis and allows for the creation of publication quality plots with minimal adjustments and tweaking.\n", "\n", "Before the first plot is created, the line `%matplotlib inline` is used to specify that all plots should show up in the notebook instead of in a separate window." ] }, { "cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [], "source": [ "import seaborn as sns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's make a dataframe with just weekday counts to look at weekdays and weekends separately." ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [], "source": [ "bike_counts_weekdays = bike_counts.loc[(bike_counts['day_of_week'] != \"Saturday\") & (bike_counts['day_of_week'] != \"Sunday\")]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The relationship between one quantitative and one categorical valuable will be explored while stratifying the data based on its remaining categorical variables. To start, let's visualize summary statistics of bicycle counts across the day with a boxplot." ] }, { "cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.boxplot(x='hour_dt', y='bikes', data=bike_counts_weekdays)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot parameters can be modified to change the appearance." ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 114, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.boxplot(x='hour_dt', y='bikes', data=bike_counts_weekdays, width = 0.4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In a boxplot, the xy-variables are the categorical groups (the hour) and the measurement of interest (the bicycle counts).\n", "\n", "The aim of a box plot is to display a few statistics from the underlying distribution of one quantitative variable between the values of one categorical variable. The inclusion of multiple distribution statistics facilitates the comparison of more than just the mean + standard deviation (or another single measure of central tendency and variation). The `seaborn` box plots are so-called Tukey box plots by default, which means that the graphical elements correspond to the following statistics:\n", "\n", "- The lines of the box represent the 25th, 50th (median), and 75th quantile in the data. These divide the data into four quartiles (0-25, 25-50, 50-75, 75-100).\n", "- The whiskers represent 1.5 * the interquartile range (the distance between the 25th and 75th quantile).\n", "- The flyers mark all individual observations that are outside the whiskers, which could be referred to as \"outliers\" (although there are many definitions of what could constitutes an outlier).\n", "\n", "Most of these plot elements are configurable and could be set to represent different distribution statistics." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Why would the distribution be so broad around 7-9 am and 4-6 pm? A boxplot can hide some things about the underlying data, such as if it's bimodal. To delve deeper into the data, we can start adding more categorical variables to look at. \n", "\n", "A very effective approach for exploring multiple categorical variables in a data set is to plot so-called \"small multiples\" of the data, where the same type of plot is used for different subsets of the data. These plots are drawn in rows and columns forming a grid pattern, and can be referred to as a \"lattice\", \"facet\", or \"trellis\" plot.\n", "\n", "Visualizing categorical variables in this manner is a key step in exploratory data analysis, and thus `seaborn` has a dedicated plot function for this, called `catplot()` (short for \"categorical plot\"). This plot can be used to plot the same violin plot as before, and easily spread the variables across the rows and columns, e.g. for the variable `direction`. **Note**: if you have an older version of `seaborn`, replace `catplot` with `factorplot`." ] }, { "cell_type": "code", "execution_count": 115, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 115, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.catplot(x='hour_dt', y='bikes', data = bike_counts_weekdays, col = 'direction', kind = 'box')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By splitting the data to by the direction of travel, we can see that the broadness of the distribution during those two time periods was actually concealing two peaks that are split based on direction of travel. The eastbound count is much higher in the morning rush hour, and the westbound in the afternoon. People are heading into downtown in the morning and leaving it in the afternoon." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can achieve a similar effect by colouring the data by `direction` instead of splitting it into two plots." ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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VHQb8w32OiJwOTAHOACYBvxGRwlQO2Jarzdoa+6yNyV+BNlKLyADgauBB4Nvu5uuAS9zHc4HFwN3u9qdVtQ74SESqgHOBZckcs3PnzlRXV9O7d2/rshkwVaW6uprOnTtnOyumjQlPpxIKhQCYMGGCTaOSg4LuxfRL4HtA96htfVV1h/v4UyDcLagEeDtqv+3utiZEZBowDZxePc0NGDCA7du3s3v37lZn3iTWuXNnBgwYkO1smDaqtrY221kwcQQWIETkGmCXqq4UkUu89lFVFZGk6ihU9VHgUXB6MTV/vUOHDgwdOjSFHBtjMiVcWpgxY0aT5ya3BFmCGA9cKyJXAZ2BE0TkCWCniPRT1R0i0g/Y5e4fAgZGpR/gbjPGGJMFgQUIVb0XuBfALUF8V1VvEpGfAlOBWe7v590kLwBPicjPgf7AMCDx8F9jTJti07m3HdkYST0LeFZEvg5sBW4AUNX1IvIs8B5QD3xLVW0KT2PyTFVVFZXrNtDQpRcFR51a4sp1GxKkMtmQkQChqotxeiuhqtXAxBj7PYjT48m0Y6FQiEMHC/nPVSdEtm09WEjXkNU45ouGLr2oPfWqyPPija9kMTcmFhtJbYwxxlPeT9Zn2p6SkhLq6ne0nIuppEWv5xasf70x6WMBwuQl619vTOtZgDB5xfrXG5M+1gZhjDHGkwUIY4wxnixAGGOM8WQBwhhjjCcLEMYYYzxZLyZjTEaFQiEKD+9vMnq68HA1oVB9FnNlvFgJwhhjjCcrQRhjMqqkpIRP64pazMVUUtI3TiqTDVaCMMYY48kChDHGGE8WIIwxxniyAGGMMcaTNVKbnLStxlkwaOdh5x6mrlEYluU8GdPeWIAwOae0tDTy+Ki7ZvGw0tIm240xwbMAYXJO9BTd4Wm7Z8+ena3sGNNuWYAweSO8mhwQ+T1jxgxKS0ttXQhjUmABwuSNqqoqNq9fzaBuDXQ85rRdbF6/Osu5MqbtsgBh8sqgbg0t1rI2+cPWHM8sCxDGmDbH1hzPDAsQxpg2w9YczywbKGeMMcaTBQhjjDGeLEAYY4zxZAHCGGOMJ2ukNsZkXOHhzyje+AoFR5wuydJYD9iCQbkmsAAhIp2B14FO7nHmqep9ItILeAYYAmwBblDVvW6ae4GvAw3AdFX9e1D5M8a0XirjEqLn1KqqOuhuO83m2spBQZYg6oDPqWqNiHQA3hSRvwFfAP6hqrNE5B7gHuBuETkdmAKcAfQHForIcFVtCDCPxpg0SGZcgs211XYEFiBUVYEa92kH90eB64BL3O1zgcXA3e72p1W1DvhIRKqAc4FlQeXRGNM6Ni4hvwXaSC0ihSJSCewCFqjqO0BfVd3h7vIpxyseS4CPo5Jvd7cZY4zJgkADhKo2qOpoYABwroiMbPa64pQqfBORaSKyQkRW7N69O425NcYYEy0jvZhUdZ+ILAImATtFpJ+q7hCRfjilC4AQMDAq2QB3W/P3ehR4FGDs2LFJBReT30KhEIcOFjaZoG/rwUK6hlqcRsYYHwIrQYjISSLS031cDFwObAReAKa6u00FnncfvwBMEZFOIjIUGAYsDyp/xhhj4guyBNEPmCsihTiB6FlVfUlElgHPisjXga3ADQCqul5EngXeA+qBb1kPJpOMkpIS6up3tJjuu1OJNWUZk4ogezG9C5zlsb0amBgjzYPAg0HlyRhjjH82ktoY0ybYkrKZZwHCGNMmVFVVUbluAw1delFw1OmfUrluQ5Zzld98BQgR+SIwX1UPisgPgTHAT1R1VaC5M8bkrGzc0Td06UXtqVdFnhdvfCWQ4xiH3xLE/6eqz4nIhcBlwE+B3wLnBZYzY0xOszv6/Oc3QIR7E10NPKqqL4vITwLKkzGmjbA7+vzmdxxESET+D3Aj8IqIdEoirTHGmDbI70X+BuDvwJWqug/oBcwMLFfGGGOyzleAUNXDOFNiXOhuqgc2B5UpY4wx2ee3F9N9wFhgBPBHnKm7nwDGB5c1Y5K3rcaZi2nnYefep65RGJblPBnTVvltpL4eZ1T0KgBV/UREugeWK2NSEL0i2VG32+Ww0lJbqSwgoVCIwsP7mzRMFx6uJhSqz2KuTDr5DRBHVVVFRAFEpGuAeTImJbZSmTHp5TdAPOv2YuopIt8AvgY8Fly2jDG5rqSkhE/rilp0cy0p6RsnlWlLfAUIVf2ZiFwOHMBph/iRqi4INGfGGGOyym8j9edV9W/Agqhtt6nqI4HlzBhjTFb5nmpDROpU9TUAEfkecClgAcIYk7TwPE7hOZwqKioSzt9kjeKZ5zdAXAu8JCIzcZYNPRW4LrBcGWPaheLi4mxnwcThtw1ij4hcCywEVgKTVdXWgzamnSs8/BnFG1+h4Iizip801gOJG6lTme3VGsUzL26AEJGDgALi/u4InAJMFhFV1RPipTfG5K/o8SVVVQfdbafZuJM8EjdAqKoNhjPGeLJxJ/kvUQniVFXdKCJjvF63BYOMMSZ/JWqD+DYwDfgvnCqmsHCV0+cCypcxxpgsizubq6pOcx9eBbwM7Af2AS+424wxxuQpv91c5+KMon7Yff5l4HGcdSKMMcbkIb8BYqSqnh71fJGIvBdEhoyB1AZSGWPSy++KcqtE5PzwExE5D1gRTJaMOa64uDipwVQVFRXMmDEjElwqKioCzJ0x+S1RL6a1OI3RHYClIrLNfT4Y2Bh89kx71drSgo3QNab1ElUxXZORXBiTJlYNZUz6JBootzVTGTHGmERSndrDpMZvI7UxxmRVa6b2CHd6CIVCAEyYMMFKmz5YgDDGpCyTvc3SMbVHbW1tWvOU7/z2YkqaiAwUkUUi8p6IrBeRGe72XiKyQEQ2u79PjEpzr4hUicj7InJlUHkzxqRXsr3NMq28vJzZs2dTWlpKaWmplR58CrIEUQ98R1VXiUh3YKWILABuBf6hqrNE5B7gHuBuETkdmAKcAfQHForIcFVtCDCPxphWsAttfgssQKjqDmCH+/igiGwASnAWGrrE3W0usBi4293+tKrWAR+JSBVwLrAsqDwaY/JfuBoMiPyeMWOGlSR8yEgbhIgMAc4C3gH6usED4FOOd0EoAd6OSrbd3WaMCVguNeJWV1fz4x//mPvuu4/evXu3+v2qqqqoXLeBhi69KDjqzDlauW5Dq9+3PQisDSJMRLoB/w3cqaoHol9zV6VLamU6EZkmIitEZMXu3bvTmFNjTG1tbdYbcufOncvatWt5/PHH0/aeDV16UXvqVRwaPYVDo6fQ0KVX2t47nwUaIESkA05weFJV/8fdvFNE+rmv9wN2udtDwMCo5APcbU2o6qOqOlZVx5500knBZd6YdiK6CiYsW9OUVFdXM3/+fFSV+fPnU11dnfE8mOOC7MUkwO+BDar686iXXgCmuo+nAs9HbZ8iIp1EZCgwDFgeVP6MMY5wFczKD3dy8Khy8KhSuW5Di6CRCXPnzqWxsRGAhoaGtJYiTPKCLEGMB24GPicile7PVcAs4HIR2Qxc5j5HVdcDzwLvAfOBb1kPJmMyI1eqYBYuXEh9fT0A9fX1LFiwICv5MI4gezG9ibPynJeJMdI8CDwYVJ6MMbntsssu45VXXqG+vp6ioiIuv/zybGepXQu8kdoYY/yaOnUqBQXOZamwsJBbbrklyzlq3yxAGGNyRu/evZk0aRIiwqRJk1p0c7X1PjLL5mIyxuSUqVOnsmXLlrilh0xN65FL40OywQKEMdiFIJf07t2bhx9+2PO1bP1Psj02JFssQJh2r6KigiVLljQZJLZkyRLA5hpq78L///Dsse3tfLAAYdq9qqoqDu/bxaBuDew85jTLHd63KyvjALIhFApReHg/xRtfiWwrPFxNKFSfxVyZXGABwhhgULcGvj/m+Eww/7nqBF/prGoq91kATJ0FCNPuhUIhDh0sbBIUth4spGuoxUwvMbXlOuqSkhI+rSui9tSrItuKN75CSYkt5dneWYAwphVyrY461RJNPq/1nI0AGG7XCh+/rU4tbgHCtHslJSXU1e9oUcXUqST7s803n/ra74UnmRJNa9Z6NrG15VJlmAUIEyiro/fm90IfPfX1XXfdBcS/8KRSoknHWs+mqfLy8kgnh7b8WVqAMBmRD3dTqYoOBtEBMtFn0nzq61tuuSVvLjymbbAAYQKVa3X02dI8GPi50HtNfR0uRRiTCRYgjAlYdDBIJkB6TX3dVgJEKo200QMWw4qLi31VSyY6Xj43wgfJAoQxOSrZqa+jV4YL/w6X3LLRiybZasWqqir2Ve+mQ8HxVYj3Ha7xPWAx1vGsET51FiBMYGJdsHKxy9+2GmccxM7DzkjqukZhWII0qf594XSJLuJTp05l/vz5gDP1dX19fWQmU6904ZXhGrr0ouCoc5Fd+eFOCg9/lvDvb56nioqKVv2PUm0rKe1Rn9KAxXjHS7URvi2dv0GxAGECU1VVxeb1qxnUrYGO7hQWm9evznKuWoq+kzzqXgiGlZYmvMNM9e8Lp+vk3inXbV3BtprCFvuFp75+8cUXmTRpElu2bEmYLrwyXLToEcSJZGqW1LbAK+BWrtuQ5VxllgUIE5hQKIS6tQV9uziNrVsPFka6vOaKVO8wE/19se5Aq6qqfE/tET319QMPPJDylCCJ5MIdcTpGtKdb84CbTLDNBxYgjAlIzCqfQ4ehp7/3iDf1tTFBswBhApPLI5SbS6UO3s/f51Xl023FHLYmuFP2GmDYmjvsUCjE5MmTI/kOsh7dbxtLc7l2vqQ6yV+qf38usgBhTJR4dfDNB7xlQjoHGGZqsKLfNpZ8FS45aoFzefXbUSAXWYAwBv918Gm5yBYUMrh7Xdw7Za8BhlVVVSnfYZdE7ZOJEdiptpVsqylkxptO/VvfLo1sqylM2JvMj1RLiKlO8pcvbRcWIIzxqfmAt/DFO59lclbScK+x8GfcaXApwyBub7Jkx35YL63kWIAwbVrz2U4zrWp/Ef+x5MTI82ONwhkZz4XDq84cjtebl6RYl5+pqqnmpSY/JR2vrsZeVVptre4/V1iAMG2a12ynmVJaWkooFGpyAe1ZXBy54411waahPjIgz0u87rEDO6SQ0cYG9u3bF8lnMo2mbWFywObVWZC+7r+pyKcV7CxAmEClMkLZL6/ZTjNZiigvL0/5zvTgsYKYde2pdo/1qjMH6LbqT3Skjo7H6gD/jcap9sZpTW+r6ODY3kYt5yILECYwqY5Q9ivXZzuNdcHuWvk0nToKR93nXnXtnt1jV/0JIqmSk0qjcbZ6I+VSO0Eqk/zl0xKuFiBMYIJeiKYtzHba/ALT2PkEpLGe0tLTIvs0/0ziVU1V7S8KpJePl/BI8fAocQBVEo6Eb814htaUylIVqx3LJvmzAGHasGRnO800zwvMKX2BvpSWlvqepTRCBAo7cLRDJ8C75OEVkGhoe3XfmRSrHas1NziFhz+ja+XTgPM/cMZBWAnCmIxpPtvpLbfckuUcNZXoAhOrm2ysqqnija8w+pTjF5nmF6tYAWn9+j0JR27HykcujWwOQhDtWM2760bfFLQ1gQUIEfkDcA2wS1VHutt6Ac8AQ4AtwA2qutd97V7g60ADMF1V/x5U3kzmpHsa6WhPPfUUIgI4F7NsdHMNildJoPDwZ4RC9U16I0U34sYKSJMnT+bQ3l0Z/gsyw6tBHPw3igfRjpVKd91cFWQJYg7wK+DxqG33AP9Q1Vkico/7/G4ROR2YApwB9AcWishwVW0IMH8mg4JqeCwoKKCgoIDTTjst8c4pyvRCPPGqpg4dOpT0+7WmJBDUyOZckWvtWJkcmOhHYAFCVV8XkSHNNl8HXOI+ngssBu52tz+tqnXARyJSBZwLLAsqfyYz/Jzczec48vuFiO6jP3PmzNQzmUBrFuKJJV53zvLy8iavQ3YmektlZHNYpgKLV/AD/wEwl9qxwt+Dzz5zzqva2tpIh4BsBYlMt0H0VdUd7uNPOd5qUwK8HbXfdndbCyIyDZgGMGjQoICyaTItU6N1U+F8SZ3A0Ng5uipDfa1tEX2xj65i81OqSlcpM8b9AAAWHUlEQVTJK5ULdqpVJa0JLKloPtYmmYCUS+1YVVVV7N57AC3sDMD+gu7U7P0s+c4MaZS1RmpVVRHRxHu2SPco8CjA2LFjk05vck/zOY7yUfMLfaLunKl+Dl5tPpm+YLe2Dj6Z6VO8xtok8/c1X7UvXe1YqQz4C9+IpHITEpRMB4idItJPVXeISD8g3HIWAgZG7TfA3WZM1sXrVeRn8FM2+vZHB6S21miazPQp6RhrE71qXzrl0oC/VGU6QLwATAVmub+fj9r+lIj8HKeRehiwPMN5Mybrk/+1VlsvgWVj+pQgVu1L5aYgF0dgx54xrJVE5M84jcwjRGS7iHwdJzBcLiKbgcvc56jqeuBZ4D1gPvAt68FkglJRUcHkyZOZPHkyFRUVTV6LvnvNBdXV1UyfPp3q6uqsHD+6ymrGjBktPq908+p2mm/i/U/DA+y6Vj5N8cZXfHeEiD6n0/l/CixAqOqXVLWfqnZQ1QGq+ntVrVbViao6TFUvU9XPovZ/UFX/VVVHqOrfgsqXMeA0ijdvGG9+95qti3K0dAWs1lzoi4uLM1Zd4tXtNN/E+p+WlpYyeuRpdO8odO8onH1KX0aP9D+1h9c53Vo2ktpkTarjC1o7LiFWo3iuTf6X7uqWVC7ymW4/yaVup5D+gZ7x/qetaSsKalp2CxAmI7zq9lMdXxDEuASIP2gq1sjmIOfXSWfAykZDeSoy3e3U78C0dJWgcu0mJBELECYjvHqmtGZ8gdd02K1d9zfW3WuiSfeCkmujfDMhqG6nzYVLBqFQKO7AtHil2FQGd7a1/6kFCBO4bC/s41esu1c/XSkT9X5KpXdUrlW3ZEpQ3U6jRS9V2lDkDrDrUMe2fQd9D0xLpb4/0f80lfETqS7s5EdgjdTGhMXqmVJSUkJDl97UnnpVk5+GLr1TXj+5NcJ3ryKS9N1rosbkVBqbp06dSkGB8xXN9ijfZLWmUTzc7TTIm4jwWhfgjLwOr3nhZ70LcG4aSt3Fr5K5CPv5nybbKSBc5XrwqHLwqLLyw51UrtuQlhHYVoIwgUt33X6sBXUSrfvrp3E7lbvXRCWkWK8nKlVkqrolKPkwUCzdEs1AnGpbUfMq19ZWt4ZZgDC+RNfZQnL1roHU7TfUU1izi8htoMjxxzH4adxOZdBUoobHWK/7GTGcieqWIOR6o3hJSQmb9+1i5+ECjjRIZPuxRgm89JqJGYjTxQKESUoq9a6tqdv3MmHChEiwCuenuLg40gslltZOuhdLooZHr9dvueUWX+0yQYzyNcdvTkKhEAVR53TP4uK0dTzwKiEGMQOxV4k6UWnaLwsQxpfmfbSTuTtMVFUSa7bTRHnJFYkaHr1eb2vdHXNdso27mTiHkplTKldZgDAZkaiqJBP11a2ddC+WRH33vV6/+eab21R3x7Ygl9o8mrc71dfXs337diDx4M5ke7wFOYeTBQiTUDpWVItXVZLr9dWJJCoheb3eXruwBiVT55Df70LzEuLbb79N7f7dDOrWQMdjTi+muq0r2FZT2OIYuVTysABhEoruM57o5G6vEpWQmr+eSwvVGP/8fheatzvt3buX4Sc0eK58Fy3XxgzZOAjjy6Buzsk9+8J9zL5wH98fc4BB3dI34W6mZi0Nd6tNZcbMeBL13W/+emvGXGR7htd8k8zn6Xf8xGWXXUZRkXP/XVRUxIknnugrL6nOZpvqLLCJ5EUJojVdME1ioVCIQwcLW9ztbD1YSNc0rXaViWJ1a6fMSLYxPZFUu7DmUhVEPgji82xeQlRVtvr4DqUyFUfzFQPTOQ1MXpUggpju1gSvNdNsJ3P3V15ezuzZs5k9e3ZkFGz4ud+LfTqnvk5lxHAuTkneliX7eZaUlDC4u1Oajv4Z3L2hyfiJ5iXEgoIC6hqErQcLqdpfRNX+IrYeLKQuagwGtCx5hNum4q1hEh7VHS0d02xAnpQgWtMF0yRWUlJCXf0Oz/rTTlFfCr8zYzbXmi6fmbybzoXGdOsem16pfJ7bapySwM7D7hxOXRrZVlPIsGb7RZcQi4qKWjRuhy/q0Rf35iWP+vp6ZsyY0WRSwSVLllBVVdXi+xVEL642HyBi9SpIVwQ1Dr9filRKcKnOcJlqg166q4oyqa3NBprrkv08oy/mR91zqNPgUoY1ew2a9tzzOyi0eY+3LVu2tJhUsE/9Djav39UkXVA3L20+QCxZsoTde6qhsAganUbTyjXvEgqF2tQXP5f5/VKkumhJql0+W3M3nUt95pNh3WPTK9nPM9XR/2F+bk6iSx7/8R//0aRRPMzvpIKpTkse1uYDBACFRTR0OX7nWHjY6mXTKdGXorXjJFLt8pnq3XQuVBWlyrrHplc2Ps9ENyfpnl6lNe2ybT5ABDmK0PjjWYpb9x401PsqyaU6a2l7vJtu6zO85ppMf57J3pz4bf9rLvqmLSw89XoyvZvyqheTSZ+k+9q7pbiGbic7P116OwHDp6lTp1JWVpbUHVxbXi+hNVL5rExsqXye0etdJLPWRaaEB/TVbV1Bx2MH6HjsAHVbV7B5/eqk1olo8yUIaLmmgDTWE+Rawe1B895B8RZvLykpYffeAxQcOYA0Hjv+Jo0NvqdOTqVY3V7vpm2G1/RK9fPMVDuW3w4i0ZoP6Avz23YR1uYDhOfgp9LTKC0tjdtAE34tun6uuLjYBtnh3TsozOtLET11cvPPM8g1m6Htrpdg2rZMtWMl02sqCG0+QHg1oJaWlrZYkLx53+Gqqip2V38GBcfnUKk5XJuWZfragngzRibbO6g1M1G2lt1Nm3yWaq+p8IJIQJOShwhJLYiUl20Q4fq3PvU76FF0jB5Fx9y+w03r3xq6nUzNmJsjPw3dTs5irjMr3hrJ4YZfcHoHvfzyy2l5X2NMapJt8ygtLWXYGWfRafBYjnY4gaMdTqDT4LEMO+OspEoebb4EAbSoH29oaEAS1L/FW4WptX2HU5HqnXcq6RINMBs4cCAfffRR5PmgQYPS8r7GmNQl0+aRqOQxffp0X++TVyWI6Hly/Mx7Ek+m53VK9c47lXSxZoysqKhgxowZTU5EEaFz586+7lpSnYnSGBNfeXk58+bNY968eUndsLa2t1VeBIjwJGzhD/Dqq6+mbNRoho88i05dutGpSzeGjzyLslGjmTBhAhCuhxMKjhyI9H6isYHa2qbtEOG+w34+3HgTasWT6gRsqabzGmAGzt9auW4D7378GSqFKNBQ1Jn171f5apuJ9b7GmOxpzQSTeVHF1Fw4wkYPFmk+ore0tLRJI3Zxo3AYpfZQDZvWreZYo1Pa2LRuNXUN4nvqjniljliT2aU6ZUSy6cLHP3r0aJPtxcXFVFRUONVvDceckehuHzlpqIfGel9d49rjwDVjcllre1vlXIAQkUnAbKAQeExVZ7Xm/WJFzvCHFn3Bfv/99zl6JH610r//+7+zZcuWyIUZoLGxERGhS5cukQAxf/585s+fT79+/Xjsscci+3oFkOaNwn6njEiUrnlAev/99zlypJbjFW0CKHur97BkyRJ69uxJbW0tdXV11OP8fQU0UFBUSM+ePRPmx6aBMCa/iIZHU+QAESkENgGXA9uBfwJfUtX3vPYfO3asrlixIm3Hj154KFyy6NWrV5O7/cmTJ7N7zx4guj1DidW60adPH+bNm9eiIT1cggE4ePAgdXV1kTS9e/fmkksuoby83HO8RkNDA/X19ZHgEFZUVMR1111HeXl5JJCF9ykoKHCDmlIAhMObuD+9+pzEvHnzIp9DKtN2A/z85z/nxRdf5Nprr7VZRo3JUSKyUlXHJtov10oQ5wJVqvohgIg8DVwHeAaIdIuumorVi6mkpKTF+AkajtG1a9fI+AtoOdf7kiVL2LNnTyTJmjVrYuajurqaJUuWUF5e7s5z5B2QioqKmgSJjh07Rh7v27evyWvhEo9IAcVdutDY2EhdXR09e/Zk4MCBLWZlTbVYagPXjMkfuRYgSoCPo55vB87LdCbiXSDDd/5NRwz3iDR+x2rz6NmzJ/v27fOsmgovDAJEqqoSVemESyax7tgnTJiQlZHiNnDNmPyRawEiIRGZBkwD//3z0yle8KioqIjZ5hHdDuEl1niGeBd6iH3H3pantDbG5IZca4O4ALhfVa90n98LoKr/v9f+6W6DMMaY9sBvG0SujYP4JzBMRIaKSEdgCvBClvNkjDHtUk5VMalqvYjcAfwdp5vrH1R1fZazZYwx7VJOBQgAVX0FeCXhjsYYYwKVa1VMxhhjcoQFCGOMMZ4sQBhjjPFkAcIYY4wnCxDGGGM85dRAuWSJyG5ga4yX+wB7YrwWj6WzdJYuO+naQh7zJd1gVT0p4Tuoal7+ACssnaWzdG0nXVvIY3tIF/1jVUzGGGM8WYAwxhjjKZ8DxKOWztJZujaVri3ksT2ki2jTjdTGGGOCk88lCGOMMa2QlwFCRCaJyPsiUiUi9/hM8wcR2SUi65I81kARWSQi74nIehGZ4TNdZxFZLiJr3HQ/TuKYhSKyWkReSjKvW0RkrYhUiojvhTREpKeIzBORjSKywV23I1GaEe5xwj8HROROH+nucj+PdSLyZxHp7DOPM9w06xMdx+t/LSK9RGSBiGx2f5/oI80X3eM1iojn3Pox0v3U/SzfFZG/iEiL5QNjpPtfbppKEXlVRPr7SRf12ndEREWkj8/j3S8ioaj/4VV+jyci5e7fuF5E/rfP4z0TdawtIlLpM91oEXk7fF6LyLk+040SkWXud+JFETnBI53n99vH+RIrXdxzJk66uOdMnHQJz5m4WtsNKtd+cKYJ/wA4BegIrAFO95HuYmAMsC7J4/UDxriPuwObfB5PgG7u4w7AO8D5Po/5beAp4KUk87oF6JPCZzoX+Hf3cUegZwr/k09x+l7H268E+Agodp8/C9zq4/1HAuuALjgzFC8ESpP5XwP/G7jHfXwP8JCPNKcBI4DFwNgkjnUFUOQ+fqj5seKkOyHq8XTgEb/nMTAQZxr9rV7nQIzj3Q98N8Fn75XuUvd/0Ml9frLffEa9/l/Aj3we71Xg8+7jq4DFPtP9E5jgPv4a8L880nl+v32cL7HSxT1n4qSLe87ESZfwnIn3k48liHOBKlX9UFWPAk8D1yVKpKqvA58lezBV3aGqq9zHB4ENOBe6ROlUVWvcpx3cn4QNQiIyALgaiL+GaZqISA+cL9fvAVT1qKruS/JtJgIfqGqsQY3RioBiESnCueB/4iPNacA7qnpYVeuBJcAXYu0c4399HU4gxP39/yRKo6obVPX9eBmLke5VN58AbwMDfKY7EPW0Kx7nS5zz+BfA97zSJEgXV4x03wRmqWqdu8+uZI4nIgLcAPzZZzoFwnf/PfA4Z2KkGw687j5eAPy/Hulifb8TnS+e6RKdM3HSxT1n4qRLeM7Ek48BogT4OOr5dnxcsNNBRIYAZ+GUBvzsX+gWo3cBC1TVT7pf4nzRG1PIogILRWSlOGt7+zEU2A38UZxqrcdEpGuSx52Cx5e9ReZUQ8DPgG3ADmC/qr7q4/3XAReJSG8R6YJzFzkwyTz2VdUd7uNPgb5Jpk/V14C/+d1ZRB4UkY+BrwA/8pnmOiCkqmtSyF+5W0Xxh+bVKHEMx/l/vCMiS0TknCSPeRGwU1U3+9z/TuCn7ufyM+Ben+nWc/zm8YskOGeafb99ny/JXhd8pIt7zjRPl8o5E5aPASIrRKQb8N/Anc2idkyq2qCqo3HuBs4VkZEJjnENsEtVV6aYzQvd430e+JaIXOwjTRFO0fy3qnoWcAinSO2LOEvHXgs852PfE3G+sEOB/kBXEbkpUTpV3YBT7H4VmA9UAg1+8+jxfkqSd1qpEJEfAPXAk37TqOoPVHWgm+YOH8foAnyfJC8Mrt/iVNWOxgnY/+UzXRHQCzgfmAk865YK/PoSPm4oonwTuMv9XO7CLe368DXgdhFZiVMtczTWjvG+3/HOl1SuC/HSJTpnvNIle85Ey8cAEaLpncAAd1tgRKQDzj/lSVX9n2TTu1U2i4BJCXYdD1wrIltwqs4+JyJPJHGckPt7F/AXnOq4RLYD26NKN/NwAoZfnwdWqepOH/teBnykqrtV9RjwP8A4PwdR1d+r6tmqejGwF6cONhk7RaQfgPu7RbVIOonIrcA1wFfcC0yynsSjSsTDv+IE3DXueTMAWCUi/5IooarudG9iGoHf4e98Aeec+R+3GnU5Tmm3RcO4F7dq8QvAMz6PBTAV51wB50bEVz5VdaOqXqGqZ+MEpA9i5Mnr+53wfEn1uhArXaJzxsfx/J4zEfkYIP4JDBORoe7d6xTghaAO5t4Z/R7YoKo/TyLdSeGeCCJSDFwObIyXRlXvVdUBqjoE5+96TVUT3mG7x+gqIt3Dj3EavRL22FLVT4GPRWSEu2ki8J6fY7qSuRvcBpwvIl3cz3UiTl1qQiJysvt7EM4F5qkk8gjOOTLVfTwVeD7J9L6JyCScasJrVfVwEumGRT29jgTnC4CqrlXVk1V1iHvebMdpzPzUx/H6RT29Hh/ni+uvOA3ViMhwnI4NfiebuwzYqKrbfe4PTpvDBPfx5wBfVVNR50wB8EPgEY99Yn2/454vrbgueKZLdM7ESZf0OdOEJtGi3VZ+cOqgN+HcEfzAZ5o/4xSjj+F8ib7uM92FOMXLd3GqNiqBq3ykOxNY7aZbh0ePjQTpLyGJXkw4VQVr3J/1fj8XN+1oYIWb178CJ/pM1xWoBnokcawfuyfxOuBPuD1hfKR7AydwrQEmJvu/BnoD/8C5uCwEevlIc737uA7YCfzd57GqcNrJwueLV28kr3T/7X4u7wIv4jRCJnUeE6MnW4zj/QlY6x7vBaCfz3QdgSfcvK4CPuc3n8Ac4LYk/3cXAivd//07wNk+083AuU5sAmbhDhz28/32cb7EShf3nImTLu45EyddwnMm3o+NpDbGGOMpH6uYjDHGpIEFCGOMMZ4sQBhjjPFkAcIYY4wnCxDGGGM8WYAwxhjjyQKEMc2IyBBJctr3NB57johMdh/f6U6VYUxWWIAwJgPcKSSSdSfOjLbGZIUFCGO8FYrI79zFV14VkWI5vjBNeNGWEwFEZLG4i7+ISB93ziNE5FYReUFEXsMZdduCOH4lzgJXC4Hw9A/TcSYsXCQiizLw9xrTggUIY7wNA36tqmcA+3AmOXscuFtVz8SZguI+H+8zBpisqhNivH49zgIypwO34E5OqKoP48wxdKmqXtqaP8SYVFmAMMbbR6oaXvJyJc6sqD1VdYm7bS7OQkqJLFDVeAvxXAz8WZ1ZUz8BXks5x8akmQUIY7zVRT1uAFqsGx2lnuPfpeZraB9KZ6aMySQLEMb4sx/YKyIXuc9vxlnaFJwZUs92H09O8n1fB250VxfshztNtusgzkI2xmRFKj0rjGmvpgKPuF1PPwS+6m7/Gc6qadOAl5N8z7/grGHwHs56GMuiXnsUmC8in1g7hMkGm+7bGGOMJ6tiMsYY48mqmIzJABEpw1mhLVqdqp6XjfwY44dVMRljjPFkVUzGGGM8WYAwxhjjyQKEMcYYTxYgjDHGeLIAYYwxxtP/BdmaCemsY+YSAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.boxplot(x='hour_dt', y='bikes', data=bike_counts_weekdays, hue = 'direction')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The text is a little small, which can be changed with the `set_context()` function from `seaborn`, using a number above `1` for the fontscale parameter. The context parameter changes the size of object in the plots, such as the line widths, and will be left as the default `notebook` for now.\n", "\n", "These option changes will apply to all plots made from now on. Think of it as changing a value in the options menu of a graphical software. " ] }, { "cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [], "source": [ "sns.set_context(context='notebook', font_scale=1.2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`seaborn` allows you to choose which data you will explore and easily change things like the plot type and other plot characteristics. Above, all we had to change was adding the `hue` option. We could change the boxplot to a violinplot by simply changing the function call." ] }, { "cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 118, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.violinplot(x='hour_dt', y='bikes', data=bike_counts_weekdays)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This doesn't look very good because the width of each violin is scaled so that they each cover the same area. We can change the way the violin width is plotted using the \"scale\" parameter. Let's change it to scale the width by the number of counts." ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.violinplot(x='hour_dt', y='bikes', data=bike_counts_weekdays, scale = \"count\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Or we could plot only a few of the hours by subsetting the data frame:" ] }, { "cell_type": "code", "execution_count": 120, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.violinplot(x='hour_dt', y='bikes', \n", " data=bike_counts_weekdays[(bike_counts_weekdays['hour_dt'] == 7) | \n", " (bike_counts_weekdays['hour_dt'] == 8) | \n", " (bike_counts_weekdays['hour_dt'] == 9)])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we wanted to include the afternoon rush hour as well, we could keep adding lines to the subsetting code above. But there's an easier way! `pandas` has a special `isin()` method for comparing a data frame column to an array-like object of names, so we can use `isin()` to get all the counts for a list of hours we define." ] }, { "cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [], "source": [ "rush_hours = [7, 8, 9, 10, 16, 17, 18, 19]\n", "bike_counts_weekdays_rush = bike_counts_weekdays.loc[bike_counts_weekdays['hour_dt'].isin(rush_hours)]" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 122, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.violinplot(x='hour_dt', y='bikes', \n", " data=bike_counts_weekdays_rush)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The colours can be changed with the `palette` keyword." ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.violinplot(x='hour_dt', y='bikes', \n", " data=bike_counts_weekdays_rush, palette = \"Blues\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also split the colours by direction on this smaller dataset." ] }, { "cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 124, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.violinplot(x='hour_dt', y='bikes', \n", " data=bike_counts_weekdays_rush,\n", " hue = 'direction',\n", " palette = \"Blues\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It would be nice to change the x and y-axis labels to something a little prettier. To do this, assign the plotting command to an object, and then use that axes object to change more plot elements." ] }, { "cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 125, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = sns.violinplot(x='hour_dt', y='bikes', \n", " data=bike_counts_weekdays_rush,\n", " hue = 'direction',\n", " palette = \"Blues\")\n", "g.set_xlabel(\"Time (h)\")\n", "g.set_ylabel(\"Bicycle counts\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">1. Create a violin plot of `bikes` vs. `day_of_week` using the `bike_counts` dataframe. Colour by `direction`.\n", ">2. (Optional) Change the plot orientation so that `day_of_week` is on the y-axis and `bikes` are on the x-axis. \n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le'ts explore a few other categorical variables. Using `hue` to colour data by different categorical variables is great if there are only a few, but it can get busy if there are many possibilities. For example, let's create a `pointplot` of counts vs hour, coloured by the day of the week." ] }, { "cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 126, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.pointplot(x='hour_dt', y = 'bikes', data = bike_counts_total, hue = 'day_of_week')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's not too bad, but it'll be cleaner if we show each line on its own axes with `catplot`." ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 127, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.catplot(x = 'hour_dt', y = 'bikes', col = 'day_of_week', col_wrap = 3, data = bike_counts_total, \n", " kind = 'point')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can go further by colouring the lines by another categorical variable, \"direction\"" ] }, { "cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "Could not interpret input 'direction'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m sns.catplot(x = 'hour_dt', y = 'bikes', col = 'day_of_week', col_wrap = 3, data = bike_counts_total, \n\u001b[0;32m----> 2\u001b[0;31m kind = 'point', hue = 'direction')\n\u001b[0m", "\u001b[0;32m~/anaconda2/envs/py3/lib/python3.6/site-packages/seaborn/categorical.py\u001b[0m in \u001b[0;36mcatplot\u001b[0;34m(x, y, hue, data, row, col, col_wrap, estimator, ci, n_boot, units, order, hue_order, row_order, col_order, kind, height, aspect, orient, color, palette, legend, legend_out, sharex, sharey, margin_titles, facet_kws, **kwargs)\u001b[0m\n\u001b[1;32m 3714\u001b[0m \u001b[0;31m# facets to ensure representation of all data in the final plot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3715\u001b[0m \u001b[0mp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_CategoricalPlotter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3716\u001b[0;31m \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mestablish_variables\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhue\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0mstring_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 154\u001b[0m \u001b[0merr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"Could not interpret input '{}'\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 155\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 156\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 157\u001b[0m \u001b[0;31m# Figure out the plotting orientation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mValueError\u001b[0m: Could not interpret input 'direction'" ] } ], "source": [ "sns.catplot(x = 'hour_dt', y = 'bikes', col = 'day_of_week', col_wrap = 3, data = bike_counts_total, \n", " kind = 'point', hue = 'direction')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Oops - there's no 'direction' column in the `bike_counts_total` dataframe. We need to go back to the original!" ] }, { "cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 129, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.catplot(x = 'hour_dt', y = 'bikes', col = 'day_of_week', col_wrap = 3, data = bike_counts, \n", " kind = 'point', hue = 'direction')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This clearly communicates a message: the counts depend on the day of the week and the direction." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A great aspect of the `seaborn` is that if there is a change of minds (or hearts) in what type of visualization to use, only minor modifications are needed to completely change the plot appearance. For example, to change the plot type to a boxplot, we only need to change `kind`." ] }, { "cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 130, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.catplot(x = 'hour_dt', y = 'bikes', col = 'day_of_week', col_wrap = 3, data = bike_counts, \n", " kind = 'box', hue = 'direction')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">\n", ">1. Add a new column to the `bike_counts` dataframe called 'weekend', and fill this column with True if `day_of_week` is Saturday or Sunday, False otherwise. \n", ">2. Create a two-panel cat plot split by the `weekend` variable and coloured by `direction`.\n", ">3. (Optional) Change the plot panel titles to \"Weekend\" and \"Weekday\". (Hint: assign the plot to a variable and look up how to change subtitles in seaborn. You will need to create a figure object, then use Python slicing to access each subplot.)\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To recap, `catplot()` facilitates the representation of variables within data as different elements in the plot, such as the rows, column, x-axis positions, and colors. There is a great description on this in the `seaborn` documentation:\n", "\n", "> It is important to choose how variables get mapped to the plot structure such that the most important comparisons are easiest to make. As a general rule, it is easier to compare positions that are closer together, so the ``hue`` variable should be used for the most important comparisons. For secondary comparisons, try to share the quantitative axis (so, use ``col`` for vertical plots and ``row`` for horizontal plots). Note that, although it is possible to make rather complex plots using this function, in many cases you may be better served by created several smaller and more focused plots than by trying to stuff many comparisons into one figure." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualizing two quantitative variable across multiple categorical variables\n", "\n", "In the last section, one quantitative variable was visualized across one or more categorical variables. Here, the relationship between two quantitative variables will be explored while stratifying the data based on its remaining categorical variables. First, reexamine the variables and their data types using the entire `bike_counts` data frame." ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 624 entries, 0 to 623\n", "Data columns (total 10 columns):\n", "date 624 non-null object\n", "day_of_week 624 non-null object\n", "temperature 624 non-null int64\n", "weather 624 non-null object\n", "direction 624 non-null object\n", "position 432 non-null object\n", "hour 624 non-null object\n", "bikes 624 non-null int64\n", "date_dt 624 non-null datetime64[ns]\n", "hour_dt 624 non-null int64\n", "dtypes: datetime64[ns](1), int64(3), object(6)\n", "memory usage: 48.8+ KB\n" ] } ], "source": [ "bike_counts.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The two quantitative variables are `temperature` and `bikes`. `hour_dt` is an integer, but it functions as a categorical variable.\n", "\n", "A scatter plot is the immediate choice for exploring pairwise relationships between continuous variables. `seaborn` has a convenient scatter plot matrix function, `pairplot()`, for plotting the pairwise relationships between all numerical variables in the data frame." ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 132, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# caution: this takes a long time with large datasets.\n", "sns.pairplot(bike_counts_total)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've already been looking at bikes vs. hour, but maybe there's something interesting with temperature and bikes. \n", "\n", "The corresponding function to `catplot()` for two continuous variables is called `lmplot()` (for \"linear model plot\")." ] }, { "cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 133, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.lmplot(x = 'temperature', y = 'bikes', data = bike_counts_total)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By default, it creates a scatter plot between the two variables and fits a regression line. The regression line can be removed for now." ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 134, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.lmplot(x = 'temperature', y = 'bikes', data = bike_counts_total, fit_reg = False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It looks like the graph is quite oversaturated and many data points are plotted on top of each other. Compare the number of distinct observations that are visible in the plot with the number in the data frame." ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(312, 6)" ] }, "execution_count": 135, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are probably not 312 distinct observations visible in the plot, which means many data points are plotted on top of each other obfuscating what is beneath them. This problem can be ameliorated somewhat by adding transparency (the `alpha` parameter) and reducing the size of each point in the graph (the `s` parameter). " ] }, { "cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 136, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.lmplot(x = 'temperature', y = 'bikes', data = bike_counts_total, fit_reg = False, \n", " scatter_kws={'s': 40, 'alpha':0.4})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The scatter plot arguments are passed as a dictionary here, instead of directly to parameters in the `lmplot()` function. This is a design decision taken in `seaborn` and helps for example to ensure there are no collisions among parameters (the scatter plot function that `seaborn` uses is from matplotlib and takes a lot of arguments, some of which would be inseparable from those for the regression line)\n", "\n", "Coloring the data points according to a categorical variable is an easy way to find out if there seems to be a dependence on that variable. Let's try this with `weather`." ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 137, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.lmplot(x = 'temperature', y = 'bikes', data = bike_counts_total, fit_reg = False, \n", " hue = 'weather',\n", " scatter_kws={'s': 40, 'alpha':0.4})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's hard to say, since there are so few days with rain. The City of Toronto has count data for many more intersections than just College and Spadina, and with all that data we might see something interesting to do with weather in this type of plot. \n", "\n", "Maybe it's better to compare the hourly counts on days when there was rain at one count but not on another." ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 138, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.catplot(x = 'hour_dt', y = 'bikes', col = 'day_of_week', col_wrap = 3, data = bike_counts_total, \n", " kind = 'point', hue = 'weather')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The limited size of the dataset means that we might not learn anything from these scatterplots, but they're good to know about nonetheless. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Using any plotting function with `seaborn` grids\n", "\n", "A major strength of the `seaborn` library is that it enables exploration of categorical variables through faceting, where the variables of interest are separated into the rows and columns of the plot grid as seen with `catplot()` and `lmplot()`. These grids are very flexible and can be used with any plotting function, not just those that exist within `seaborn`.\n", "\n", "The `seaborn` function `FacetGrid()` is the foundation for both `catplot()` and `lmplot()`, and can be used directly with a custom plotting function. To understand how it works, one of the scatter plots made with `lmplot()` can be recreated using the `FacetGrid()` syntax. The first step is to set up the grid." ] }, { "cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 139, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.FacetGrid(data=bike_counts_total, hue='weather', height=5)\n", "# `height` specifies the height of the figure and 5 is the \n", "# default value for this parameter in `lmplot()`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This empty grid is aware of which data frame will be plotted, but no graphical elements are added until a plotting function is mapped onto the grid. Let's add a line plot via the `matplotlib` function `plot()`. (Side note: `seaborn` (0.9) does have a dedicated function for relational [scatter](https://seaborn.pydata.org/generated/seaborn.scatterplot.html) and [line](https://seaborn.pydata.org/generated/seaborn.lineplot.html) plots, but the `FacetGrid()` syntax is still very useful to know, and can be used with other plots such as heatmaps, histograms, and density plots.)" ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 140, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "g = sns.FacetGrid(data=bike_counts_total, aspect = 1.5, height = 5) # `aspect` controls the width of the plot\n", "g.map(plt.plot, 'hour_dt', 'bikes')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Unfortunately, this does not give the expected result because all the observations are plotted together at each hour, and the line connects all observations even across days. `seaborn` needs to be instructed to draw separate lines for each day, which can be done by modifying the hue parameter." ] }, { "cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 141, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = sns.FacetGrid(data=bike_counts_total, hue='date_dt', aspect=2)\n", "g.map(plt.plot, 'hour_dt', 'bikes')\n", "g.add_legend(fontsize=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`FacetGrid()` can facet variables onto columns and rows just like `catplot()` and `lmplot()`. Use this to make a time series plot for each day of the week." ] }, { "cell_type": "code", "execution_count": 142, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 142, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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FCaWUUkoppZRSSsXVqLpah4i4RKRMRHQ4i1JKHSHNpUopdfQ0lyql1IFGWzIsAXbv3r073nEopdRAkEE6j+ZSpdRIprlUKaWOXp9z6ajqOaGUUkoppZRSSqmhR4sTSimllFJKKaWUiqtBL06IyCki8oaItItIk4g8FbXtTBFZJyJeEflQRC6P2TdXRB4VkTZ73z+KSOJg3wellFJKKaWUUkr1n0EtTojIycDTwB+BfGAs8FN7W5m97bdAFvAd4D4RWRx1iAeBNGA8MBtYBNw+ONErpZRSSimllFJqIAx2z4lbgbuNMQ8aY3zGmIAxZqW9bTmwwRjzF3v9M8C/gC/D/uLF2cB3jTHNxpgq4MfAVSKSNMj3QymllFJKKaWUUv1k0K7WISKpwGLgLRFZBUwAPgRuNMa8DMwDVsXstgr4tP37PMBrjNkSsz0FmAqsjzlfFlYPjGgl/XBXlFJq1NBcqpRSR09zqVJKHd5gXko0G6unxhXAecBGrN4S/xKR2UAGsDlmnxZ7PfbPlm62E9Um2reA/z7qqJVSanTTXKqUUkdPc6lSSh3GYA7r8Ng/7zHGrDXGBI0xfwJ2Yw3XaAMyY/bJstfTw3ai2kS7A6t3RvSy9KjugVJKjT6aS5VS6uhpLlVKqcMYtJ4TxphWEdkFmNhN9s91wDkx2xYBH0RtTxWR6caYrVHbfVjDQ2LP10JMTwsROfI7oJRSo5DmUqWUOnqaS5VS6vAGe0LMO4GrRWSOiDhF5CqgDPgPcD8wV0SuEhG3iJwPfAy4C8AYswd4HviliGSLSBFwM3CvMcY/yPdDKaWUUkoppZRS/WQw55wA+DXWpUCft39uAs63Cw+IyMeBXwG/ByqAq4wx70Xtf4W9rRwIA48B1w1W8EoppZRSSimllOp/g1qcMMYY4H/spbvtLwFze9i/Abh8YKJTSimllFJKKaVUPAz2sA6llFJKKaWUUkqpA2hxQimllFJKKaWUUnGlxQmllFJKKaWUUkrFlRYnlFJKKaWUUkopFVdanFBKKaWUUkoppVRcaXFCKaWUUkoppZRScaXFCaWUUkoppZRSSsWVFieUUkoppZRSSo0KJhJmy4s38OGKW+IdioqhxQmllFJKKaWUUqPC3rX3Ur/jeWq2PElH4/Z4h6OiaHFCKaWUUkoppfrImAiRcDDeYag+aKl8n/L37yJ3wmk4XMnsW3t/vENSUbQ4oZRSSimllFJ9tOutX7Hm8c9iIqF4h6J6IeBtZOtLPyI5s5TpZ/wPhbMuoW7HC/jaKuMdmrJpcUIppZRSSiml+qi54l28TTup3/FivENRh2EiYba+/GNCne3MPOsXON0plMy9AhGhct0D8Q5P2bQ4oZRSSimllFJ9EOr04G3eA8DeNfdiTCS+Aake7V1zDy0V7zFp6fdJzZ0CQGJaAWOmnk/NlqcIeBvjHKECLU4opZRSSimlVJ946rcAhoKp5+Nt3knjntfjHZI6hJbK9ylfdTcFU89j7PQLD9hWcszniIQDVG54JE7RqWhanFBKKaWUUkqpPvDUbQJg4gnfIimjmH1r7sEYE+eoVKyAt4EtL/6I5MxxTDn5h4jIAdtTssvIm3g6VRsfIxRoj1OUqosWJ5RSSimllFKqD9rrNpOUWUpCSg6l85fjqdtES8V78Q5LRTGRMFtf+jHh4EfzTHSndP5ywoF2qjc9McgRqlhanFBKKaWUUkqpPmir20R6wSwAxky7gITUfPauuSfOUaloe9f8hZbKlUxe8gNScycfsl16wUyyShZTuf5BIqHOQYxQxdLihFJKKaWUUkr1UmdHPYGOWjLs4oTDmUDJvCtprVpNa826OEenAJorVlL+/t0UTD2fMdM/ftj2pfOXE/A2UvvhvwchOnUoWpxQSimllFJKqV7qmm8ivWD2/nWFMy/BnZTFPu09EXcBbwNbX7qR5KzxTDn5+oPmmehOVvGxpBfMYt/a+zGR8CBEqbqjxQmllFJKKaWU6iVP3SbE4SQ1b+r+dU53MsVzP0NT+Zu0N2yLY3SjmzXPxI2HnWcilohQOn85/rYK6ne9PMBRqkPR4oRSSimllFJK9ZKnbhOpOVNwupIOWF80+3KcCak690Qc7V39F1oq32fy0ut7nGeiO7kTTiU5azz71t6nV16JEy1OKKWUUkoppVQvGBPBEzUZZjRXYjpFsy6nYefLeJv3DH5wo1xzxUrKV9nzTEz7WJ/3F3FQOn85HQ3baN73zgBEqA5HixNKKaWUUkop1Qu+lr2EA+3dFicAiud+BocrgX1r7xvcwEa5rnkmUrLLmHLyD3s1z0R3CqacS0JqgT5/caLFCaWUUkoppZTqBU/9ZoBDFicSUnIYO+Ni6rY/i99TPZihjVrGRPbPMzFj2a043clHfCyH003JvCtorVpNW82GfoxS9UbcihMi8qSIGBE5NWrdmSKyTkS8IvKhiFwes0+uiDwqIm0i0iQifxSRxEEPXimllFJKKTXqeOo24nAlk5I94ZBtSo/5HCBUfPDXwQtsFKve9Dgtle8z6aTv9Xmeie4UzrwYV2Im+9be2w/Rqb6IS3FCRD4HpMSsKwOeBn4LZAHfAe4TkcVRzR4E0oDxwGxgEXD7wEeslFJKKaWUGu08tZtIL5iJOJyHbJOYNoYx0y6gess/CXgbBjG60aezvY7d7/6OrJLFjJ1xUb8c0+lOoWjOJ2nc8xodTbv65Ziqdwa9OCEiJcAtwDUxm5YDG4wxfzHGBIwxzwD/Ar5s71cGnA181xjTbIypAn4MXCUiSSillFJKKaXUAImEg7Q3bDvkkI5opfOXYyIhKtY9OAiRjV473rwNEwkd1TwT3Sme80kcriSde2KQDWpxQqxXzD3ALcaYvTGb5wGrYtatAo6J2u41xmyJ2Z4CTI3ZDxHJEpGy6AUoOfp7oZRSo4fmUqWUOnqaS0eGjsbtmEiwV8WJ5MxS8icto3rT4wT9rYMQ3ejTsOsVGne/yvhjv0RyZmm/HtudlEXhzEuo3/Gczh0yiI64OCGWWSKS3ofd/h8gxpi7u9mWAbTErGux1/e0nag20b4F7I5Z3uhDrEoppTSXKqVUf9BcOgJ46jYCh54MM9a4BVcRDnqp2vDoQIY1KoUC7ex48zZSc6dQPPezA3KO4nnWcSvWPTAgx1cH63VxQkT+V0S+YP8uwMvABqBCRE7oxf6TsIZhfPEQTdqAzJh1Wfb6nrYT1SbaHcCEmGXp4eJUSil1AM2lSil19DSXjgCeuk24k3NJTBvbq/apuVPILTuFyg0PEwp0DHB0o8ue9+4k0NHAlFNuxOF0D8g5ktLGUjDlPGq2PEnQ1zwg51AH6kvPicuATfbvZwNzgROAvwI/68X+S4FcYLWINIhI1+wwT4nIH4B1WBNcRlsEfGD/vg5IFZHpMdt9wIexJzPGtBhj9kQvQEUv4lRKKWXTXKqUUkdPc+nI4KmzJ8Psw9wGpQuuJtTZRvXmJwYwstGlrWY9VRv/TtGcT5IxZvaAnqt0/ueJhAJUbnhkQM+jLH0pTozhoyR6DvB3Y8x7WFfXOOaQe33kMWCi3bZrAasnxQ3A/cBcEblKRNwicj7wMeAuADuJPw/8UkSyRaQIuBm41xjj78P9UEoppZRSSqleCwXa8Tbv6fWQji4ZY2aTVbKYynUPEAl1DlB0o0ckHOTD124hMa2AsuO+OuDnS8meQO6EU6na+Jj2fhkEfSlONANdfZhOB1bYvwtw6Gvp2IwxXmNMRfRib6q3r76xG/g48G2sYRp3AFfZBZAuV2D1lCjH6sWxGriuD/dBKaWUUkoppfqkvX4LYPpcnABr7omAt5GarU/3f2CjTMUHf8PbtJPJS6/HlZA6KOcsnb+cUGcbNVueHJTzjWauPrR9DviTiKzFGif3vL1+FrDnSE5ujJGY2y9hDRc5VPsG4PIjOZdSSimllFJKHQlPnTW6/UiKE5lFi8gYM5d9H9zP2BkXDdgcCSOdt6Wc8tV/Im/SmeSWnTxo580YM5us4mOpWPcARbM/qc/fAOpLz4lvYs0qnANcaozpulLGQqwhG0oppZRSSik14nhqN5GUWYo7KXZ+/sMTEUoXXk2np5q67c8NQHQjnzGG7a/9FIczgUknfXfQz19yzOcIdNRTv+OFQT/3aNLr4oQxxmOM+aYx5iJjzAtR6280xtwyMOEppZRSSimlVHy11W06ol4TXXLGLSE1dyr71t6LiYT7MbLRoXbbv2itWs3EE64lMTV/0M+fXXoCKdkTqVz/IMaYQT//aNGXnhOISK6IfFNE/k9Ecu11x4vI+IEJTymllFJKKaXip7OjnkBHLRlHUZwQEcYt/CK+lnL2rPxDP0Y38gW8Tex6+9dkjD2GsTMuiksMIkLx3E/T3rCN1uo1cYlhNOh1cUJEZgNbsYZ3fAXo6tN0AdZVM5RSSimllFJqRPlovomju2xl3sTTGTvzEvatvZfabf/uj9BGhZ1v30446GXqqTci0qfv1vtVwdTzcCdlUbnuwbjFMNL15dm9HXgImAJEX7rzOWBpfwallFJKKaWUUkOBp24T4nCSmjf1qI4jIkxe8n0yixbx4Yqbaa3+oJ8iHLma9r5N/fbnKF1wNSnZE+Iai9OVROGsS2nc8zq+1n1xjWWk6ktx4ljgd+bgQTb7+OgSo0oppZRSSik1YnjqNpGaMwWnK+moj+Vwupl59m0kpo9l83Pfxd9W1Q8RjkzhoI/tr/+c5Kwyxi24Kt7hAFA46zLE4aRyw8PxDmVE6ktxQoDurptSCrT1TzhKKaWUUkopNTQYE8FzlJNhxnInZTL73DuIRIJs/M+3CAU6+u3YI0n5+3fR6ali6ik34nAmxDscABJT88mffDY1W54m1OmJdzgjTl+KEy8DX426bUQkAbgR0GuqKKWUUkoppUYUX+s+woH2fi1OAKRklzHz7NvwNu9h60s36BU8Ynjqt1Cx/kHGzryEzKL58Q7nACXzPksk5KN6y5PxDmXE6Utx4gfApSLyNpAI3AlsB2YDNwxAbEoppZRSSikVNx9Nhtm/xQmA7JLFTF7yPZrK32T3u7/t9+MPVyYSYvuKW0hIzmbi8d+MdzgHScubRmbRQqo2PIqJhOIdzojS6+KEMWYnMA94no96StwPLDDG6IwgSimllFJKqRHFU7cRhyt5wCZjLJp9GUWzP0nFugeo3vLPATnHcBIJB/lwxc20N2xl0pLv4UpMj3dI3SqZ+1k622to2PVKvEMZUVy9bSgiLmNMHfCTbrblGWMa+jUypZRSSimllIojT+0m0gtmIg7ngJ1j0knfwddazo7Xf0ZyZilZRQsH7FxDWdDfyubnv0dr1WrGL/oyeRPPjHdIh5RTtpSkzFIq1j9E/uSz4h3OiNGXYR1/7W6liOQAL/VPOEoppZRSSikVf5FwkPaGbQMypCOaOFzMWHYrSRmlbH7ue6PyMpW+lr188I/ltNWsZ9oZNzP+2C8hIvEO65BEHBTP+TSe2g201WyIdzgjRl+KE8eIyO3RK0QkC3gRqO/XqJRSSimllFIqjjoat2MiwQEvTgC4EtOZfd4dAGx89luj6koQLVVrWPuP5YQ625j78T8yZup58Q6pV8ZO/xiuhHQq1z8Y71BGjL4UJ84FPiUi3wUQkQysuSc8wMcGIDallFJKKaWUigtP3UZgYCbD7E5yZikzz/kl/rZ9bHnx+lEx2WLttmfY8K//hzs5m2MuuY/MwmPiHVKvOd0pjJ15MfW7XsHvqY53OCNCr+ecMMaUi8h5wAoR6QCuAALA+cYY/0AFqJRSSimllFKDzVO3CXdyLolpYwftnFlFC5l88g1sX3EzO9/+FZOXfL/H9kF/Kx1NO+ho3G4vOwgHvSSk5OJOySUxJQ93Si4JKXkfLal5uBLS4zpswpgIe1b+kX1r/kJW8bHMOPs23IkZcYvnSBXN+SQV6x6kasOjTDzxW/EOZ9jrdXECwBizTkQuAf4DrAWWGWM6BiQypZRSSimllIoTT91mazLMQf4nvnDGRXibd1G57kFSsiZQNPsyIuEgvpYIdwZ2AAAgAElEQVQ9tDdux9u0g/ZGqyAR6Kjbv58rKZPUnCkkpOYT9DXhqdlAo7eBSLjzoHOIM4EEu2iRmFpASvZEUnOnkJY7haSM4gGdADQc8vPhqz+hfscLjJ1xEZOXXo/D6R6w8w2kpLSx5E86g+otTzL+2C/hdKfEO6RhrcfihIi8cIhNLVhDQv7R9cdqjNFpSpVSSimllFLDXijQjrd5d9yuxDDx+GvxtZSz481fUr3pcbwte/YP8xCHi5TsiWQVLyI1ZwqpuZNJzZ1CQkreQYUUYwzhQDsBbwMBb2PMT+v3jsbtNOx+FUwEAIcrkdScydZiHzs1ZzLu5Oyjvl8BbyObnrsOT+1GJhx/LSXHXDmkJ77sjeK5n6F+xwvUbH2a4jmfinc4w9rhek5U9nG9UkoppZRSSg1r7fVbADNo803EEoeT6Wf+lA9X3Ewk6CNn/JL9RYLkrPG97mkgIrgS03ElppOSPeGQ7cJBH97m3QcMEWnc8xo1W5/a3yYhJc+KIXcKKdkTSM4cR0rW+F4XLTqadrLx2WsJ+pqYefZt5E08vVf7DXUZY+aQMWYulesfpmjWZQPa62Sk67E4YYy5arACUUoppZRSSqmhwFO3CRi8yTC740pIY+ZZvxiUczndyaQXzCS9YOb+dcYYgr5GayhJ4w7aG7fT0bSDlvUPYyLBj+JMzCQ5yypUJGeNJzlzvPV7ZikOVyIATXvfZsuL1+N0JTPvwj8fcJ6RoHjeZ9jywvU0lr9B3oRT4x3OsNWnOSeUUqqvjC+EafRjfCEcEzMQZ18uEqSUUkopNfg8tZtIyizFnZQZ71DiRkRISMkjJyWPnNIT9q83kRB+TzXelj34WvbiaynH27KH5or3qN32TPQRSEwvJDmjhJaq1aTmTGTWeXeQNIgTjA6WvAmnkZheSOX6h7Q4cRR6M+fEZcaY1h7mnwB0zgmlRiNjDHhDmCa/VYBo9BOJ+t00+cH70WWwJDsR56kluE4qRFKH58RHSqnRIRQx7G71UZqeRJKrd0VVE7QuXibupIEMTSk1CNrqNpFZND/eYQxJ4nCRnFlKcmYpjD9wWyjQga+1q2BRjq+lHF/LHgomn8Xkk3+IKyE1PkEPMHG4KJ79SXa9cwft9VtJy58e75CGpd7MORGJ+l0pNQKZzjDGEwB/GOMLgT+E8Yetn75wzO0Q+MKY9gCm0Q/+8IEHS3QiOYlIbhKOiZlIbiKSmwzGEH6jitCTOwk9uwfn8WNxnVaCY4zOaqyUGhoq2ztZWdPGezVtrK5royMYYUJGErctnUxxmtU1OeJrJdxUQaS5gnDTPsLNFftvRzz14HDhHncM7knHkzDpBJxjpyJycHHDGMM/dtTzty01pLid5Ca5yU12Wz+T3OQmuchNdpOX7CYnyU262znsJ41Tarjo7Kgn0FFLRhyHdAxXroRU0vNnkJ4/I96hDLqxMy6ifNXdVKx/iOln/E+8wxmWej3nRNfvIpIMTLJX7zTG+AYuPKXUQDARg9nrIby5icjmJiK72yBiDr2DAEkuJNlp/UxyIjlJOKZkWUWInCQk11pIdR/yA7Rr0Rgi+zyEXq0g/FYV4dcrcczOxXV6CY5p2frBWynVKyYcpHPjC4QbduPMKcWZOx5n3ngkOatPeaQjGGZ1nYf3qttYWdtGZbt1ub0xSU5Oy4pQRjP3N6TzxX+v5kftTzGj4T2M33PAMRzp+TiyS3BPOh5ndgmms4PAznfxvvw7vC//DknJJmHSYtyTTiBh4mIc6fkEwhFuX72Xf+1uZF5+GtmJLhp8QTY2tNPgDxIIH5yPExxCTpJVrDitNJtLJuWT2MseHUqpvvlovonZcY5EDSeuxHTGTP841ZseZ8Lx3yAxNT/eIQ07vZ5zQkQSgJ8D/w9ItFd3isgfgR8aYw6+gK5SasiINPmJbGkisqWZ8NYm6LAvRzUuHdeyUmRMCpLsgiQnkuQ6oBhBgqPfCgeO0nQSPjcDc+FEQm9UEXqtksBv1iHFqbhOL8V5bAHi1lmOlVIHM6FO/Gufxvf2X4m0VIE49l/6DkCSMnDmjceZOw5nbplVtMgdhzN3HOJKJBwxbGv28l51M+9VNrKxJUgEIYkQc00NF3Rs5pjGdynyVdCV8WYlFnJL6Te5IfVSvpU7k3PHOHFkl1hFkewixJ18UJypy64l0t5AYOd7BHe9S2Dnu3RueA6A1jHz+HneFWwOZ/L5aXlcM28cjqj8aoyhIxihwR+k0Rek0W8tTf4gDb4g+zx+/u+DCh7ZVstVswq5YEIeLocWdpXqT566TYjDSWre1HiHooaZ4jmfomrDo1Rt/DsTFn813uEMO2JMD9+WRjcUuQu4CLgReMtefRLwP8DTxpgvH2b/XwAXAKVAO/Af4PvGmMaoNmcCtwNTgArgRmPMY1Hbc4HfA+cCIeAx4NreFkZEpAzYvXv3bsrKynqzi1LDlukME9neYvWO2NKEqfFaGzITcM7MwTEjB+f0bCQ94ciOH470y+SWJhgm/H4doVf2YSo7IM2N6+RiXKcUIxlHFtsoNij/oWguVYPNBHz4Vz+B7+2/EWlvwFU8m5STv4B78olEWqoJN+4l3FhOuGGP9bNxLxFPHQD1rmzWps5iXdYCPkiajEes+SAm+/ZwTMdm5ns3Mz1YSVJOEc7sEpzZJThyrJ/OnBIcmWPxhODGt3exqtbDZ6eP4StzinH2oSBgTIRw7Q7Wb/mA/64dS7txcW31fSzxbcRdOg9n/kS7qFKGM3ccjoyCboeCdFld6+GuDZVsbOygOC2RL84q5MxxOX2KSfVIc+kot/5fXyXkb2HBZQ/FOxQ1DG167jpaq9ey+MpncbpG9RxEfc6lfSlOtAKfMcb8O2b9+cBDxpgep7IVkZ8Bfwc2AtnAA0CnMeZj9vYyYDPwDeBvwFlYxYfTjDHv2W2eA8LAFUAy8DTwrjHm6728D2Xom4AaQUzEgMea+yFiT0BpGv2YWi+RXa0QMuB24JiShWNGNs4ZOUhR6lH1gjA+P8G/PUNk6y5IcENKEpKchKQkWb+nJEFKMpIcfTsJyUhDxuQe8tzGGCLbWgi9so/IxkZwCo6ZuTjn5uKcnYtkJna7nzqAfqBWI0rE78G/8lF87z6E8bXiLltE8tIv4J5w7CFziS8UZm1dO+9VNbKyuoVyr/U5JwcfC0J7WZTYxsJsF7l5Y/cXICT10LmpSyhi+PWavTy5s4ElRZncdPwEUvrQy+vZ3Y3ctqqc3GQ3P19cQlnLZgI73yW4dw3hhnIIRo2SdSdF9foYH7WMw5GUDlg58+3qNu7eUMn2Fh8TM5O4ZnYxJxdn6hC5o6e5dBQzJsI795xO/uSzmHLKDfEORw1DLVVrWP/UNUw55UcUzrwk3uHE04AWJ+qBJcaYbTHrpwNvGmPy+nRikQuwihoZ9u2bgHONMYuj2jwKdBhjru5K4MBMY8wWe/u5wONArjHG34tzlqFvAiqOIk1+Ih/UYzqC4HKAy4HYP3E7wCUf3XY5wG3dNsHIR4WHA66G0QmhyIEnSXUjeUk4p2ThmJmDY1ImktA/wyQijS0E//wEpr4Z59IF1kqvH+P1Y3z+/b/j9UEofND+MqEY11kn4Zg6vscPz5E6L6HXKq3HqsnqGCVl6Tjn5uGck4cUH12BZQTTD9RqRIh0NON790H87z+G6ezAPWUJKUu/gLt07sFtjWFHi4/3atpYWdPG+oZ2ghFDglM4Jj+dxWMzOG5MBhMzk446bxhjeGJHPXes3cfEjGRuWzqZsak99/AKRQx3rqvg0Q/rWFiQzs0nTiQr8cBRtcYYIp56wo17rF4gDeV2D5Bya/hK9NCVtFwSZ5xJ8klX4swsJGIMr+xr5s8bq9jr6WRGTgpfnlPMsWPSNU8eOc2lo5i3pZxVD1/C1FP/i7EzLox3OGoYMsaw9vEriIQ7WfjJv4/mXDygxYmfAznAV4y9k1iP9J2Axxjzgz6dWOTXwCJjzFL79pNAlTHma1Ftvgd82hizQEQuxCpmpEZtzwfqgHnGmPUxx88CsmJOWwK8oW8CajCZtgDhNXWEV9UR2dl69AdMd1uTT2a4kRSBxDBIEIwPE2xHPB5MZwDXGcfjnNt/YyUjeyoJ3PMkhCO4r7oI5+RxPbY3gSD47GKFz0+koo7QipXQ4kHGF+E660Qc0yf0mLCNMZjKDsLrGwhvaMDssSaik5xEHHPycM7NsybldOukcLZ+f/fTXKoGU7itFt/bf8O/+h8QCpAw8wxSll6Na+y0g9q+X9PGs3saWVnTRnOnNYfOpMxkjhubweKxGczLSxuwCSPfrW7lx+/sItHp4NaTJjE7L63bdq2dIX78jjUc5PIpBXz9mJI+zw9hQgHriiCN5YQbygnVbCWw5RVASJx7PilLluPMHUcoYnhuTyN/2VRNrTfAgoI0vjynmDmHiE31SHPpKFb74bNse/nHLLz8UVJzJ8c7HDVMdb2Oxk6/kMJZl5KWP3M0Fin6tzghIndH3XQAlwGNwEp73bFALvC4MeaLvT6pyOXAX4BTjDFr7HUvYw3R+FFUu2uAHxhjJovIlcCtxpjiqO1uIAAsNca8GXOOm4D/7u78+iagBprpCBL+oN4qSGxrBgNSmIpzUQHORQVIfrI15CIU2b+Y6NvBCCYUwQTCmPIaIrUNEOrA+FsRTzum1XNwzwSHQGY6kpkOXh+mrgnHghm4Lz4TST14wra+CK/dQvDhZ5GsdNxf/ASOgpwje1xCIcIrNxJ6+V1obkPGFVpFihkTe5WwTWsn4Q2NhDc0EtnSBMEIJDpxzMzBOSfX6lWR5j6i2EaIgfhAfROaS9UAM6EAHS/egX/VE2AMiXPPJXnJclx5Ew5qu7vVx+/WVfBOdRtZiS6OG5PBcWMzOHZsOvnJgzdPze5WH997YwcNviA3HFfGWeMPzIs7W3z84M0d1PuCfH/ROM6f0KcOpj0Kt1Tje/uv+Nf8EyIhEmctI3np1bgKJhMIR3hqZwP3ba6muTPEiYWZfGVuEZOz9LLNfaC5dBTb8eZt1Gx5mpO+8Bri0Am61ZGJhINsf/3n1G9/jki4k5TsCYyZdgEFU84jMa0g3uENln4vTrzay+MYY8zpvTqhyKeAPwCXGGNejVr/JFAZPX9ENz0nHjTGpEVt154Tasgw/hDhdQ1WQWJLE4QNkp9sFSQWFtCc6+LVympeq6zGFwqRnpBARoKbjIQEMtxuMhLc+9elt3aQunUXqeu2k97WjsvhsIoOWVbxQaJ/2gtpKYjD+pbQhMOEX3qX0IvvQGoy7svPxjmr79V/YwzhF98h9NybtE8qoerjp7InFGR3mwcR4fTiQmbl9P0SoCYUJrxqI+GX3sU0tSIlY6wixazJvT6WCYSJbGu2e1U0QmsA3A6cx43BdVoJjuJR+W2hftunhp2Ir5W2R64jtHctSQsvJXnJcpxZRQe1a/YH+cumap7aWU+Sy8HymYV8YkoBif0wMe+RaukMccNbO/mgvp3lM8fyxdlFOER4dV8zt6zcQ6rLyc+XTGJWburhD3YEIu0N+N55EP+qxzEBLwnTTrHm5CiehS8U5u/b63lwSw3eUJjPTB/L1TML9fKjvaO5dBRb+8TncbgSmXfh3YdvrNRhhDo91O98kdptz9BWsw7EQXbJcRRMPZ+8Cafh7OaKTyPIwA3r6A8i8gXgl8DHjDFvxWy7CTjHGHN81Lru5pyYYYzZam8/F3gCyNE5J1Q8GGOIrGsgtLLWmsQxGEGyE3EuLMC5aAyN+U5erarhlYoqPmhoxADj09MoSE6iLRCkLRDEEwzQHgz1eJ50t5uxKckUpqZQmGIvqcmMTUmhMDWFDLe723/qIxW1BB9+FlNdj+PY2bgvOt2aqLIHrYEAu9s87G5pZefqjez2tLMnM5WGqMMnOp1EjCEYiVCYksKy0iKWlZYwJTOjT4UKEw4TXr2Z8IvvYBpbkOICXMtOxDF7CtKXmfAjBrPXQ+itasLv1UAwgmNGNq7TS3HMzOnTsYY5HSethpVw0z7aHrqWcEsV6Rf9hMTZZx/UJhCO8Pj2Ou7bXIMvFObCSfl8YVYh2UlDo5dUMBzhl6v38szuRk4tyWJ8RhL3b65hVm4qPztp4qD05oj4WvG99wj+9x7B+NtwT1xMytIv4Bq/AE8gzO/WVfDM7kbGpSfyg0XjmV+QPuAxDXOaS0epSDjIW39eSvHcTzPxhGvjHY4aYXyt+6jd9gy1H/6bTk81TncqeZPOZMy0C8gsnD8Sh30M3eKEiHwT+C+sAsSqbrZPADYBX8O6ksdZWFf3iL1aRxD4HB9dreO96HkqDhNDGfomoPqJiRiCD20j/FY1pDpxzs/HubiQhrEJvFJdzSsVVaxvbAJgYkY6Z5QUcXpxERMyPpqkzARDRDbtoHPVJtp27KHd4cBTXEDH9DLaxxXiEWgLBGns9FPT4aPa66W6w4svfOCQjhSXi8Ko4kVBcjIiEI4YwuEwwZ17Ce2uJJyYANMnEMnOIIKxthtDyBiqO7zsbvPQ1PnRlXmTwxHKEhKYUFLIxIx0JqSnMyEjncLUFLyhEK9XVfPCvkpW1tYTNobx6WksKynmzNJiJmT0/sOvCUeIrNlM6KV3MPXNSGG+1ZNiztQ+FxZMe4DQG1WEXquE1gAyJgXXaSU4jx+LJI747pn6gVoNG8F962l75NtgDBmfuh33uPkHbDfG8GpFC79fV0FVR4ATCjP4+rwSJmQOvW+ZjDE8vK2OO9dVYIALJuTy3YXjSBjkXh2Rzg78qx7H984DmI4mXKXzSFl6Ne7JJ7Gq1sMvVpVT1RHg4kl5fHVeCal9uNrIKKO5dJTy1G1m7RNXMuOsX5A/6cx4h6NGKGMitFavpXbbMzTsfIlw0EtSejEF084nu2QxCal5JCTnjoReFUO6OGGAENAZs2mmMWav3eZM4FfAFKACuNEY82jUMfKA3wPnYF1S9DHg2t70mrD3L0PfBFQ/MOEIgXs2EVnTAK4qalNreS03nRX5GWxOs3omTDJwWkIyp2VlMSEvZ/9QDFKTMeXV1rCGtVvA1wkZaTgXzcK5aBaOsT2PSzbG0BYIUuX1UmMXK6q9PvundbsjdHBPDCfgMAZnxOBwOHAluHGI4HQIDhEKkpOZmJFOmcNB6etrGd/QSvEly3AvmHnYx6O1M8CrlVW8uK+S1fUNGGByZgbLSotZVlJMcVrvujSbcITIB1sIvfgOpq4JGVeI+xNn4SgZ06v9DzhWKEJ4TR2hlyswez2Q4sK1pAjXqcVI9uBcczrS5IewwZE/aG8u+oFaDQudm1/C8+R/4UjPJ/Ozv8WZO/6A7ZsbO/jtB/tY39DBxMwkvnFMKYvHZsQp2t5bVdtGkz/EsnF9H+7Wn0zQj3/tU/jeup9IWy2uolmkLPsm4ZL5/GlDFY9tryM3yc33Fo5jSXHsSAOF5tJRq2rjY+x44xccd8UzJKUXxjscNQqEgz4adr9K7bZnaKlYCXz0v7kzIZWE5DyrWJGSR0JK7kE/E9OLcCUMzNDBfjB0ixNDgb4JqP5ggmECv1tL5EMPH2bVc8dxqWwOW8WAqTg4NRDhlOZ2ShrboK0dIjF/Yw4HRCLgduGYMxXnsbNwTBm/f76I/uALhRCwiw8OHICIYIIhQs+/RfjVlZCZhvtT5+KcWrZ/v/D2coL3/ROcThKuvhhHWfGhTnFIDT4/r9iFiq6eI7OyszitxOo1UpSSwtjUFFJcrkMew0QiRFZvJvivFdDhw3nyQlxnn4QkJfY5HmMMkZ2thF6pIPJBPYjgXJCP64xSHGX9/89OpN5HeG0d4TX1mHL76iIlafsnQ3XkDmihQj9QqyHNGIPv7b/hfek3uErnkfHJ23GkZu/fXtMR4I8bKnmhvInsRBdfmlPEBRPycI6eoVn9yoSDdK77N97X7ibSVot76lJSz/wmHzrG8LP397Cr1c8Zpdl8e0EpOUNkmMwQobl0lNr2yk007X2b4z///EjsYq+GuM72OjqadhDwNthLo/Wzo4GAr5FARwORkO+AfZzuFKaf+VNyy06OU9Q90uJET/RNQB0t4w/h/eW7OKqC/GlyBw+ODzMxI53zxpdyWnERJTE9BEw4Ap4OTKsH0+Kxfra2IwU5OOdNO6J/tvtDZE8VwUeexdQ14TzxGFwfO5Xwum2EHnseyc/G/cVLceQe/bdp1R1eXqqo5MV9lWxrOfAyqpkJCfvnzShKSTlwTo3UFNLcbozXT+jfrxF+Z51VTLn4TBxzphzxB4ZIg4/wikpCb1WBP4yMT8c5LRvH+HRkfAaSk3hEx47UeQmvqSe8pg6zrx3AOvaCfMTpILS6DrO7zVo/IQPXQmuSVMnq9+dfP1CrIctEQnQ8exv+1U+QMGsZ6Rf9BHFZfwMdwTAPbK3h4W21YOBT08Zw5YyxOuygn5igH997D+N7815MwEfi/AtJOPlLPFQR5r7N1SS7HFw7v5RzxufoP2QWzaWj1KpHPkFSRgmzz7sj3qEo1a1w0Eugo4FOu4BR8cFfaW/YxuQl36No9uXxDi+WFid6om8C6mhU17Xg/9Uq8lsd3DrTT/OsNK6YOY3jxxQMyw9zJhAk9J83CL++ClJToN2LY2oZ7s9fiCT3f9Gk0e+nyh56Ej1/RrXXGpbSGTOPRrrbzcL8PM4eV8IJgTCOJ16yJvacORHXJctw5GQecSzGHyL8dg2hlTWYinYI23kwzY1jfDqO8Rk4ytJxjEtHMrt/LCI1HVZBYm29dQyswoNzQT7O+fkH9ZCINPgIr64jvKrOai/gmJxl9aiYn4+k98ukefqBWg1Jkc4OPI//kOCOt0g+6fOknPF1RByEIoandtbzl03VtHRawyG+MreYwtT4FG5Huoi3Ge9rf8a/6u/gTCD5xCupnX05t35Qy8bGDhaPzeD7i8bp46+5dFRq3P0am577DpOWfI/iOZ+KdzhK9Uo46GPLizfQVP46xXM/y8QTrh1Kl8DV4kRP9E1AHYmtzS08uWYr5z/XTlmHg6dnd7Lo8sVMz8s5/M7DQGRXBcF/vIRjYgmuC09DnIOf0IwxNHcGrMKF10tVh5d97R28UVVDU2cnaW4XpxUVsay5gzmvvI/DGFxnnYTz1EVHHa8JRjCV7UTKPUTK24iUezDVHfuH/El2IjLeKlQ4StKIlHusgkRVBwCOiRk4FxTgmJ+PI6d3c1lEaryEV9dahYoaLzgEx/Rsq1AxLw9JOeLu1fqBWg054bY664ocdTtJO/96khZegjGG1ytb+MP6SvZ6Opmfn8bX5pUwc4AuuakOFG7aR8fLvyOw+SUkNZfEU77MsxknctfGGgC+PKeYSyfnj+bhNJpLR5lQoJ1Vj1yGOzGD+Z94AIdThzmp4cNEwux8+1dUbXiE3AmnMf2Mm4fKZJpanOiJvgmo3jLG8E5NHQ9+uIPyfY3cvjaFQp/gPyODgkuPjXd4o0YoEmFVXQPP76tgRWUV3lCYgsREzmjzs2xLOZMz0nF/YhmOiaX9el7jDxHZ147Z6yGyxy5Y1Ntj/AQckzJxLrB7PBzF0AxjDKayg/Aqu1DR6AeXkHj9IhzFaUdySP1ArYaUUM2HtD10Laazg/TLbiVh8olsaGjnznUVrG/ooCwjia/NK+bEwsxh2QNtuAtWbKDjhV8T2rcOZ14ZbSdfy2+aCnm3po0pWcl8e0Epx+SPysuOai4dZba/fivVmx7nmEvuI2PM7HiHo9QRqVz/EDvf+hXpBTOZde6vSUjJjXdIWpzoib4JqMNpDwZ5tbKKBz/cye42D7P8Ln7xnpvUsJOEKyfiOmFCvEMctfyhEK9X1/D83greqakjbAwT/EGW1bZwVnERJReciqSlHLSfCYWteT/a2jFdP9s6oK0DMLjOWYJkHL4QYDqCRCrbcYxJOeRQj6NhjMGUewiva8D1sQl9voSqTT9QqyEjsP0tPI9fjySlk/GZ31CTUsof1lfyakULuUkuvji7iPMn5OEavd/ODwnGGALbVuB96f8IN5bjHL+A9+d8id9XuKjzR1hWlMpXZxdQkJ4KTjcig3t51DjRXDqKtFZ/wLp/foHiuZ9h0knXxTscpY5Kw+4VbH3pBtzJucw5/7ekZMf1fxctTvRE3wRUtEa/n23NrXzY0sq2FutnRYfVVX9KRjpX7/Vy/Bo34nCR8I15OKf1fIlPNXhaOjt5uaKK/+zZy4bmFgDmtfs5Iz2TE/xBxrZ59xci8B7iSsNpKeAPQHoKCdd84rCXcB0m9AO1irtwWx2+1/+Mf80/cY6ZTOTS27l/b5And9ST4HTwmWlj+PS0MaToZJdDigkH8a/5J97X7sZ0NOGXBB7PPYcnc87GSZhPNvybjze9hNshiCvBKlS4EsCZgLiTSF78KRIXXDxSesBoLh0lIuEAa/7+GcIhP4s++RhO98Ffcig13HjqNrHx2W9jwgFmnvNLsorj1utbixM90TeB0ckYQ7XXy7aWVrb9f/buOz6Ou078/+u9XatebBXLvcg9juN00jsESEJJgAQSchx8+V2BA658Dw6OcpXjgPtxBFIIJZCQAimQnpjYcRLbcey4ylW2JVm9S9vn8/1jRvZ6LcuyLGkl7fv5eMxjtbMzs5+ZXb3ns+/5fD7T3p+I6KAlHDm6zLTsIAsK8qkqyGeZ18eSh9dB3RTwe/F9eRXuyoxs1joh1PX08tz2ap47cJBDHvuK3qxYggssFxf5/SzPycWbn4vkZdtTbg7kBhG3G+twA9H7Hod4HN9dN+OaNyPNe3PGtEKt0sbqaye09kFCGx4FK4Gc/SGemXkbv9rTSjhu8f45Jdy9pILiLO3LPZ5ZkV5i+9/CxMIQj1IXtvjfliLeCOVS6Q7z+ewDrHI1QSKGiUchESPRepB43Tb8Kz5Aznv/DvEObfydcUxjaYao2fATDm38KUvf+0OKZl6c7uIoNWLCXfVs++NfE+o8xILLv0Zp1Y3pKFWkHSQAACAASURBVIYmJwajJ4HM0B6JsL21nW1t7Wxra2NXeyfdsRgAbhFm5eY4iYgCqgrzWVCQb9+2MhQh8fZ2Yk+9DT2zIceH/8urcE3VLPpEYIzhYHcPbzQ0sa6hkXdaWolZFkGPh/OmTuGi8lIuLJvK1KyUu2i0dRL76aOY1k68H38v7rMXpWkPRoRWqNWYs8LdhN54iNa3Hme/ewoHZ1/Hwamr2NiRoCUU4z0V+Xz+rGnMyhsXg3OpYXrjSCff33SYwz0R3lORz1+fPZ1pOXYXN2Ml6PvTvYReuxd3+ULyPvqfuAsq0lziM6KxNAP0tu1n06Mfo2Tu1Sy6+jvpLo5SIy4e6WbH81+ho24DM1d9lhmrPjPWrds0OTGY4Z4ETDgCft9kaao4qcQtiz2dXWxrbbOTEa3tR7tmuEWYl5/H4qLCo60i5ubn4RcX9MUxPVFMdxTrQBPWtoNYh1og7gJrClKche+LK4d89wU1/vTF42xsamZdQxPrjjTSGLIHtJyfn8dFZaVcWFbKsuJCPC4Xpi9M9IEnMPtr8dx4Ge4rzpuo/+9aoVZjojUUo7qlne3bNlJ9pJH93nIafFOOvl4S8LKwKMjHqko5e6q2PJssogmLR3Y38eCOIyQsw8cXlvLJReUEnFZr0d2v0f27fwJxkXvLt/HNuyjNJR42jaWTnDEWW353N32dB1l12+P4sgrTXSSlRoWViLHnT9+msfoZpi54Hwsu/9pY3o1GkxODGe5JIHr/E5jeEN4bLx3xuwKo09MaDvNuaxtbW9vZ1trGrvYOIpYFQEnAz9LiIpYWFbI0v5CFHYKnuhPTHMJ0RzE9MUx3FHrjYJ3ke+934ZqZh+/uJUiebwz3TI0mYwz7u7pZ19DIuiONbGltI2EMQY+H+fl5zCvIY15ODjPf2sasLXvIu+AsPDdfhbhOf+A3YwxtkQi1Pb3U9fYSTVgUBwIUB/xHHz3D2O4QaYVajYq9HX28dKidPR197G7vozUcP/pauemiakohC8tLWVAYZEFhkKKAdt2YzJr7ovxoSx0vHGqjNOjlL1dM54rKAkSERNthun77FRKNewle/lmyLr17Ig6iqbF0kqvf9lv2rvl3qq78JqVV70t3cZQaVcYYDr19Hwc33EN+xTlUXfnPBHLLx+KtNTkxmOGcBIwxJN58l/jzr0NXD67Fc/C89zJcFVNOvbIaMTHL4t7tu/hl9R4swOty2eND9CcjiguZGnNj7WjD2t5GYkcbhOLgEqQkgOR4IdcHJoZpb8E0NYIVQabm4l4xD/eq+UhxDuKdcBUoNQw9sRjrG5vZ2NzM3o4u9nZ20RtP+rEVjjLX7WX+kvnMLypgXn4elTk5uJ3WFHHLorEvRG1vL3U9vdT29jmP9vNQIjHo+xf4fJRkBSjy+ynJClDs91OcFaDESV4sLiok4B7WYIFaoVYjqj0c495t9Ty1vwUBZnpjzOrczpyuXczPD7D0kpspnLMy3cVUabK5uZv/3nSYPR0hqgrtljJXTi/EnQjT88y/EHn3j3gXXELuzd/CFZhQLWg0lk5i4Z4G3n74o+SWLmXZjT+aqC0llTptjbv/yO5XvwlYTJl3PdPP/hTZRXNH8y01OTGYMzkJmGiMxJpNxF95E8IRXOcswXP9e3AV5Y9CSVWyA13dfH3921R3dHLjrBncPHsmCwry8YoLU9NFYnsriW1tmEPd9gp5PtxLi3EvKcK1qAisGIm3d5B4cwumoQX8PtznLMZ9wXJclWXp3Tk1LhhjaOgLsa/TTlTs3lfD3rYOarN8JJxKi9/lYmZeLn3xOEd6+0gkxU6fy0VFdpDKnGymZWcz3XmszMnG73bTGg7TEg7TGo44f9uPraFjf8eTtvfENVcyLX9YFXmtUKsREUtYPL63mQe2HyEUT3BTfhcf2XcfweZdeMoXEbzy83jnXqiVekXcMjxb08pDuxo41B2hNOjj1gVTuXF2Me7NT9D7/Hdx5ZeTd+t38ZTOT3dxh0pj6SRljGH7s39DR916zrn1t2TlTUt3kZQaU+HuI9RteYgjO3+HFQ9TNPNSpq+8k/yys0bj7TQ5MZiROAmY3hDxV94isWYTGIP7ohV4rrkQydFBE0eaMYbH9h3gf97dTsDj4f+ecxaX5U8hsaMNa3srie1t0BsDAdecfFxLinAvLYayIDQ2Yx2ow9p3GGvHfojHkRnluC84C/fZCxG/dtlQg0ts20PPr57hUEk+NddeyH6T4EBXN9lez9HEQ38yYkpWANdp/kgzsTjWgVqs6hoSuw7Q2dxKq89DW26Qcz95M/7yYbXO0gq1OmPr6jv5wTuHONwT5VzquavmfirDh3FPmUvwis/hW3iFJiXUCSxjWFffya+rG9nc3EOO180H55Zwc3YLgaf+HivURc77v0pg+XvTXdSh0Fg6STXve5GdL/w9cy78ApUr7kh3cZRKm1i4g/qtv6Vu28PEw53kla1g+so7KZrxnpE8x2tyYjAjeRIwHd3En19LYv028HnxXH4u7svP1R+9I6QlFObbG9/hjcYmLiydyleXLyd/dSPxFw7Z40XkeO2WEUuKcc3NwbS2YPbX2gmJg3UQse/OQUEu7iXz7FYS00rTu1NqwrEO1tu3GgV8n74F1+zhX2ExxmAaW7GqD2BV12DtOwyxOLhduGZNw7VwNq6qWUhFKeIa9klhXFeoW0IxOiNx5hboXRvGo5rOPn7wxk7e6oRpsSbubniYc6nHv/Q6/MtuwFOxWJMSakh2tPbym+pGXq1tR4BrKrJ5/76fMb3mJQLn3kr2dV9EBhmQzcSjWN3NWF1NWF2NJLqaMJEe3IWVuEtm4i6egSs4qgMYjutYqoYnFu5k48Mfxp9Tytm3PIi4POkuklJpl4iFaNj5e2q3/JJITyPBorlMP/tOpsy9ZiQGztTkxGCGexL4xzc3UNfbx+y8XGbn5jI7L5c5ebmUZwehqY34H1/D2roHcoJ4rrkI94VnIZ5h9RdXwKt19fzr21sIJxL81fIl3BTNJ/6b3ZjmEO7zy3CfW4iJdWBq6rAO1GHqGu2EhYCUTcE1pxLX7Gm4ZlcihXnp3h01wVnN7cTufRTT0YP39htxL19wwjImYUE8DvEEJBKYeOLoczshUUOi+gB09gAgU4twLZhlJyTmTh/JpOa4rlD//6++wa+bfCzLhQ8tmcXllYX43DrOS7q11+3h/o27eDJUSsCKcFv789xc7iJn+fV455ynFXg1bPU9EX67u4mnD7QQiluc42njA/t/zqoiL9mX/zlWbztWVyNWZyNWdxOJrkasriZMb9sAWxPgWJ1VsvJxF9uJCnfxTNwls+y/i6YjHv+ZFn1cx1I1PNWvfpPG6mdY+eFfklNSle7iKDWuWIkYzXtf4PA7P6evfR/+nDIqV9xB2cIP4vYO+6KSJicGM9yTwEObdvBWdzv7e3poDoWPzve73czKzWF2Xi4zE4YZ2/cza38dFdnZ+K+7GNdZVYhXK3VD1ROL8b3NW/nDwcMsLMznm4uXU/5CI4k3G6DAg2tuFJr3Y5rb7RU8HmRmOa7ZTjJiVgWSpbf+VCPP9PTZd+05VA8FeXYSIikBwaniaJbfTkZUzcK9YBYyemPVjOsKdeOGp3hq4yaezTmfBt9UCtwJbpxbys0LyijPPuMfE+o0JLqa6Hv3OZ7eXccv/BfS487merOHzywsZuqSSxGftm5RI6crGuf3+1p4dHcjreE4syJ1XNr5FmWxZqbGWpnqilKUE8SdV4orbyruvKm48kqTpimIN4DVXk+i9aA9tRwk0WY/Wj0tSe8muAoqcBfPIOv8j+Gbf/FwijyuY6k6fe2169n69P9h+tmfYvYFf5Xu4ig1bhlj0XZwLYff+TldDZvxBPKZfvadTF/xyeFsTpMTgxnuSSDyw82Y1jCeK6cTWllMTbSPA13dx6bubhr6QkeX9xnDvJ4wH2np5srp0/CeswTX3Bln0lR70tvS0so3NmyiobePT1XN587WbMzvD0DUAn8TcBjxunHNn2FPsyuRaaXaQkWNGRONEX9hHaarx/7eeTzgcYPHjbiPf47HfXQZKchFppcN67akwzDuK9QmFiK05VnWbX6LP7CADTnLMSJcMCXAhxZO5/yyPNwaK0dNovUgvWt+xvp9+3mg5BZqAtM5KxDiC+fNpap8TG4rpjJYNGHx4qE2frOjjv098eNe87uFsqCfsmwf5dk+yrL9lAXtv8uz/RQFPCcd28eK9GK1HiLeWkOi9ZCTvKgheOmf4V905XCKOu5jqRq6RDzM24/cCsA5tz6C26MXspQais4j73D4nZ8TLJjJnIu+OJxNaHJiMMM9CcQ3NBJ/+TDmYDdkefBcUoH7smm4io4Ft95YjJruHg50dbO/s4u1h2o5GIkwMxTljsMtXBkz+FYuxr1yMVIxRfvtOmKWxX07dvGLXXsoC/j5ZjSbeet6odcP0gOFjXiWV+JaMhfXglmI74z7Pik1mU2YCrUxhvjBTRx862meaXHzQsHFdHjyKfMZbq6axo1zSigM6P/7SIk37KZnzQOsOdTC4yXXszswm/KAi79YOYvLKwv0nKTGXG8sQUNvlCO9ERr6ohzp/7s3SkNflI7I8ckLj0so8Hko8HsoCDiPfg+Ffq/9eHSel0K/h1yf+7QHKk4yYWKpOrUDb/4Ph995kGXv/zGFleeluzhKTTjGWIgM6yKbJicGc0ZX+4zB2t9F4pXDJN5pBhHcZ0/Bc1UlrtknNtFOGMOrtfXcv2MX+7t7mJ4w3HGgkauaOvGWldi3sly5OGPHRDDG8G5LK99bv4ldoRA3tof4q20xfNEK++4bSz143jsf14xybXGi1NBNyAp1orOB7g1PsLp6D38Mnsu2YBVeDJdX5nPLgnKWlWSfyY+MjBar3Urnmgd5sTHGE8XXU+crZVrQwycWVXDD7GL8OuaHGqf6Ygkak5IWTaEYHeEY7ZE4HZG48xijN2YNuL5b4EvnzOCmuXrno0zW01LNpsfuoLTqfVRd8fV0F0epTKPJicGM1EnAag2TWF1L/PUjEIojs/PwXDUd94oSJKWiZxnD6roj3L+zmr2dXVS6PdzR0sPVOw/iAWROpZ2oOGshEpz8zcz64nGe23eAx3fsZm8iTn4szj/v6mZF1zQIe3AtKcB3+2KkQPufKzUME7pCbeIRItteYPfGF3kmVskrBRfR58qiwGNYWZrHqvJCVpXmMS3bp1f6B2GMIVazkdY1v+SZziBPFl1LmyefBfl+7lhcweWVhdp1Rk0a0YRF59FkRX/iIkZHJM4lFQUsLs4ezmYndCxVNisRZfPvPk2kp5FVtz2GNzBq4z0ppQamyYnBjPRJwITjJN5sIP5KLaY5hBT6cV9eieficiT7+ObIljGsqW/g/p3VVHd0Mi0Q4JPi4ZqtB3A3tYHbhZSWIKXFuMqK7b/LipHiwhMSHhPR/s4uHttRzbN19fQBizvD3Nrn4RKm4doZgnw/vtvm4z5rWFc4lFK2SVGhNsYQr91K+1uPsrq2gy3BKrYEF9HmLQCg1JtgVWkeq6ZNYVVpHsVZ2v0DnKTEnrXUr/0Nvw+V8YeiK+l1ZXHOlCB3LJ7GuaW5mtRRamgmRSzNVJGeRuq3P07DjieIhdtZdM2/MmXetekullKZSJMTgxm1q32WwdrWSvyVw1jVHeB34141Fdf8AlwzcpHS4NGuCcYY1h5p5L6du9jV3kl5MMinSku5rr4NT0MLprEV09ZJXKDb46bb56G7pJCe4nx6CnLozgnSHfTT5XGT6/dTVZDPgoJ8yoJZ46rSaYwh1h3l7e2H2LrtELH2KJUhF4u6DOUxL56Yk3ARcF82De8H5iBZemcTpc7QpKtQW+Fu4rVbiR7cTE1dDW93CVsC89garKLXbV8RnemLsmpqLufOnMbZU3PJ9Q0cSyxjsAwkLEPC2JNlwOsSgt7xM7huSyhGXU+EoMdFttd9dPKktHYwVhzT14HV2068aS/733yKxxPzeLngYmLi4bJp+dy+qGK4V46VymTjOpZaiRjxSCfeQCHiGj+xK52MMXQd2Uzdtodp2f8qGIviWZdSsew2HWdCqfTR5MRgxqJCbdX2EH/lMIlNzRBJ2DMDblwzcnHNzEVm5uGamQtFft5obOb+HbvY3t7BlKwAhX4/XdEoXdEoffHEoO8TjCcIu11YTkIiT4QFWUEWFOZTVTqFqpJiZuTm4B7lhIXpiWE19WEa7clqDhFt7MVqDuGLHv/dsgLgLs/BVZaDTMlCSrLs41IaHNUyKpVBxnWFeiSYRIx4QzWRg5upPnyQtzsstnhmsj04n6jLh8tY5LjiJIyLBIIFzqNgBjk8RV6YkRdgRn4OM3IDzMzzMz03QEW2/4SkwEiLJCy2NPewvqGLtxq62NcZGnA5H3GCJkowESYr0Ucw3kuWFSJohQm5AmzIWY7bJVw/q5hPLCpnRu7k7yqo1CgZ17G0u3kn7zx2O4gLX1YhvmAJ3mAJvqNTsf2YfezvyXqHikQ8TNOe56jf+gi9rbvx+HIpW3QT5Us/QlbetHQXT6lMp8mJwYxlhdpYBtPQh3WwC6umG+tQF6a2B+LO8c72OsmKXPbmWzwabSbsE7L9XnJ8XnL8PvL9PvJ8PnK9XvJ8XnJFyO3sJbu1A1djG6GWdvZ2dbE7FmW338Pe7AD7gz5izi0LA5ZhnrhY4A+wID+PuSXFFBcXUFBUQNDrGXJLCxOzMM0hTFMfVmNSIqKxD3qPjaZtuaAtG/b54hwJJPASYoHEqDp7Dt5Ll+LKmZwnRqXGkXFdoR4NxhistsP01mxm26FDbGqP0Zlw4zZxxCRwW3FcxsJtnEcs5zGByxjcJAiLnzpfKfW+Uur8ZXS5c45u341hWtDN9PxsZuYFmZEbYHqufbvDkoAX7zC63Rlj2N8ZZn1jF+uPdPBOcw9RC7wkWBSp4ezOzcyK1BIRHyF3gD5XkFCgkJAvn5A3lz5PNiF3kD5XgD7x0Wc8xMXNNbOncmtVKVOyfCN5iJXKROM6lkb7WmjZ/wrRvhaifa32Y28L0VAr0b42MCde4HL7sskunEte+Qryy1aQV7Ycb1bhSO3KmAt3H6F+26M07Pw98Ugn2UXzqFh2K1Pn34Dbm5Xu4imlbJM/OSH2fUy+DdwNZANrgc8aYw4OYd1ZpLFCbeIWpq4X65CTsDjYhTnSB9ZJPgPBHm5a5PhHlz1J0IMUBZBiP5LjBm+ChBXiUKSTnaEudkfD7DGGPQEPfZ7jm/35LEOBMRSIi1LjZkbCR7nxM9XyURT3khd1EexJ4GmN4O+IIUlF7PQbaoMWB7ISHApaHM62OBy0OBKwyEvEubGhkw/m5FLxnnNwVc3Wu20oNXbGdYU6nYwxYCywEmAlMCbh/G1hwl0kWg+RaD1IovUQHa1HONQV4nA8cCxp4Suj3l9KTI51GREMhR7DFL+LqUEfU3OC9hT0HZ1Ksrz43S46InHWN3Ty1qFGNjT10BK3Y3JlpIGze7dxdu8Olvt6yJ1WhadyGZ7SBUhOEa5gIZKVN9xbeCmlhmfCxlJjJYiFO44lLfqn3hZ6WnbR3bQdY9kXlrIKZpFfvoK8shXkl68gkFc5rroIpzJWnI76TdRve4TWmtcAKJl9BRXLbiW/fOW4LrtSGSojkhN/D3wWuB6oA74HXACsMMYMfD+pY+vOYpxVqE00gXW4B1Pbg4kkwBhIGDthcdxkt8Y4+jxhML0xTGsY0xqG0PH3A8frQooDSFEACrx0uWO0xPpIdESQ7gTePotAGHKjLgKJEyu9bT6LZr+hLsviULbF4WCCDl+MPneMbBOjKBqnOBanKJqg2BiKXW6KPR4qK0rxX7oKV1nJGB1BpVSSCVuhHo+sSC9W6yHirTUkWg8RazlIQ3sbtb1xmgnS6imgxVtIq6eQFk8hLd7Co+NgJMuTKN2WFyNCTqKXs3p3cnZ4N6vyDNOmzcZTuQxv5VJcORo3lRonJm0sTcTD9DTtpLNhM10Nm+k6soV4tBsAb1bxccmKYOFswBnfxlgYJ7FrJ3ct+++j8yx7uUQMKxHFSkTtv60oljPPOPPtKWY/j0dIxEMk4mGsmPMYDx//3Hk0VgwATyCf8kW3UL7kQwRyy8fkuCmlhiUjkhM1wL8bY37sPC8AGoBrjTGvJS1XABSkrF4JrJmMFWoTih9NVJjWMKYtjNUaxrSGMG0R6LUDOgLk+ZBCP1IQcB59SNAF7jgRE6Y90kN7bw9dvX3kejwUZQUozg7iyw5CMIBkBezHYACyAohHB2NSapwY8Qp1psXSoTKxMFZfO6a3A6uvHau3HdPXTm9PJ029YZrDcZoj0Bx302L5KHLFOK9QWFQ5ncD0ZbhL5yEuHQRYqXEqY2KpMRZ97QfoPHIsWRHurhuT9xaXB5fHj9uThcsTwO11HlOfe4/NC+RNY8qcq3B59JbzSk0Apx1LJ1TNSETygZnAxv55xpgOEdkHrABeS1r8C8DXx7aE6SNZHqQyBypzBnzdhON264o836C3JvVg95WpHJ1iKqUmnoyKpUMl3gDu/HLIP/6qXRag7R+UUgMYl7FUxEV20Vyyi+ZSseRDAER6muhq2EyoqxYRD+JyIeK27wwibkRciMt9dJ793APiwuX24XJ7EbfP/tvlxeX2IW6v89qxv7W7mlIq1YRKTgB5zmNHyvyOpNf6fR94MGVeJbBm5Is1/knAA4GJ9nErpcYBjaVKKXXmJkws9edMZcq8a9NdDKVUBppov1a7nMf8lPkFSa8BdosKUpIYOlCOUkqdHo2lSil15jSWKqXUqU2o9lTGmE7gILCqf57Th28esDld5VJKKaWUUkoppdTwTbSWEwD3AF8RkVeAeuA/gGrsW4qeihugtrZ29EqnlFJpMnv27FlArTEmPviSZ0xjqVJq0tJYqpRSZ244sXQi3q3DBXwHuBt77Ma1wGeNMTVDWPc9jMO+fUopNYJmDyUengmNpUqpDKCxVCmlztxpxdIJl5w4EyLiB84FjgCJ01i1f8CiS4BMSm9n4n5n4j5DZu73ZN3nUb/ap7H0tGXifmfiPoPu92Ta7/EcS2FyHvNTycR9hszc70zcZ5ic+31asXQidusYNmNMhKF1/zhO0oBFtaOdRR9PMnG/M3GfITP3OxP3eaRoLD09mbjfmbjPoPtNhu33mRpuLIXMPOaZuM+QmfudifsMmbvfySbUgJhKKaWUUkoppZSafDQ5oZRSSimllFJKqbTS5IRSSimllFJKKaXSSpMTQ9MB/LPzmEkycb8zcZ8hM/c7E/c53TL1mGfifmfiPoPud6btdzpl4jHPxH2GzNzvTNxnyNz9Piqj7tahlFJKKaWUUkqp8UdbTiillFJKKaWUUiqtNDmhlFJKKaWUUkqptNLkhFJKKaWUUkoppdJKkxNKKaWUUkoppZRKK01OKKWUUkoppZRSKq00OaGUUkoppZRSSqm00uSEUkoppZRSSiml0kqTE0oppZRSSimllEorTU4opZRSSimllFIqrTQ5oZRSSimllFJKqbTS5IRSSimllFJKKaXSSpMTSimllFJKKaWUSitNTiillFJKKaWUUiqtNDmhlFJKKaWUUkqptNLkhFJKKaWUUkoppdJKkxNKKaWUUkoppZRKK01OKKWUUkoppZRSKq00OaGUUkoppZRSSqm00uSEUkoppZRSSiml0kqTE0oppZRSSimllEorTU4opZRSSimllFIqrTQ5oZRSSimllFJKqbTS5IRSSimllFJKKaXSSpMTSimllFJKKaWUSitNTiillFJKKaWUUiqtNDmhlFJKKaWUUkqptNLkhFJKKaWUUkoppdJKkxNKKaWUUkoppZRKK01OKKWUUkoppZRSKq00OaGUUkoppZRSSqm00uSEUkoppZRSSiml0kqTE2pAIvINEdmb7nKkEpHLRWSbiMREZHW6yzOQ8Xrs0klEFoqIEZFV6S6LUmdqvP6Pa3wcP8bTforIahG5L93lUGo4xtP/UjKNt2fGqRPenu5yJBuPZcpEmpxQE82PgU3AHOCWNJdlXBCRWU5AHWxane5yKqVGncbHAYjIN0WkIWWeS0TaBpn/T2NbSqXUBKPxNoXWR9VI0OSEmmjmAy8aYw4bY9rSXZhx4jBQnjR9AUikzNMTp1KTn8bHgb0MlIrIkqR5K7HrQIEB5hcCL41h+ZRSE4/G2xOlvT4qIr7R3L4afZqcUIhIQER+LCKdItIuIj8G/CnLrBSRZ0WkSUR6RGSDiFyf9Po3RKR6gG0/ICIvD7EcVSLyB2f7PSLytIjMc167XEQM4AZ+4WRf7zzF9r4lIq8nPb/CWe/bSfO+IyJvJD2fJyKPi0iHcyxeEJFlKds9x5nfIyLNIvKEiMwcpBxFIrJWRF4VkbyhHIvTYYxJGGMa+ieg05nfkDS1OZ+zEZEPp5RvrYjck/Tc5xyXgyIScpot3pWyzudFpFpEwiLS6uxbadLrnxCR/c7ra4DFKet7ReR+Z5mQiOwTkX8WEa/z+iKnrCtT1rvWaUJZPlLHT6nBaHyc2PHR8QbQB1yVNO8q4E/AmgHmdwPrk8p4m4hsduJZjYh8T0Syk14fynfkQRF5SUT+3ImtXSLyVHLcdJa7RkRed+JinYj8TESKk15fIiLPO59Br4jsFJE7kl6fKSLPOesfFpG/TD0YIvJxEXnLKW+L871akPT6ahH5aco64sTprw1+qJUaPo23EzveDrU+mrRKnoj8UkS6RaRWRP4hpbw1IvLVlHn3SVLrCyde3e8c4yPAIWf+B0XkHRHpc47hehE5O2m9K0TkXSeuvysiV6Tuj/OZ7HS2cVhE7hGRfOe1XKfcH09ZZ5aIWCJyyXCPY6bT5IQC+FfgQ8AngQuBXuD/S1kmD3gEuAL7ytLzwFNJFZr7gLkicln/CiKSC3wU+CmnICJZwAtAALjMmXKA58TOgq7DzrgC/IXz9yOn2bjzuAAAIABJREFU2OyrwLkikuM8vxJodh5JmveKU4ZSYC3QBFwCXABUA6tFZIqzzGLsCu0bwCpn/QTwoogEBtivGcDrQD1wvTGm6yT7f0nSSfBk07On2N+R8gvgBuDT2EmFfwF+KCKfcMp6MfB94BtAFXA58HDSvlwI/NKZzgL+x1k+mRuoA24DFgFfBj7vPGKM2Qm8BnwmZb3PAM8YY46MxI4qNQQaH5nY8dEYE3XKnpqEeMU5DickLYwxcee978Ruvv1f2PHwk8DVwD1J6wzlOwJwLvZ35H3AdcAy4LtJ+3kl8CR2PF0O3ATMAp4QEXEW+w3QClzkrP83QLuzvgC/A4qx4/L7gQ9gfyeT+YFvO/Ovwf6M/iDHrjj+BPhY0ncD7M9yJnD/APul1EjReMvEjren6evYdb0V2J/9v4jIVYOvMqCPAlOw4/c1IlIGPIodL5dgf5e+D/TH9QrgGeBt7O/Ql4AfDLDdEPDn2LH/Tuy4+kMAY0w38GtOrKfeDewyxqwZxn4oAGOMThk8AdlAGPhMyvyNwN5TrLsF+Mek508Bv0p6/lns4OsbQjnuxr6yVZI0rxQ7MHwyaZ4Bbh/ivgWcfXuv8/x17B+/UewTTS4QA65yXv8G8GbKNgTYB3zBef4g8HDKMn6n7DclbWcvduWyDvvHuesUZc0C5p1imjbE/b4TiJ/keBjgwynz1wL3OH8vdJaZnbLMv/QfG+BjQAuQfZL3fwx4OWXel53trhqk3P8AbE16/nHsrHvQeT4FiAA3pPv/RqfMmDQ+Tp74CPwt0IGdGPVh/+hZDpw9wPy/TlqvBvhcyrYudY514VC/I86xaQL8SfP+DjiS9Hw18G8p25nhvNcK53kncOdJ9vFqZ9kFSfOmON+T+wY5NkXOehcnfWbNwJ8lLfMb4Ml0/0/qNHmnof4vnWRdjbdm/MTbpG3dyQD10aTj98OUeTuBf016XgN8NWWZ+4DVSc9XA7uT9ws7rhtg1kne+9vAQcCTNO/GU32mwM3Y9VCX83yls85857kbqAW+mO7/p4k8eVCZbi52MFuXMn8t9j8qAE6m9p+xM7NlgAc72CY3H/sJ8JiI/KUxph07m/hzY1+1OpUlwA5jTEv/DGNMo9hN85acfLWTM8aExW4id6WIvIZ91eojwF3YlUvBzjL3N7U7FzhHRHpSNpWF3bewf5l5AywTSFoG7Arha8C9xpivDKGsIewTSLqd6zxuPXahDrA/717n7z8C/wjUiMiL2Jn+J8yxpnqLgcdTtrs29Y1E5PPYn8VMIOi8R/J35XHsTPatwM+ATwEN2FdJlBoLGh8nT3x8Cfh34BynzL3AVuz9tJLmB7HHqOj/XGcC3xOR7yZtqz84zsOuqJ7yO+LYZYyJJD2vx/7R0+9c4AIR+YsByj8f2Izd0uI+p0XHauApY8wmZ5nFQIsxZnf/SsaYZklp4i4iK7CvWK4ASpL2ZybwujEmIiIPYn9H7xO7W8nNwHFdApUaYRpvJ0+8HarNKc9TY+JQvW2MsZKev4tdV9zm1FNXY9dTDzuvLwbWG6eFnGOgeuot2ONmzMNusePCTmKXAfXGmE0ishH4M+xk8w3YMfUXw9gH5dDkhBqqB7Gv4PwtcAA7g/ww9j9pv2exrwzd4QTfc4BPjG0xT/AK9uA7LwP7jTH1IvIK9klNgDeMMWFnWZez3EAVw86kZX4J/NsAy7Qm/d2BHRxvEpEfGGNqByuk0zftVM3k1hhjbjjFMoPpD9ySMt+b9LcLOwt8LnYW/4T1jTGdTuX2EuwmdH8J/IeIXGaM2TqUgojdR/p72N+n14Eu4Hbs4I7zPskV5J9hX824P+UEpNR48CAaH/uXGa/xcTPQhh2zsrCvvBnAiMifkuY3GGO2Je0PwF9jN8tOVQssGGD+yaT+MDIcH49d2AmUXw6wbgOAMeZbIvIQcD325/R/ReQ/jDFfHWCdE4hIELvJ+lrsH0aNzkvbOf77+hPgSyKynGNN0Meqa6FSg3kQjbf9y4zXeDtUA8XE5CEHLAavs/brTX5ijEmIyA3YddmrsbsK/ZuIfMQY88xQCiYi52N3DflX4CvY3ecuAH7O8d+1e7C7o3wVO0nxhDGmFTVsmpxQ+7CDw0XYlZN+F6csdynwt8aYpwDEHgxsDtBficMYY4nIvdg/JquA14wxJwxKdBLbgc+JSEl/ttrpc1eF3dd3uF7FzrB/BOdqGPYJ4mvYAe+JpGU3YjdBq006QaTaiN08bp9TsT2ZGPZJ6BHgTyJypTHm4CDLb8S+ijWY0CleH5QxJioinUBF/zynoloFvJNUDsFusnfS0eqdbPOrwKti33JvD/b4EVuBHdjfp2QDfZ/eMsb8MKksswd4q59iV5A/h30l4IFT7adSI0jj4zETOj46x/9VjiUhkhMAr2KPzZDFsePQf7X0MFBljLl3oO2KyFC/I0OxEVhijBn0qqUxZj/wv8D/isjfY1ecv4ode0tEZL4xZo9TvhLs78lGZ/VF2FdS/9HYY/sgIheR8gPAGLPX+eH0Gey+/Q8YYxLD2Celhkrj7TETOt6OoCaS6qyOs7ETzYNyjsl6Z/oXEXkOOyH7DHasvENE3ElxLfV79h7slmhHE7+SMqC842Hsi22fxR5P6NpTlU2dQjr7lOg0PibspvON2JWzKuA/sK9kJ/eX3Yh9pWUZdtB6Cjt7+2DKtsqxA2EE+MRplCELu//Xy9h9uM7BDuR7SeojyGn08XOW9wI9Tpk+5MwrdJ5bOH1snfml2E3KnsduFTALOzh9B7jIWWYR9kjuDwHnAbOxK24/AOY4y3yj/9hhJwAfwe43N2eMPs87OXkfv8ewEwnnOZ/lY87neE/SMg9hXxH8OHYzyxXY2eAvOa9/GPgr53OagX2iDfV/3tgVCwu72fAC5/WDJI05gd3Xshs7kM9znrcB4QHK/LLzfXo63f8rOmXepPHx6LITPj4C/8eJVVGOH5dhWdL8u1LWucOZ/4/AUuc7cBPwk9P8jjwIvJSy7dtx6tDO8yucY/8953s0F7uFxP3OdyAH+BH2ldbZ2JX01dhXMcH+gbMZeMs5/iucz6sLZ8wJ7CbHYezkxlzsZM0G5/O+M6V8H3G+qwlgerr/F3Wa/NMQ/5c03prxH2+d97yTwcecuD1l3kvJnyP22BBt2D/4q4D/dj7r1UnLrCZlTB3seujXgPOx66lXOcfzW87r07DH5rjfOY5XYcfOo2XC7kpkYbfanYM9SGstA4xlgR2XI8DudP8PTYZJ79ahAP4e+D32laT1QAH2P1qyu7CbWq13ln0Ou0JzHGPfReEZ7AD82FALYOw+btdi/3O/hj0CcS/2iMJD6SN4su3GsLsNuHGa5Rq7/+G7zvbXJy3biD2ibwt2BrsaO+jPBI44y+zEDno52CeNHcC92CezjgHeP479I38tdsZ6fuoyY+wL2CfYl7E/p2exWzsk+xT26PTfwB6c6EXs5pD7nNfbsbPwL2IPQvRt7AGLHgIwxqzDPiHd6Wz7i9gjyif7H+zmcr/CHi15ubOdgfwUuwndKUfZVmoUaHxk0sTHl7H7YzeZpHEZsK+49mD/eDiuxZgx5pfYI8HfiH08NmDHxrqkxYbyHTklY8yr2ImH5di3OH0XuzLejf0DJo79Y+Z+7Nj8PPYPuY876xvsxEkn9vfkGewxgjYlvUcLdlLkGuwrxN/FTg4P1F3u9862njPH+morNZo03jJp4u1I+HfgD9hJlTXY8ejRIazXiX38nsS+IPcA9vH7FoAxpg77bkbnYSclfkBKPdXY3T++gz0g/Fbs1sEnG7Ojv546YAs7dXrEyfgoNWJEZD32oFpfTHdZ1MQnIn+DfdKYabRZsZrgND6qicIZCLMWuM0Y82S6y6PU6dJ4q8aCiLwX+zbO040xTekuz0SnY06oEeP0bb0RuxncbWkujprgxL4v+Qyc+09rYkJNZBof1UQhIl6gmGMtRJ5Oa4GUOk0ab9VYcMZtm4odKx/SxMTI0G4daiQ1Y/eV/StjD9h1lIg8KyI9J5mGNQK4iNwzyDa3n3oLapy7F7s58gbsJndKTWQaH9VEcTF20/FrgU8ZvUOSmng03qqx8LfYXaXjJN1tTp0Z7dahxoSITMPuBzeQkNP/63S3ORX7vsMDiZnBRyNWSqlxQeOjUkqNDY23So1vmpxQSimllFJKKaVUWmVUtw4R8YjILBHRsTaUUmqYNJYqpdSZ01iqlFLHy7RgWAkcOHDgQLrLoZRSo0HG6H00liqlJjONpUopdeZOO5ZmVMsJpZRSSimllFJKjT+anFBKKaWUUkoppVRajXlyQkQuE5E1zu112kTkyaTXrhaRLSLSJyK7ReSjKesWi8gjItLlrHuPiPjHeh+UUkoppZRSSik1csY0OSEilwJPAfcAU4Ay4DvOa7Oc134IFAB/AzwoIucnbeIhIAeYCSwFVgH/NTalV0oppSaHt/bFOdSaSHcxlFJKKaWOGuuWE/8G/NQY85AxJmSMiRpj1juv3QlsNcbc78x/Bnga+CwcTV5cB3zZGNNujKkHvgbcJSKBMd4PpZRSakJKWIafrY3wo5cjhGN6O3GllFJKjQ9jlpwQkWzgfOfvjSLSKiJviMhVziJnARtTVtsIrEh6vc8YszPl9SCwYID3K3Buz3R0wh4VWSml1BBpLJ18mroM8QS09hie3BRNd3GUyggaS5VS6tTG8laihdjJkNuB9wLbsFtLPC0iS4E8YEfKOh3OfJzHjgFeJ2mZZF8Avn7GpVZKqcymsXSSqWu3AJhf6uKlHXHOn+thVok7zaVSatLTWKqUUqcwlt06up3HB4wx7xhjYsaYe4ED2N01uoD8lHUKnPkM8jpJyyT7PjA7ZbrkjPZAKaUyj8bSSaau3UIEPneFn7yA8PO1URKWdu+YKMIxgzH6eU1AGkuVUuoUxqzlhDGmU0T2A6ln1P7nW4DrU15bBWxOej1bRBYaY3YlvR4Cdg/wfh2ktLQQkeHvgFJKZSCNpZNPXbvF1FwhP+ji4xf6+PErEV7aHue6Zd50F02dQkefxT89EeKi+R5uO19vVjaRaCxVSqlTG+sBMX8EfFpElomIW0TuAmYBzwI/B5aLyF0i4hWR9wHvB34CYIypAZ4H/lNECkWkAvgW8DNjTHiM90MppZSakOraLSqL7NP/ypluVsxw8+SmKM3dVppLpk7lpe1x+qL24/Y6vduKUkqpyWWskxP/jX0b0eeBduDPgfcZY2qMMQeADwBfxO6m8X3gLmPMW0nr347dUuIgsB14G/jS2BVfKaWUmriicUNTl6GiwD79iwgfv9CHCPxqXVS7C4xjfVHDn3bFWDHDTVm+8OCaCL0R/byUUkpNHmOanDC2bxpjKowxecaYC40xf0p6/SVjzHJjTJYxZr4x5pGU9VuMMR911i00xnxWW00opZRSQ1PfYWHgaMsJgKJsFx9a5WN7XYK39uvV+PHqT7tihGLw/hVe/uwyP50hw2/ejKS7WEpltFjYEOrSVmdKjZSxbjmhlFJKqTTpv1PHtMLjT/+XL/QwZ4qLh9+K0BPWq/HjTSxueGl7nMUVLmaWuJlV4ubGFV7e3Jdg44F4uounVMba/kKENfeHiPZp3FRqJGhyQimllMoQde0WHjdMzT1+ID6XS7jjYj+hCPx2QzRNpVMns25vnM6Q4YblvqPz3nuWl1klLn61LkJnn165VSod2ussYmGofk3j5kRT83aMAxti6S6GSqHJCaWUUipD1LXb4024XCfeJWB6kYvrlnlZtyfOznrt3jFeWJbh+W0xZpW4WFh+rNrmcQmfvtRPJA4/f13HC1FqrMVChr4Ogy8LDr0Tp7NB4+ZE0dNqsePFKDteitKwW1ufjSeanFBKKaUyRF27dUKXjmQ3rvAyNU/45boI0bj+2B0PNh1M0NRluH6Z94RbT1YU2OOFvHs4wet7tIKt1FjqbLRbLC29zo8vCNte0CThRLHr1ShuL+RNdbHlDxH6OrX12XihyQmllFIqA/REDB19hmmFJ7aa6OfzCHdc5Kepy/DMZm3umm7GGP74bozSPGHlTPeAy1y52MPCche/eVNvB6vUWOo8YreUKJ7pZuHlPjrqLOq2aZJwvGs7nKBxT4K5F3pZeYsfLHjn9xGshCaWxgNNTiillFIZoN4ZDLNykJYTAIsq3Fw038PzW2PUtumP3XTaWW9xqNXiumXeAbviALhEuOsSPyLwszURLL1yq9SY6GywyCoQfEGhcrmHgnIXu16NEdNb/I5bxhh2vBwlkCvMPtdLdqGLZe/101FvUf2aJuTHA01OKKVGXVPTFh757dW0d+xLd1GUylj9d+qoOEVyAuCj5/rI8sMvXo9gWVrRTpdn342SnyVcOM8z6HLFOS4+doGP3Q0WL23XK7dKjYXOBov8MjueighLrvUR6TXsWauDY45XR3Ym6DxiseBSL26vnfCtWORhxtke9r8Zo2mfxs900+SEUmrU7dj5EOFwG1u3PpDuoiiVsWrbLYI+KAyevFtHv5yAcNv5fvY3W6zepZW1dKhpSbDziMU1Sz143af+zC6a52HFDDdPvB09mohSSo2O/sEw+5MTAAUVbqaf5aFmY5zuFv0fHG8SccOu1VHyprqoXHp8wnfxVT5yp7rY8nSEsHaPSytNTiilRlUo1MKhQ6vx+fKoqXmeru7D6S6SUhmp3hkMM3VQxZM5f46bJdPcPL4xSluPVtbG2rPvxsjywWVV3iEtLyJ88mI/WV64/7UIce0/rdSo6R8MM7/s+LFgqi734fbB9hcjOjjmOHNwU5xQp2HhlT4kpZuc2yusvMlPIg7vPKktBtNJkxNKqVG1Z++TGBPniiv+CxEP27f9PN1FUirjGGOoPcWdOlKJCLdf5MMY+PWbOgr9WGrstNhUk+CKhV6yfENLJgHkZdkDmh5qtXhmi/afVmq09A+GmV96fEz1B4WqS3y01lg0VOutRceLaMiw9/UoU2a7mTJ74MGFc4pdLL3OR9thiz1rNX6miyYnlFKjxrIS7N79BGVl51JWeg7z5n2Avfuepq+vOd1FUyqjtPcZQlFOKzkBMCXXxQdX+th8KMGmg1rRHivPb43hdsNVS4bWaiLZylkeLprn4Y9bYuxv1s9MqdGQPBhmqhkrPeROdbHj5SiJmCZ1x4O966LEwrDwSt+gy1Uu81K53MPe12O01Gj8TAdNTiilRk39kTfp7T1C1YIPA7B0yScxxmL7jl+luWRKZZY6564bp5ucALh6iYfpRS4eXa+tJ8ZCR5/Fur1xLp7vIT9r6K0mkt12gY+CoPDAaxEicf3MlBppyYNhpnK5hCXX+Ah3Gfau0yvw6dbXYXHw7TiVyz3kTT32mb3euIN1TTtPWH7JNT5yioXNT0WI9Gr8HGuanFBKjZrd1Y8RCBQzffrlAOTmVjJ79nXs3v0Y4XBHegunVAap6xh+csLtEi5f6KGlx9DYpRW10fbS9jgJA9ctPf1WE/2CPvv2og2dhic26p0DlBpJAw2Gmap4hpuKxW72vxWjVweoTavq1VEQqLr0WEyt72vlbzf8jL/b8DNawp3HLe/xCStvDhCLGDY/Fdak/BjT5IRSalT09jZSW7eG+fM+gNt97ISwdOldxOMhdu16OI2lUyqz1LUZCoNCtn94V+Kryu0+utVHtJnraOqLGFbvirFqlpupeWdWRVtU4ebqxR5e3hFnZ71+bkqNlM6GgQfDTLXoSh/ihh0vaYIwXTrqE9TvTDDnPC+B3GMx9Xvbfo+IELMS/KT6uRPWy53iYsm1PlpqLPa9oa1fxpImJ5RSo2LPnt9hjGH+/FuOm19YMJfp069g566HicV601Q6pTJLXYdFxTBaTfQrzRMKgsIuTU6MqtW7YoRjcMPy4beaSHbLKh9l+cKv39Q7Byg1UjobBh4MM1Ug18X8i7007U3QtFdvyTzWjDHsfCWKLwhzLzgWU9c17WR1w1buXnANH5l9MU8efJN9XUdOWH/6cg8Vi91Uvxaj7bCe+8aKJieUUiPOsuLs3vM7plVcSG7utBNeX7bsLqLRLqp3P56G0imVWRKWob7DovIMkhMiQlWZi+oGS3/kjpJY3PDSjjhLprmZUTz4Fdmh8nmE65Z5OdJhONCsTcuVGgmDDYaZava5XrKLhO0vRUno+C9jqnFPgrbDFgsu8eFxWg1GE3H+c+vjzMiewifmXMHdC64j6PHzPzufPmF9EWHZ9X6CBcI7T0aI9unnNxY0OaGUGnG1tWsJhZpZ4AyEmWpKyVLKy89nx45fkUhExrh0SmWW5m5DPAEVhcPr0tGvqtxNV8hwpFMraKNh3d44XSHD9ctGptVEv1WzPPjc8LpeuVVqRAw2GGYql9seHLOv3XBgg3YPGCtWwrDr1SjZxcL0FZ6j8x/a/yqHe1v4yrJb8Lk9FPiy+fSCa1nbuIMNzbtP2I7HL6y8yU+0z7DlGW2BNhY0OaGUGnG7dz9GMDiVysr3nHSZZUvvIhRqYe/eE7PVSqmRU+vcqeNMWk4ALNRxJ0aNZRme2xpjVomLheUjWzXL8gkrZ7lZvz9OVK/cKnVGhjIYZqopczyULnCz9/UYoS5twTQWDm+J09tmWHSFD5fLTsw39LVz/+4XuaJsORdOXXR02VtnX0J5ViHf3/EUljnx88kvc7PoKh9N+xIcWK9J3tGmyQml1Ijq7q6jrv4N5s+7CZfLc9LlysrOpaRkKdu2/xzL0mCv1Gipa7cQgfKCMzvlT8kVirJ13InR8HZNguZuww3LvYicWQuXgVw830soCpsP6Wen1JkY6mCYqRZf5cMY2PmKDo452mIRw+41UYqmu5g679jn9N/bf48xhi8u/eBxy/vdXj6/6H1Ud9byXO2mAbc5c6WHsio3u1ZH6WnVBNNo0uSEmlDi8XC6i6BOYc+eJxAR5s+/edDlRIRly+6mp6eOmpoXxqh0SmWeunaLqbmCz3NmP3rtcSfcVDcktGnrCDLG8OzWGKV5wtkzRmasiVRV5S6KsoXX92giWKkzMdTBMFMFC1zMvcDLkZ0JWg9qknA07X8zRrTPuVuKk+x9q7mal49s4a75V1MRLD5hneumrWRR/nT+d9cfiCRO7H4jIiy9zo/LDbvXaIJpNGlyQk0YHR37+c3Dl7N+w3cxAzS7UumXSMTYs/dJKqddQnZ26SmXn155CQUF89i67Wf6mSo1SuraLaadYZeOflXlLnrCUN+hyYmRsqPe4lCrxfXLvUebH480lwgXzfewoz5Be6/GWqWG63QGw0w19wIvWfnC9hcjWJbG0NEQ7rbYvz5GxWI3BRV2sjdmxfmPrY9TGSzhjnlXDrieS1z89ZIP0BBq5+H9rw24jD9bmH2enWDq1BaEo0aTE2rCqK19DcuKsnPnr3nttX/QgRTHocOHVxMOt7GgauCBMFOJuFi29C46OvZx+PDAJwOl1PBF44ambjNiyYn+cSe0a8fIefbdKAVB4YK5J+8GNxIumufBGHhDB8ZUathSB8NMGItoYmj/U26vsPAKH93NhuZ9GkNHQ/VrMTBQdZnv6Lzf7H+Ngz1NfHnZzfjdJx9weFXJfC4pXcIDe16kI9Iz4DJzzvPizYJdf9LBTUeLJifUhFFf/yYFBXM555wvUHPwRV586S+IRrvTXSyVpHr3Y+TkVFBRfsGQ15k16xpycirZuu0BbSqu1Ag70mFhDCOWnCjJdVGSo+NOjJQDzQl2HbG4ZokXr3t0Wk30m5rnYn6pi3V74xprlRqGgQbD/O7WJ7jiuX/gnzb9io0te075v1W2wI0nAEd2aQwdaV1NFrXvxpl5joegM8ZSU6iDe6uf45LSJbyndMkpt/GXi99PKB7hvt0Ddzf2BoR5F/loOZCgpUY/w9GgyQk1IcTjIRqbNlNRcSFLl3ySS97zHZqbt/Dcc3fT29eU7uIpoLPrIA0NG5g//2ZcrqH3m3a5PCxb+ilaWrbR0LB+FEuoVOapbXfu1FE0cqf7BeVudjcksPQH7hl7clOMbD9cWjW6rSb6XTzfQ0OnYX+zdu1Q6nSlDoZpGYsX69+hxJ/Hnxq28bl1P+Lml7/D/btfoDHUMeA2XG6hbL6Hxj1xEnr3nBG185Uo3gDMv+hYq4nv73iShLH40tLBx0HrNye3jJtmXsijNWs51NM84DIzV3oI5ArVq6Oa6B0FaUtOiMjvRMSIyOVJ864WkS0i0iciu0XkoynrFIvIIyLSJSJtInKPiPjHvPBqzDU2voNlRY9ekZ8z5wau/n/snXd4VVXWh999e3rvFdJpSei9qCBF7M6og469jKjjjDrWcSyjjo5j/cY2jn3sXamCCAmGltDSAyEhvd2Qevv+/kjAAAHSE8h5n+c+ufeUvdfNSfbZZ+21fuvsl2lqLmflimsw1u8bZAsV8vK+RAgNMdEXnPrgY4iKWoqTky+79/y3HyxTUBi+lBklGnVbpY2+Ij5QRbMZSuuUB9zekF9hZ2+pnYVjtTjp+jdq4jATR2jQaWCzIoypoNBtjhXDzKo/SL2lmVvjF7N6wWM8lryMACdPXs1ZwdK1j3JH2uv8WLYT6zEVyQLj1djMKCvvfUjNATs1hXaiZ+jQOrWNp9tr8llTmsHvo88m1MW3y23dFLcQnUrDK9nfd7pfrRHEztJSX+6gMk+5hn3NoDgnhBBXA87HbIsEvgVeAjyBPwHvCCGmdDjsQ8AViADGABOB5/rfYoXBpqw8DZVKR0BA8pFtQUFTWHjuf3BIG6tWXUdlZeflfxT6H7vdzL6CbwkPn4uTU9dvAIdRq3WMHnUVFRXbqK7e0w8WKigMT0qMDoI9Vaj7UGgx7rDuRIXinOgpUkq+Srfg7iQ4K+HEOdB9jUErmBChYWuhDYuyaqug0C2OFcNMrcxCIJjqH49Bo2Nx2ERen7Gcr89+iGtizqGgoYz7tr/DojWP8NzeryhoKAPAb4QajR4qlNSOPkH2iGKVAAAgAElEQVRKSe7PFgzugojxbVFoNoedZ/Z8QbCzN7+PObtb7fka3Lk6+izWl+9iV11hp8eEjNXg6iPI/dmiiJv2MQPunBBChAJPADces+saYI+U8i0ppUVK+T3wHXBz+3mRwLnA3VJKo5SyDHgYuFYIYRgg8xUGibKyNAL8k9BonI7a7u0dx+JF72Aw+LBm7R8oKlo3SBYOb4qK1mG2HCIu9pIetxEbewk6nTt79r7dh5YpKAxvyowOQjz79lbv46rCz02Qq+hO9Jiccgd5FQ4Wj9Oi1w5M1MRhpsdoaLXAzmLl+ikodIdjxTBTq7IY6xWBp87lqONCXXz5Q8ISvpv/CC9NvZkJPtF8VpjC5Rue4eqN/+L70q0ExKipyLfhsCsPtr2lqsBOfZmDmJla1O0lsz8u3Mj+xgr+NPoiDGrdKVo4nmVR8/DVu/Ni5jedpm6oVIK4OTqaaiWle5VItL5kQJ0Toq3Y7H+BJ6SUxcfsTgS2H7NtO5DUYX+LlDL7mP3OQGwnfXkKISI7voDQ3n8LhYGmpaWa+voCgoM7F1l0dQ1m0cL/4uOTwIaf7yU75+MBtlAhN+9z3N3CCQyc1OM2tFpnEhKu4ODBDRiNBX1onUJvUMbS05dms8TYIgnx7vuH37jDuhPKilG3kVLy1Q4L3i6COfEDozXRkbggFT6uglQltWNAUcbS0xvLMWKYtaZGsuoPMiNg1AnPUQsV0/0T+Meka1m14FH+POYiLHYrj+38iJqAEmwmqClUnIS94XDUhIuXIHRs23haYzrEm7mrmO6fwJzAMT1q10mj55b4xew2HmB9+e5OjwmIVeMZpCJvk1XRD+lDeuycEG2MFkK4deO0WwEhpXyjk33uwLHqMfXt20+2nw7HdOSPQOExr03dsFVhiFBWngZAcPC0Ex5jMHiyYP6rhIXNYevWZ9iR/rIiUjNAGOv3UVW1k5jYixGid/7OhPjL0Wic2KtETwwllLH0NKW0XQyzryMnoK2kaIsFDiq6E91m90E7+6sdnJfU/xU6OkMlBNOjNWSV2qlrVq7fAKKMpacxDceIYW6uygI4qXOiI556V64YOYcP5txNkJMXn5hWodErVTt6S1mWncZqSexsHar29MUXs77D4rBxz5iLaVsX7xlLwycT5RbEy1nfHacbAiCEIG6eDlODpChdcfb2FV2esQgh/imEuL79vQDWAXuAEiHEiZ8afz0/irY0jBtOcEgD4HHMNs/27SfbT4djOvICMOKY16xT2akw9CgvS8Ng8MbLK+akx2k0BubOeZbY2EvZu/dtUlMfweFQ6hD3N3l5X6BSaYmOWtrrtvR6D+JiL6XwwGoaG0v6wDqFPkAZS09Tjjgn+rBSx2Hi2lcPc8qVh9vu4JCSr9Ot+LkJpscMfNTEYaZFa5BAWoEyoR5AlLH0NOZYMczUqmx89e7EuYd0qx2NSs0VI+eQUV+APsKkpHb0AoddkrfRgru/iqCENqdRRu0+VpZs56qoswhz9etV+2qh4o5RSylpqeGLA6mdHuMbocZ3hJqCzRasJuU69gXdmbFcBmS2vz8XGAdMA94DnuzC+bMAH2CHEKJGCFHTvv0bIcSrwC7aBC47MhHY2f5+F+AihIg/Zn8rkHdsZ1LKeinlgY4vQHnaOc2Q0kFZ+RaCg6Z0aVVepVIzdcr9JCX9gX37v2fdujuxWpsHwNLhic3Wyr593xMRcQ4Gg1eftDlq1DKEULM3890+aU+hdyhj6elLqdGBkw68nPt+dd7LRUWAuyC3Qln16w7pB+wcrHNwfrIWTQ9ESkvqc/j7qvNZn/tOr+zwd1cRG6giNd+mRBkOEMpYenrTUQzT5rCTVpXDjIBRPVqZvyBiKq4aA1udtyupHb3g4G4bLfWS2DlahGi7Lv/Y/TmBTl5cFzO/T/qY7p/AZN9Y3sxbQ6O1pdNj4udosbbC/q3Kgmhf0B3nRAC/DqILgc+klFtoq66RdMKzfuVTYGT7sYdf0BZJ8QDwLjBOCHGtEEIrhFgCLAVeB2gfxFcDzwohvIQQwcDjwNtSSlM3vofCaYTRmI/JVHfSlI5jEUKQOO4Gpk9/hPKKbaRufrQfLRzeFB5Yg9Xa1CshzGNxdvYjOvoCCgq+paWl8xrTCgoKp6bU6CDUS9WrsNaTERekJr/Cjl3RnegSDofkmwwLQZ6CKSO7HzVRUL2d//v5RupbKvh+70vsLFnbK3umR2uobJDsr1aiXxQUTkVHMczdxgM02UzM8E/oUVsuGgMXRUznK/NaVDqppHb0ALtVkp9ixStEhX9UW9TE5wdSKGgs50+jL8Sg6b4IZmcIIbhz9Pk0WFp4J79z0X2PIDVBCWoKt1oxNyv3w97SHeeEEQhsf38WsKH9vQDUpzpZStkipSzp+GrfVd1efaMQOB+4i7Y0jReAa9sdIIdZRlukRBFtURw7gD934zsonGaUlf0CtJUN7S4x0ReQOO5Giop+VMpT9hN5eV/g4TESf//kUx/cDcaMvhopHezc+WqftqugMFyQUraVEfXqP93r+CA1rVYorlUebrvClv12yuslFyT/mhvdVfaU/sQbKcvxdPLnLwu+INInkY+2P8JBY1aP7Zk4QoNOgyKMqaBwCo4Vw0ypzEQtVEz2i+txm5ePnI1D7cDoX66kdvSAonQb5iZJ3FwdQggONFbyas5KpvjFMS9oXJ/2FecRyuLQiXy0/2fKW+o6PSZ2lg6HDQpSLX3a93CkO7OWVcCbQoj/0pYnt7p9+2jgQE86l1IKKeWGDp9/lFKOk1I6SSljpJSfHHN8jZTyN1JKdymll5TyZiVq4symrCwNT89onJ17ljc2atQyDAZv0hWBzD6ntjaHmpq9xMVe0ucrs25uoYwedRX5BV9TUpLSp20rKAwHjC2SVguE9qNz4lfdCWXV71TYHJJvMyyEeasYH3nK9Zyj2HrgG95Ju4dgz1iWz3kLX9cwrp36HK56L97afBf1rVU9ssmgFUyI1LBtvw2LojSvoHBCjhXDTK3MJtknCletocdtBjh5siA4mbWajW2pHQeUcbSrWM2Sgl8s+I5Q4xOuprK1nuVpr6FXaXhg3G/6JVrw1oTFCAT/zlnR6X5XHxVhiRqKMmy01CsO+97QnVnLHbSpCnsDl0gpD1fKmEBbyoaCQp9is7VSWbXzhCVEu4JW60ziuBupqNxOWdnmPrROIS//C9RqAyNHLumX9pOSbsHLM5rNvzyGyXRsoR4FBYWTUdpeRSOkH50THs4qAj0EuRXKROxUbM63Ud0ouXC8FlU3Js7rc9/l4x2PEus/mVtnvYaLvk0H3M3gzfXTX8Bsa+a/m+/CYmvtkV0zYjS0WiGjSHkwUlA4EUfEMANVVLQY2ddYzkz/rlXpOBm/i55HllMWDo1NSe3oBoVbrVhb27QeDlmauT3tNRqtLbw07RZCXHz6pc9AJy+ujJrDypLtpNfu6/SYmJlahAryNinaE72hy7MWKWWjlPIOKeWFUso1HbY/JKV8on/MUxjOVFZm4HBYCA7quXMCICbmYlxdQ9vLiyqT6L7Aam1m//6VREbOR6/vrJJv71Grdcyc+QRmcz1pW55SIl8UFLpBafvKTX+mdUBbakd+hR2bojtxQqw2yXc7rYz0UzEurGtRE1JKvtvzIt/vfZGk0AVcP+NF9Brno44J9ohh2eQnKa3P4aPtj+Dowf0tNlCFr6tgs1K1Q0HhhBwRw3QSpBwpIdozvYmOxHuEkuw/knz3XCrylNSOrmBpkRRutRIYp0bvZ+euLf/hYHM1z02+gXiP0H7t+7qY+YQ4+/D4zo8w2Y5P3zC4qYicqKV0r42GKuV5o6d0a9YihPARQtwhhHhZCOHTvm2qECKif8xTGM6UlaehUukICOidnoFarSU5+Q8YjXkUFq7qI+uGN/kF32CztRAXe2m/9uPtHUtS4i0UFa2l8MDqU5+goKAAQGmdxNNZ4KrvHzHMw8QHqTHboKhGmYidiI15NozNkosm6LoUbmx32Pg0/XF+ynuX6SMvY9nkv6NRaTs9dnTQbJaO/SO7Sn9kddbr3bZNJQTTojVkldqpa1KuoYJCZ3QUw0ytzCLY2ZtI14A+aXtZ1Fy2u6YrqR1dpOAXCzYrRM1Uc/+Od9ljPMDj469iom9Mv/ftpNHzUOJvOdhcw+u5Kzs9JmqqFo0ecn9WtCd6SpedE0KIMUAObekdtwAe7bvOo61qhoJCn1JWlkZAQDIajVOv2xoRuQBv73gydr6K3a6EW/UUKSV7977Dtm3PERAwHl/fMf3e5+jRV+PnN44tW56iuaVnudUKCsON0npHv6Z0HCa2PQc7V9Gd6BSzTfLDLitxgSrig059Pax2M+9u+QtbDnzNgoQbuSTpPlTi5NEWc2KWMSXyQtbmvMmO4s4nzCdjerQGCfyyT4meUFA4lo5imGa7lW01+czw71kJ0c6Y7p+APaABi9pMebbyP3gyWhscFO2wETJazYuln7GpMpO/jLuUc4K7UjSyb5jkF8vFEdP5cN8G9hoPHLdf5ySImqqlqsBOXYlyX+wJ3Zm5PAf8D4gBOopQrgJm9aVRCgotLdXU1xcQ3IMqHZ0hhIrxyctpaiolL++LPmlzuGGztbJp04PsSH+JyIhzOPusl/utRGFHVCoNM2c8hsNhZXPq35T0DgWFU2B3SMrqHYR49f//p7uTINhT0Z04EeuzrDS0Si4cf+qoCZO1iTdSb2dv2U9clHgvC0fd2qUxVgjBJcn3M9J3PJ/seJQDtbu7ZaOfu4rYQBWb823K+KqgcAwdxTAzavdhsluYEdB7vYnDqISKK2Jmke2aRWmeVUntOAkFm61ICZsDN/Ldwa3cFLeQSyNnDLgdd4w6Hz+DB4/t/BiL/XiHUuRELXoXQc5PFmVM7QHdcU5MAl6Rx/+WD/JriVEFhT6hrDwNgODgaX3WZnDwNAIDJ7J7z5tYrc191u5woKmpnJWrrqfwwGrGJy9n9uyn0Wp7H9HSVdzdw5kw4S7KytPIzft8wPpVUDgdqW6U2Oz9K4bZkfggNfmVdmzKpPooWi2SVXusjAlRExN48uiHRlMd/954E4U1O/ndpL8zK/rybvWlUWm5ZuqzeDj58/Yvf8bYUt6t82fEaKhskOxT8qQVFI6ioxhmSmUWepWWiT7RfdrHotCJFPkUIM0qJbXjBDTXOTi4y0briEr+W76CyyJncmPsuYNii6vWwAOJv2F/YwVv5a85br9GJ4iZqcVY4qBqn3I9u0t3Zi4C6CzpMQxo6BtzFBTaKC9Lw2Dwxsur73LIhBCMH38HJpORzKwP+qzdM52Kyh38sGIZjY0lnH3WC4wde92AREwcS1zspQQHT2PHjudpaCge8P4VFE4XSgagUkdH4oLUWGxQqOhOHMWPmVaazXDhhM71Ig5T11zGKz9fR2XjAa6f/jwTwhf1qD9XvRc3TH8Bq93MW5vvwmxr6fK5EyI16DVtVUUUFBR+paMYZmpVFhN8ozFodH3ah16tZeLYIEwqE/l7Gvu07TOFvBQLDuHgZfXbnB2UyN1jLx6UuehhZgSMYknoJN7J/5GcQyXH7Q9L1ODsKcjdoERPdJfuzFzWAX/o8FkKIXTAQ8DxbiMFhR4ipYOy8i0EB01BiL6dXPv5jiEi/GwyM9+ntbWuT9s+05BSkpP7GWvW3IpO58GSxe8RGjp4GVxCCKZPfwSVSktK6l9xOBRvtIJCZ5QaHQgg2HNgnBOK7sTxNJkla/ZaSY5QE+l74qiJiob9vPzzdTSZjdwy61USAnsXohzgPpKrpzxN+aECPtz6UJcreBi0ggmRGrYV2jDblIm0gsJh6tvFMIubqjnYXMPMPkzp6MilUTPId8+lpgAlteMYGqoclGXa2OyVQkJQII+Pvwp1Hz8f9IQ/jbkQT50Lj2V8hO2YOalKLYibo6OxWlK8U3H6dofuXNm/AJcIITYDeuD/gHxgDPBAP9imMEwxGvMxmer6NKWjI8nJt2G3m9mz561+af9MwG638kvaE2zZ8hQhwVNZsvhdPDwiB9ssXJz9mTLlfqqrd5OZ+d5gm6OgMCQpNTrwdxfoNAOzquRmEIR6qRTnRAfW7LFissIFySdeYS0xZvN/P9+AQzq4bc5/GOGT2Cd9xwdO58LEu9lbvoEVe1/p8nnTYzS0WmFnkXIdFRSgTQyztV0MM6UyE2gTsOwPvPSuuEZZ0Fh1FOY39UsfpyvbfqzHpDJTMaKAZyddj06tGWyTAPDQuXDfuMvIayjl3YJ1x+0PSlDjE6ki60cLjdVKZGFX6bJzQkq5D0gEVvNrpMS7wHgp5cF+sE1hmFJW9gsAQX0khnksHh6RREefT27eZzQ2lvZLH6czra01rF5zE/n5XzF27HXMm/c8Op3bYJt1hBGR5xIRMZ+du16lri5vsM1RUBhylBoHplJHR+KDVBRUObAqK34capX8mGVl0kg1od6dX4f9NRn8e+PN6DRO3D7nLYI9+rYM3syo3zJ95GWsz3uHbUXfdemc2EAVvq6C1HylopWCAhwthplalU2kqz+hLr791t/iyQmYVCZ2pCuVyQ6TmV+FqUjPnqAdPDvzGly1hsE26SjmBY1jfnAS/8lbzf7GiqP2CSFIWqpHo4P0r03YLMr9sSt0p5SoRkpZJaV8VEp5npRysZTyr1LKKiFE//2nKgw7ysrS8PSMxtnZr9/6SEy8GSHU7Nz1ar/1cTpSU5PF9z8sw2jMZc7spxmfvByV6uRCbgONEIKpU+5Dr/ckJeUh7HallrSCwmEsNklVoxxw50RckBqrHQoHaHWossHB6j1WvtxuYW+JDbN16Ez6Vu62YLPD+SeImsitTOP1lNtwN/hy+5z/4usa1uc2CCG4KPFuYvwm8+mOx9lfk3HKc1RCMC1aQ3aZg7omZZVPQeGwGKbO10p6bQEzA0b3a38jPQMw+pWjKnGnxWLu175OBypajaSsrqFF08y1S8fjYxg6C2UduWfsJThrDDy28yPsx6TSGVxVJJ9voKlGkrlWma92he7MXjqNoRZCeAM/9o05CsMdm62VyqoMgoOn9ms/Ls7+JCRcyf79K6kzKqvvAPv2/8Cq1dcjhJpFC98mMnLBYJt0QgwGL6ZPexhjfQE7d7422OYoKAwZyusdSDlwYpiHiQ1UI4CcfkrtkFJSVGPn6x0WHvmqhQc/b+WzbRZW77Hywhozd3zYwj9+aOXbDAv5FYNXOaSu2cGGHBvTozUEehx/DfaU/sR/Nt+Jn2s4t835D57OAf1mi1ql5fdTn8HbJYT/pN5JQfX2U54zPUaDBDYXKDnSCgqHxTB3NhdgddiZ0U8pHR1JGOeBk92Z1Tty+72vgcJukxSlW8leb6Eo3Up1oZ0WowOH48TjdL25iSdXfU9oYwThUwQRXkN3Hdxb78Y9Yy5mr7GIj/b/fNx+3xFqoqdrKdlto2SPEpl2KrqTtJMkhHhOSvnnwxuEEJ7AWqC6zy1TGJZUVmbgcFgJDupf5wTA2DHXkJf3Benpr3DO2S/1e38ATU1lpKb+DYu1CV+fUfj4jsbXZzSeniNRqQYnh05KBzt2vEhm1vsEBExg7pxnMBi8BsWW7hAaOouYmIvYm/kuoaGzCAhIHmyTFBQGnRLjwFbqOIyLXhDm06470Uf/ig6HJL/SQUaRjYxiO7VNEiEgJkDFb6doSQ5X4+YkKKi0k13mIKfczncZVr7NsKLXQEyAmoRgNQnBKkK9Vai6qezucEhMVmixSJrNkmZzx/eSZgtH3re0769vbXMOnZd0fIWOHcUr+Gj7I4R6JXDTjFdw1rn3zS/qJDjr3Lll1qu8kbKc11NuY9nkJ0kMOfuEx/u5qYgLVLG5wMZZo7Q46wZPDV9BYbA5LIa5qjITZ7WeJJ+R/d7nlMQQvl9/iMLMVhxTHagGQPjxUIWdqgI7/jFqPAL6LlrWbm0Tg9yXZsXcJBEq6BhYIFTg5CFw8VTh7CVw9lLh7CloMhzi/pz/ML/oQlQudiZOH7qOicOcGzKeNWUZvJq9gtkBYwh3PTr6O2aWlrqDdvautuAZrMbVZ/AFPYcq3XkaWgRsFkKUSyn/KYRwp017ohFY2i/WKQw7ysrTUKl0A/KgqdO5MXbMtexIf5GKih0EBk7o1/4qK9P5acPdOBw2fH1GcaBoLXn5XwKgVuvx9o7D12c0Pj4J+PqOxt09os+rlRyLw2ElNfVv7C9cSVzcZUyedDcq1cnL3g0lJk38E+XlW0lJfYTzl36MVus82CYpKAwqZUaJRg3+7oNQ7jdQxU85Nqw2ibaHYpxWmySrzE5GkZ2dB200mUCjhlHBapYmqUkM0+DmdHTbo0M0jA5pe99sluSW28kut5NTbuezbW2RHC56iA9SE+WvxiElJgu0WiWtVjBZJK3WX7eZrNBqkZhPETygVbc5ZZx1bT993QThvhoSw9T4uh09dm/e/zlfZDxFlN8Erpv2PAatS49+Pz3ByzmQ5XPf4q3Nf+S9tHu5JPl+po+89ITHz0vQ8tpPZu75uIUpURrmxmsI9xla6X0KCv3NYTHM8EQVmyuzmeIXh3YAFpE0WhW68FbCikeyqTyLOcFj+q0vc7Mk92cLB3e1DXZ5m6x4BquIGK8hKEGDuofjuN0qKcqwsT/NirlZ4h2uIul8PT7hKkyNkhajpLneQYtR0lLvoNkoMZbZsR3JZDFwDcsBGL1Y12M7BhIhBPePu4zL1j/FE7s+5rXptx3lWFKpBEnn69n031bSvzYz42oDau3Q/16DQZf/y6SURUKIxcAGIUQzsAywAEuklKb+MlBheFFWlkZAQDIajdOA9Bcf/1uycz5mR/qLLF70br/VTM7L/4otW57C1TWEs+Y9j4dHJFJKGhsPUlObRW1NJjW1meQXfEV2zkcAaLUu+Hgn4OM7ipCQGQQFTupTm2y2Vjb8fC+lpamMT17OmDHXDmrN6J6g1bowc8ajrFp9I9t3PM+0qQ8OtkkKCoNKidFBkIcKtWoQnBNBatZm2thX7SA+qHsPs2ab5OM0C1v32zDbwEkLY8PUjI/QMCZUjaGLkzgXvWB8pIbxkW3Tm/oWB9lljjZnRZmdHQfanBVCtPVh0AqcdG0/XfQCHzeBk1Zg0IKTTmDQ/up8+PUFzrquV0NZn/su3+99kVGBM7l66jPo1AMv6Oai8+CWmf/mvS338XnGkzSYajg34eZOx/yJIzQ85CbYkG3jlwIbG3NtRPmrmBuvYWKkpseOJwWF04nDYpjNHvVU1tRzY8DCAes7KdmXjEIra3bk9otzwm6THNhupSDVit0GIyZriJygpTLPTlGGlV3fW8haZyFsnJbwZA0uXYzEs1kOOyUsWFrAJ0JF8oV6fMJ/vR84uQuc3MEn4uh7hJSSjUXZvLxtDeGOYK7wPwcPtSuhY4dGZY6u4Gfw4E9jLuKxnR/xxYHNXDZi5lH7ndxVJJ2nZ9tnZrLWWRi7UD9Ilg5tunXFpZS7hBAXAyuBDGC+lLK5XyxTGHa0tFRTX19A1MglA9anRmMgKfFmNv/yGMUHfyIi/Kw+bd/hsLF9+/Nk53xEcNBUZs9+Gr2+LZRXCIG7ezju7uGMHLGw/Xg7hw4VUlObSW1NFjW1WWRnf0Rm5nvExf2GSRPvQq3u/WBmNjewbv2d1NTsYdrUh4iNvbjXbQ4WAQHjGT36KjIz3yMsbC6hITMG2yQFhUGjzHhqx4CUkve2/IXa5hK8nIPxdg7CyyUYb+dgvJyD8HYJwknbfeGx2EA1QkBuub1bzokWs+TlH00UVDqYGathQqSa+CA1GnXvH4I9nVVMi1YxLVqDlJImM+jUoNPQ785YKSWrsl5jbc6bJIXO58pJT6AZxMg0ncaJa6c9x2fpT7Am+w0aTbVcknwfKnH8tYr0VXPNLDWXTdaxucDGhmwrb2208MkWCzNitcyJ0+DvroQlK5y5HBbD3EkWADMC+l9v4jABUVqkxoS+xIfs+oMkePaNaK6UkqoCO1nrLLQYJf5RahLO1h1JMRgxWUXkJA21RQ6K0q0UbrWyf4sVvxFqIiZo8I9SIzpxfNvMbZoS+7dYsbSCb6SKmJk6vMO6fh/44kAqz+z5gviAUB6cvGjIil+eiqVhk1lTms5LWd8yIyCBYGefo/b7R2sYOcXB/i1WfCLUBCecPs6XgeKkvxEhxJoT7KqnTUzzy8M3dynl0FXPUzgtKCtPAyA4eNqA9hsVdR6ZWe+RkfEKYaGz+0z7wWxu4OeN91FensaohN8xYcKdp2xbpVLj5RWNl1c0MdEXAGC3m0nP+DdZWe9TXbWL2XOexsM9osd2tbRUs/bH22hoKGLO7H8QEXHi/OPTheSkWykt3Uxq6iOct+QDXFwCB9skBYUBp9ksMbZIgr1O/tBdVLeHXaU/EuoZT1VjITmVm7Hajw6ANGhd8XY+2mExwieZcO8Tq9U76wQRPipyyu1c0EWb61scvLDaTPkhBzfN1TNpZP9N1IQQuA1Q0IKUkm92P8fGgv8xOfICfjP+oU6dAAONWqXhtxMewc3gw7rct2kyG1k2+e9oT+D0dtEL5o/Wcs4oDTnlDn7KtrJ2r5XVe6yMCVEzN0HDuFA1qkGI1FFQ6E/q28UwU4y7iXUPwc/gMWB9qzWCgBgNo/JG82H+Kp6YdFWv22ysdpD1o5maAw5cfASTfqPHP+r48VYIgW+kGt9INaZGB8U7bRTvtLH9czMGd0F4koawRA0GVxVWs6RoR5tTwmoCv5FqYmZo8Qrt+ljnkA7+L/sH3i1Yx6yA0Tw54WqcNKdvRIEQggcTf8tvf/oHf9/1Ka9MveU4R3jcnDb9iT0rzXgEqrocmTJcONUsoLSb2xUUekxZWRoGgzdeXtED2q9KpSE5eTkbNtzNvn3fExNzYa/bPHSokPXr76KpuYzp0/7aqzbVaj2TJt5FYOAEUlMe4fvvf8e0qQ8ycuSibrfV0FDM2h//gMlUzz6I7jEAACAASURBVDlnv0RQ0JQe2zWUUKv1zJn9NCtW/p6fNvyZhee+hUYztGphKyj0N6XtYpihp5jopBV+iV7jzB9mv4lB64KUkmZLPXXNZRhbyqlrKTvyvqa5hPzqrZhtLaiEmmWT/05S6InXIuKC1PyYacVsk+hPEf5f1eDg+dUmGlold8w3MDpk8B/e+wKHtPNZ+pNsOfAVs6Kv4IJxfx4QUbuuIoRgyZjbcdP78PXuf/JGynKum/YvnHQnXqkUQrSLi6oxNjvYmGtjU56NV3404+0imB2nYU68FjeD4qRQODM4VOHAxV+y23iA30cP/CJO2CgdVdmSffkNVIw2EujcM6FyS6skf5OFonQbaj2MOkdHxHgNqi5EphncVMTO0hE9XUtlgZ3idCt5G63kp7RFUxhL7VhN4B+lJnqGFq9ujuEWu41Hd/6P1aXpXBIxnXvGXoJmiJWv7wlBzt7cMWopT+/5nG8PbuGC8KNF/lVqQfKFbfoTGV+bmXaV4bTQ1RgoTuqckFJeO1CGKAxvpHRQXr6F4KAp/S4C2RnhYfPw8x3Lzl2vMWLEwl492JaWpvLzxvtRq7UsmP96n4l7hoXOZunSj9m46X42pTxIecVWJk+6F622a/octbU5/LhuOVI6OHfBG/j6juoTu4YKnp4jmTnzCX766S5+SXuCmTMeP+00NBQUekNpFyp1tFobyShZw4TwxUdEGYUQuOq9cNV7dRoZ0ZYOUce7W+7lg60PAoKk0Pmdth8XqGL1HthX6WDUSSaqB2vtPL/GjN0h+fMiAyP9Tv8JKYDdYeXDbQ+zs2QN8+NvYOGoW4fsODQ75kpcDd58tO2vvLLxBm6e8QruTn6nPM/LRcUF43UsSdKyq9jOhmwrX6dbWbHbypw4DeeO1eLpPHScMQoK3eWwGKZlRDV2i4MZAQM/X/IboUallYxqGMNH+3/mrjHdW+RyOCTFGTbyNlqwmiE8SUPcbB065+6PRyq1IChOQ1CchqZaB8UZVsqy7XiFqomZqcWzmxpDAA2WFu7e9hbptftYnnAev48+e8iOlT3h4sjprCnL4Pm9XzPFN+4455Kzh4rEJXp2fGEm5ycLo+efvtEifY1y91AYEhiN+ZhMdQOe0nEYIQTjx99BS0sV2Tkf96gNKSWZWR+wbv2duLoGs2TxB31edcTFJYBzF7zB2LHXU1DwLT+suApj/b5TnldRsYPVa25CrdKxaOFbZ5xj4jDhYXNISrqV/ftXkJX94WCbo6AwoJQaHTjpwMvlxBO89OKVWO0mpo3ous5MWzqEDzfOeJkI77F8sPUBdpas7fTY2EA1KgG57fnanZFfYeeZlSbUKvjLEqczxjFR1XiAVzfdws6SNZw35g4Wjf7DkJ9sjw9byA0zXqK2qYSXNlxLVWNRl8/VqAQTIjX8eZETj13kxPgINeuybNz3aSvvbzZT3eg4dSMKCkOQw2KYmao8PLTOjPHqeSptT1FrBYExGsY2jeXboi00WVu7dJ7NIinLtrHprVYy11hwD1Ax6zonxi7Ud+qYMNutbK3O43/7NpBSmUlFqxEp5Qnbd/VRMeocPefc7sykyww9ckyUt9RxQ+pL7K47wBPjr+KamHOG/FjZXVRCxcOJlyOR3Jj6EgeaKo87JjBWQ+REDQe226jIO0V5qGFEVzQnLpNSHjqJ/gSgaE4o9I6ysl8ABjXNIDBwAiEhM0lPf4ns7P/h7R3X/orHxzseV9eQEw6edruFX9L+zr593xERfjYzZjzW5YiG7qJSaRiffBuBARPZlPIQP/xwFVMm30t09AWd2ld88Gd+/vkvuLmFMP+c/zvj9RjGjb2eurpcdux4AS/PaIKDp576JAWFM4BSo4MQT9UJxykpJZsLvyDUM54wr+47KPUaZ26c8TJvpt7OB1sfADgugsKgFUT6tulOdMbugzZeXW/Gx1Vw17kGfFxP/zUSm93Curx3+DHnLXRqA1dOfIyJEecNtlldJi5gKrfNeZM3Upbz8oZruXHGyyfVFumMYC8VN8wxcEGyg5V7rKTm2diUa2NKlIbF47QEeZ7+11lh+HBYDPMny1amBsWjHqS0rKAEDWVZevwOBXPNpueZ5BtLovcIkrxHHrUSb7O0CV2W59io2mfHYQMnT8GEi/UExKqPuidIKSlsqiStKoe06lx21BZgtluP6tdVYyDGPZho92Ci3YOIcQ8myj0Ilz5Il805VMIf097AZLfwyrRbmOgb0+s2hyphrn68Nn05d6a9zvUpL/HilJuOc3TFz9NhLHGw6wcz7gEqnD2UsVKczDsmhHgbuENK2dj+/oScDikgQohIoLCwsJDIyMjBNUbhKNasuQWTqY7zz/90UO2wWBop2PcddXW51NXlUF9fiJRt3kyt1vWIw8LHOx5v73g8PCIxmw/x04a7qa7eReK4m0hMvGnAUlNaW2vYtOkhyiu2MiJyIVOnPoBO53pkf0HBt2z+5XF8fBI4+6yXMBg8B8SuwcZqbWHFymtoaaliyZL3cXfrG6Xr04ABWXpQxtKhh5SSOz9sYdJIDVdN7zw8tKhuLy/+dDWXJj/A9JGX9rgvk7WZN1Nvp6huD1dNforE0HOO2v/5Ngtr91p5cZnzUSVAfymw8vYmC2HeKv64wICb08CulNU1l7GvJp34gGm4GXxOfUIX2F+TzqfpT1DVeIDk0HO5IPHPuBt8+6TtgaaqsYg3Um6jyWzk2mn/JC6g55GMxmYHq/da2Zhjw2qH8ZFqliRqCfc5baJklLF0GLPjKxM1pRYeDP8rj49fxqLQiYNih90qWftSC9awWlaF/cCeugO02M0AhOr8mWObxsi6WLQVHki7QO8iCIxTExivwSdMdaSyRr2lma3VuaRV57KlKpdKUz0AEa7+TPWLY6pfPAmeoZQ011LQUEZ+Qxn5DeXsayyj2WY+Yk+Is88RZ0W0ezA+ejdcNIa2l9aAq8ZwUs2IX6qy+cu2d3DTOfHilJuJdg/qx9/e0OFgUzXL016j1tzIM5OuZbr/0ZVfmo0OUv7biqufimm/M3RJD+Q0ottf5qTOiU5PEMIJiGr/uE9K2bU4oyGAchMYmthsrXz08Vzi4y9n0sS7Btuco7DbzRiN+6iryznisKgz5mNvV7ZXq/Wo1TrsdiszZzxKZGTnedj9icNhZ+/et9m56zVcXUOYM/tpfHwS2Jv5Hjt2vEBQ0FTmzf0nWq3zgNs2mDQ0HuSHH67C2dmfxYveGS7fX5lQD1Pqmh3c+0krV07VcdaozstVfrLjMTIOruJvS9Zg0Lp2ekxXOZmDYm+JjRfWmPnjAj1jQtsCNNdmWvlki4X4IBXLzzEc5bToT6SUHKjbzcb8/7GnbD0OaUet0pIUOp+ZUb8lwntsj9pttTTy3d4XSSv8Ei/nIC5Jup9RQTNPfeIQp6G1mtdTl1PZUMiSMcuZE7OsV2Keja2StZlWfsq20mqFsaFtTorogCHvpFDG0mHM+ldbqHWu4hmvF1l77uN46ns3XvaGjG9MVBfaOecOZ8wmO3v31lGWbUVV7oZKqmnQNJDlvpf9Xvn4hKkZ5zOCJO8RqITqSHREdv1BJBI3rROTfWOZ6h/PFL/Y48pcHouUkvLWOvIbyiloKDviuChuqsZB58+PepUWF40eV63TEaeFi0aPTqVhffluotwCeXHqzQNa/WQoUGNq4I6019nXWM7fkq88zuFVlm0j42szI6dqSZinGyQr+4Vuj6VdrtklhNABTwG3AoeXZcxCiNeA+6WU5hOerKBwEior03E4rAQPwcoRarUeX99RR2k0OBw2GhqKqavLobYul5aWSsaMvgYfn/hBsVGlUjNu3A0EBIxn46YHWLHyGkJCZnDw4AYiI+Yzc+bjqNVn1EDXJdzdwpgz+x/8uO42UlIfZu6cZ3sV0eJw2Ckp2YSf3zicnLz70FIFhd5TdrhSh3fnf+MmaxMZB1eRHLaw144JAIPW5UiKx/tb7wchSAxpU7SPDlCjFpBb4WB0iOTrdCs/7LIyPkLNjXP1aAdgVcjusLKrdB0b8/9HsXEvTlo35sQsY0zQHDJK1rCt6Dt2FK8gzGs0s6J+S1LoAjRdGCellOwqXctXu/5Jk6mOuTFXce6oW9Br+ieNb6Bxd/Jj+Zz/8PH2R/luzwsUVG/niomP4qrvWaUANyfBxRN1LByrZX22lR8zrTz9g524QBWXTNQx0n/IOykUhhmHxTDzPfYzxit8UB0TAEHxGsqy7PzyvolDFQ6kwwVXN0HQRDUBcWpM3jo86rxwqvNlV10hr+WsOHKuWqgY4xXBTXHnMtUvnlFe4d1KURFCEOzsQ7CzD3MCxxzZbrJbKGqqot7STLPVRLOt7dVkMx/1udlmotlqoqyljiZrK3MDx/Jw0hW4aodfNTVfgztvzLidu7e9xcPpH1BrbmRZ1Lwj+4MTNNQW2dmfZsXFUxAYr0E3wNGFQ4UuR04IIV4HLgQeAlLbN88AHgO+lVLefIrz/wGcB4QBTcBK4F4pZW2HY84BngNigBLgISnlpx32+wD/BhYBNuBT4M6uOkYUD/XQZNv2f5GT8ylXXP4TmjNkgjdYmExGUlMfoaQ0hdjYS5ky+S+ozoCyTL0hM+sDtm//F0mJt5CYeFOP2qipySRty1PU1mbh5RXLooX/HaqRGMpq3zBl1R4Ln2+z8sLvnHHVH/9nsHn/53ye8SR3znuPCO8xnbTQM0zWZt5IXU5xXSZXTXnqiIPiqe9bsTsgwkfFz7k2ZsdqWDZdh0rVv3+izZZDpBV+Scq+TzjUWoWfawSzo69gYsR56DW//s+arE1sK/qe1H2fUtV0AFe9N9NGXMy0kZfi6eTfadt1zWV8ufNpsipSCPWM5zfjHybUK6HTY093pJRs3v8ZX+9+DhedJ1dNfpIovwm9btdslfyca2P1HistFsmdCwzE90BQbwBQxtJhSk2hnS0fm3g34r8smBjHDbGDK6lnt0p+erUVlQYC49QExWvwDD6xttAhSzN7jAewORxM9I3GtZ/0zxR6hsVu4+H091lXvouros7ijlFLj1xLu1XyywdtTigAd38V3uEqvMPV+ISpe1RpZQjQf2kdQohDwJVSyh+O2b4E+J+U8qTxOUKIJ4HPgL2AF/ABYJZSLm3fHwlkAbcD7wMLaHM+zJNSbmk/ZhVgB5YBTsC3QJqUcnkXv0Mkyk1gyPHNt7/BycmHBfNfHWxTzgiklBw6VIiHx4gzTv24J0gpSUn9K/v3/8C8uf8iPHxul881mw+RnvEKeXlf4uTkQ3T0Bezd+zYhITOZN/e5oej4USbUw5S3NprJLrPzz8s7d5r9a92VOKSDP5/9UZ+PCx0dFFdPeYpxIWfz5XYLK3a3iawtHqflognafh2PKhsK2VTwEduKv8dqNxHjN5k5Mb8jPnDGSdMSHNJBftUWNhV8THZFCkKoGRcyj5lRlzPCJwkhBA5pZ1PBx6zM/DcgWTT6D8yMuhy1qsvBp6ctJfU5vL/lPmqaSjh31M2cE38dKtH7ca/RJHl2RSs1TZK7FhiICVTGUmUsHRrs+8VCzgYrT8c9wZtn/YF4z8HXrHI4JEKgzOnOEOzSwT/3fMlnB1JYEjqJh5MuP6LV4bBL6ssc1BbbqS22Yyxx4Ggv5OHmJ/AOU+MTrsY7XI3+JJW5hhD9l9YBWICCTrbvA6ydbD8KKeUDHT5WCSFeAv7XYds1wB4p5Vvtn78XQnwH3AxsaR/AzwVGSSmNgFEI8TDwuRDibimlqRvfRWGI0NJSTX19AVEjlwy2KWcMQgg8PUcOthlDBiEE06Y+yKFDhWxKeYgli9875e9HSgcFBd+yI/0lLJZGEhKuICnxZnQ6N5ydfNmy9R/sSH+RSRP/NEDfQkHh5JQaHYR4df4QftCYRUl9Dpck3dcvk1uD1oWbZrzMGynLeW/L/Vw95SmSIuayJtPKReN1nDu2cw2M3iKlJK9qCz/nf0hOZSoalY4J4YuZFX0FwR5dU4BXCRVxAdOIC5hGTdNBUvd/xtYD37CzZC0hHnFMiljK9uIfKKnPJiFwJpck3Ye3S3C/fJ+hSKhnPHed9SGfZzzJqqxX2Ve9nd9NegJ3J79etetmEPx5kRPPrmjlxbUm/nSuQUnxUBgS1Fc4MDk14eyiJdYjZLDNAej3iDOFgUUtVNw79hJ89G68lruSekszT0/8PU4aPSp1mwPCO0xNzIx2Z0W5g7piO7XFDkr22ChKb/NWuPoIvMPV+Eep8Y9WnzHOq+5ETjwFeAO3yPaTRNtv4f+ARinlX7rVsRDPAxOllLPaP38FlEkpb+twzD3AFVLK8UKIC2iL0HDpsN8PqAISpZS7j2nfEzi2NEEosEnxUA8dCvZ9R2rqIyw972O8vWMH2xyFM5jm5kq+/2EZWq0zSxa/j17v3ulxdXW5pG15iurq3fj7JTFlyn3H/W1u2foMOTkfM23qg8TGXjIQ5neVPr8zKWPp0MfhkPzh/RbOStDwm8nHV+r4NP0JdhSv4G9LVuOkdes3O0zWJt5IWU6xMYurpzzNqKB5aPphUl3XXMaO4hVsL/6e6qZi3PQ+TI+6jOkjLsXN0Hs9GLOtlR3FP5Cy7xMqGvbhpvfhoqR7SAyZf8ZM/rqLlJJtRd/yxc5/oNc487tJTxAX0PsyzcZmB8+sMNFklty90ECE75BxUChj6TBESsn6f7ewS2TROC2fR5KvHGyTFM5wvir6had2fcoor3BemHITnjqXkx7vsEsOVfzqrDCW2LFZIGSMhjHn6tDohtw9qm8jJ4QQb3T4qAIuA+YLIba2b5sE+ACfd6dTIcRvgBuAOR02u9OW1tGR+vbth/fXd7KfDsd05I/AI92xS2HgKStLw2DwwcsrerBNUTjDcXEJYN7cZ1m95iY2bXqAs8568ai0DIulkYydr5Kb+yl6vQczpv+NqKjzOhXRnDTxTzQ2HiRty9O4uoYSHDz0xFz7EGUsHeJUHJLY7HQaOWGyNrcJYYYu6FfHBIBB68pNM19pj6C4j6unPM24kLP6pG2zrYXdpevYVvQdBdXbAYjym8g58TeQ3EUxy66i1zgxfeSlTBtxCWWH8vF2Cer3391QRwjB5MgLCPcew3tb7uONlNs4K+4aFo66tVfpLV4uKu5eZOCZFSb+tdrEPYucTijqegagjKVDnJI9NkwNkBmSyZUByYNtjsIw4KKIaXjpXHhgx3vckPIir0y9lUDnEwsQq9QCrxA1XiFqoqa1LU7s22wlb5OVhko74y8y4Opzeo+hJ42cEEL81MV2pJSySzMQIcTlwKvAxVLKnzps/woo7agf0UnkxIdSStcO+5XIidMYKR18+tl8goOmMmvW3wfbHIVhQl7eF/yS9nfGjP49EybciZSS/ft/YPuOFzGZ6oiLu5TkpNtOGFlxGIuliZWrrqO5uYIli9/Fw2PEAH2Dk6Ks9g0zHFLy4hozeRV2Hr/YCV+3oyclvxR+yWfpT3DH3HeI9Bk3IDaZrE28nnIbxXWZBHlEE+Y1mnCvUYR5jybIPQq1qmtpHg7poKB6G9uLvmd36TosdhM+LqFMiljKxPAlwyq9YihhsbXy1a5/suXAV4zwSWLZ5Cfxcg7sVZvVDW0RFDaH5J7FTgR7DvrkWhlLhxnmZsnPb7TQ4GLk2cDnWbfoCUVMUmHASK/dx5+2vImzRs8zk65ljFdkt86v3m8j41sz0g7jlugJih8ymkj9J4jZFwghrgeeBZZKKVOP2fc3YKGUcmqHbZ8AzVLK6w6LBgEJUsqc9v2LgC8A765oTijCQ0OLurpcvvv+CmbOeIyoqPMG2xyFYURa2lPk5n3G+OTbKSlNoaoqA1/fMUydch8+PqNO3UA7TU1l/LDiajQaZ5YsfheDoWfl9voQRcRtmLFmr5VPt1r43TQd8xKOf+h/fv0ybHYLd5/zyYCmJJisTWzIf58DtXs4aMyi1doAgEalI9gzlnCv0YR5jSbMaxT+bhFHiSxWNRaxveg7thevoL61AoPGlaTQ+UyKWEqkT+KwTa0YauwoXsnnGX9HrdJy+YS/MSZ4zqlPOgkVhxw8u6JtKnfvYgMBHoPqoFDG0mFGxjcmKnLtfDHmA9QeVl6f0SWtfQWFPqOgoYzb016n2nSIKLcgFoVOYGHIhJNGUnSktcFB+ldm6sscjJikIX6eDtUAlO4+BUPXOSGEuAP4K20OiO2d7B8BZAK30VbJYwFt1T2OrdZhBa7m12odWzrqVJzChkiUm8CQIWPnq+ze/SaXXboaZ+feiWspKHQHu93KmrW3UFWVgV7nwfjxtxMTc2GnKRynorp6N6tW34Sv7ygWzH8NdR+Gl/cAZUI9jCiutfP370yMDVVz29n64x7aS4zZ/Gv977go8V5mRV8+SFa25XHXNpdw0JjFQWMWxcZMSozZWOytAOg1zoR6JhDsEUuxcS9FdXsQqIgLmMqkiKWMDp6DTm0YNPsVTkx1YzHvbb2P0vocXHSeOGndcNZ54Kxzx0nnjrPWHWfd4ZcHTh0+e7uEHHddy4wOnlnZilYtuHexAT+3QXNQKGPpMKJqn41tn5pRJdbwsO15Hkz8LRdFTBtssxSGIYcszawpzWBlyQ52GwsBGO8TxcKQCZwTnIS77uRl7B12SfZ6Cwe22/AKUZF8oR4n99PL0TuQzgkJ2ADzMbtGSSmL2485B/gXEAOUAA9JKT/p0IYv8G9gIW0lRT8F7uxqpQ7lJjB0aGoq4+tvLiUkZBrz5j432OYoDENMJiP7969g5MglGAzHRtp2j8LC1WzcdD8jRy5h5ozHBnNlV5lQDxPMVsnj37ZissIjFzrhZjj+0n+e/iRbi77jb0tW46w7eZrSQOOQdqoaizhozKS4LpOD9VmU1efh6xrOpIjzGB+2CI9eVoRQGBhsdgsp+z6lpvkgrZYGWiyHaLE2tv20NGCyNiI5fq7pqvdi4ahbmRJ54VG6FQdr7Ty70oSzTnDPYgM+roMysVbG0mGCzSLZ+J9WhFrybPiz+Lq48fasu1D3YLFCQaEvKWmuYVVpOqtKtnOgqQqtSs0M/1EsDJ3ArIDR6NUnTpEsy7Kxe4UZtRaSzzfgO2LQxIaHrnNiKKDcBIYO69b/kYqKbVx4wRe4uPQuV1VBYSiwa/eb7Nz5KslJf2DcuBsGywxlQj1MeDfFTEqejT8tNJAQfPykw2xr5W8/LGBs8DyunPTYIFjYfaSUSsrGGYhDOjBZm9ocF9YGWiwNNJmN/FL4OftrMgh0j+aCcXcRF/DrSvWBGjvPrTLhZmiLoPB0HvAHRWUsHSZkrTNTuNVGwdTNfNi4gvdm/4l4z7DBNktB4QhSSnIPlbCiZDurSzOoNTfgqjFwVnAii0MnMt4nClUnzrTGGgfpX5poqpXEztYSPV07GPfYvq3WoaDQHxQXb6CkZCMTJvxRcUwonDGMG3sDDQ1FZOz8N+7uEURGzh9skxTOULYX2tiUZ2PROG2njgmAnSWrMduamTbi4gG2rucojokzE5VQHUnl8OmwfXzYQvaUree7PS/yesptxAfM4PxxdxHoPpJIXzV/XGDgX6tM/HOliXsWO+HhpPx9KPQthyrsFG6z4ZLQygeNK7hi5GzFMaEw5BBCEO8ZRrxnGHeOvoBt1fmsKt3OurKdfFu8BT+DB2cFjeOc4CTGeY84EvXj5qtixjVO7FlpJm+jFWOpg6SlenRDfCxVIicUBhSrtZVvvr0ErdaVped9iKqLqu0KCqcDdruFNWtuobYum3PPfRM/3zEDbYKy2neGU9vk4NGvW/F3V3HfeQY0qs4v+Qs/XY3Z2sK98z9THvoVhjSH00LW5LyBxdbK1BEXs3DULbjqvcirsPPCGhN+boK7F3WevtRPKGPpGY7DIUl9x4SpycF7CW9QJw/x2Vn346zRD7ZpCgpdwmS3sKkik9Wl6fxSlYPZYcVH785ZQeM4OziRZJ8o1EKFlJKidBtZP1owuAnGX6THM2jA0jy6PZYqCVUKA8ru3W/S3FzB1Cn3K44JhTMOtVrHvHnP4eTky/r1d9HUVD7YJimcQTgckv/8bMbugJvm6k/omCitz6O4bi/TRlysOCYUhjwatY65sct44NxvmD7yUtIKv+TJVRewPvddRvrZuf0cA1UNkudWmig1OgbbXIUzhAPbbDRUOqgdl092axH3jL1EcUwonFYY1DrmhyTzz8nXs2bh4zw54WoSvUfw7cEt3PL/7N13eFzVtffx75qqZknuttzkgm0wuGAbN4yNwYROQoBAIAFSXlJJSEKSm0puCDflkhByCSSE0AIEktBMMcU0g8HGuHfLFfeqZknTzn7/mLGR5SZhSSNpfp/nmWdmzj5nztozo62ZNbvMuovzXvoZ/7PwCd7ftZqeI3yM/1wWOHj34RqWzYhQU9Ey21P1nJBms7d0DdOmXUX/fuczYcIt6Q5HpMmUlq7lhRevIy+3G+eddz/BYG5znVq/9rVh0xZEeWZejC+eEWLcgCMnd/8z/9fMXv80P7/gJXJDBc0Yocjx216+jmmL72DZtpl0yOnBhafcSIAzuffNCDVROGtIgItHhMgKNmlzp7a0Dasq9Xjrb9Xk9kzwX3m3MqbLQG4/LW1zRYk0qup4hHd2LGfGlgXM3L6MmkSUwlAuZ3YfypntR5C9sBdbl3qYD3oODdB/bJCcwibrr6A5J6Rlcs4xe/b/EAzmMHLkt9IdjkiTKizsx+RJv+XVGd9kxmvf4vQJvyQvr3u6w5JWrGR7gmnzY4zp52ds/yP/647Gq/lg4wsM63m2EhPSKnXN78uXJvyRVdtn88zi3/PQ7B9Q3HEYX5lyM3PW9OflJXHmrE1wxWkhRvf1q3eQNIhzjiUvRcHgue7PYpVw8ymfTndYIo0mOxDm7KLhnF00nJp4lFk7ljNj60Je2jSPpza8S0Ewhymnj+LU7WP5cFEBHy6IUzQkwIDxQfI6pn9QhZIT0izWlYOLOwAAIABJREFUrn2e7dvnMW7sT8jKap/ucESaXFHRWE6f8N+8+96tPPPs5Ywa+W0GDrwU0/Jk0kBVEce9b0bokGtcMz581C9jCza9Qk28slVNhClyOAO7juG7XR5lzvppvLj0Lu6ddQ0jen6Cr511I88tKOSvb0SYucrHZ8eG6d50v/pJG7NlWYKdaxMETtvJjLK53DTkk3TL1udSaZuyAiGmFA1jStEwIokY7+5YwWtbF/La9rk8FXyL9gMKuWTfBXjLB7F5SYxugwMMGBekoFvalh7VsA5pepFIGU8/cynt2vXivHP/ri9nklEqK7cw691fsnXrbLp1G8X4cT+jXbueTXU6dUVuY5xz/PWNCB+sT/CDC7Lo3+XoHxjufP06qmLl/GDqf/SLsrQZNbF9vL7qId5c/TAJL86EfleS5fsSzy/yE43DOScHuXBYkHDjDfVQW9oGRasdb/61inA+/LrodxSGc3nojO8Q8KXvi5hIOsS9BIv3ruetbUt5a/sSdpZWMnb3eMbtHU8oESa7d4RhZ7SjY6/jnh9Qwzqk5Zk3/y4ikTKmnn23EhOScfLyiph69p9ZXfI0c+f+gWenXcGpI77J4MGf0d+DHNOskjjvr0vwyVODx0xMbC0rYf2eRVx8yneUmJA2JSuYy3lDvsr4fpcxfdk9zFzzKOHg05w37Gts2XMxLy6KMXtNnCvHhBjRR0M95PCWvxYlVgPLR73Nzt1l/Pa065WYkIwU8PkZ0bE/Izr251tDLmZj5U7e2r6EVzY9QXZJN8ZsHs97/4hS0WELnUfFGDe0JznBrGaJTZ+MpUnt3LWEVav+w+DBV9Khw8B0hyOSFmbGwBM+xSUXP0HXriOZ8/7vmD79S5SVb0h3aNKCbS/zePTdKAO7+Th/6LF/vXhv3VP4fUFG9bmgGaITaX4F2Z35zMifcvPUx+nXcTivrvotW6su45KR88kOwZ9fi/DHVyJsL2+Zs9BL+uxan2DTojj5w6p5ePd0Lu97Oie375PusERahN55nbmm/5n8edJX+NnnptLu8k2sHbQAykPUvNydRx9c02yxKDkhTcbz4rz33m1kZ3dixPCvpjsckbTLze3GWVPuZMKEX1BatoZp065kydKH8LxEukOTFiaeSA7n8PvgS2eE8R1h2dD9ooka5m58jqE9ziIvrPHT0rZ1y+/PlybcyVcn/oXcUCGvl9xIu3b/jyknbaVke4KfP1XNM/OiROOZM3RZjiwRcyyeHiG70Lg39DAdw+342uDz0x2WSItUEMrlvL6n8s1LJ3DptzrT7vS9DD4lv9nOr+SENJmVK//Nnj0rOG3095pzKUWRFs3MGND/Ii65+N8UFY3jgw/u4MXp11NaujbdoUkL8vS8GBt2e1x3epgOecf+V71o06tUxyo0EaZklBO6jObbU/7B1aN/RXVsL3M3X8HgXr/ixKIqpi2I8dryWLpDlBagZFaMqr2OncNWsLRyA9875VLygtnpDkukxQuFApwxsSenj+nVbOdUckKaRFXVTuYv+DNF3cfSp8/Z6Q5HpMXJyenMmZNvZ+LE26io2MS0565i0eL78Dx9mM50SzfHmb44xqRBAU4trt/UUO+ue5LOeb3p32lkE0cn0rL4zMfI3ufxw3Oe5OJTbmJr+TtsLD+Pkf3/ycji0nSHJ2lWsdNjzXsxOp7ocdfex5nQ5STO6j4s3WGJyBEoOSFN4v25vyeRiDJmzA81MZXIEZgZ/fqeyyUX/4tevSYzf/5dPP/CtVRUbEp3aJIm63cluPu1CD3aG1eMCR1z/4qa3Ty35E+s272AsX0vVXsrGSvoDzN54Of40bnPMumEq1m756+s2vFGusOSNHLOseiFCIEwPNvpGRJ4/GDop9VOirRgWq1DGt2WLbNZv/4lhg27gfz83ukOR6TFy87uyORJv2HDhnNYtPg+wuGCdIckabCtzOOOl2vICxvfPieLcODIH6B3VX7IG6seZs6GZ0l4MYb1mMq4vp9uxmhFWqbcUAEXD72J0/t/hoLszukOR9LESzgWvRCldItHeOJOXt4zl2+ceCFFOR3THZqIHIWSE9KoEokos+f8mnbtenHKydelOxyRVqVPn7Po3XuKftXJQHv2efx+eg0G3PSJLNrnHr5j4+bSlby28gEWbHoFn8/P6N4XMnng5+nSTrPOi9TWIbco3SFImsQjjg+eirBrXYK+E3zcXPUA/dt155r+Z6Y7NBE5BiUnpFEtWfog5eUbOPvsu/D7w+kOR6TVacuJia2lHpv3egzv4ydwjNUnMklljeMPL9VQHXXcfH4WXQsOTkw45yjZOZfXVt7Pyh3vEQ7kMnng55g04LPk65dhkYy0u6aCjlnt0h1Gi1NT6fH+vyJUbPcYen6I/wReYPuaUm4bdS0Bnz/d4YnIMSg5IY2mvOJDFi26j+I+U+lRNC7d4YhIC/PO6uREjwXZxsRBAc4YFKDDEXoIZIqamOOPL9ewq8Jx0yey6N3xow/PnvNYsuV1Zqx8gA/3LqVduCMXnPxNxve9jOyQvpSIZKpVe7bwyL+WUT1oK+cMPIVJ3U4m6NNH+srdHnOeqCG6zzHysjBzw/N5bMGbfKrPOIZ16Jvu8ESkHtSSSaPYW7qGd965Bb8/yOjR30t3OCLSAl06MsjAbj7eWBHn+QUxnl8YY3gvP5NPDHBikR9fG+41cjixhOOuGTVs2O3xtbPCDOyWTEzEvRhzNzzPG6seYkflejrm9uSyET9idJ+LCKpHmkjGC+zJZVTZaSTe83hhzRv8rvuTnNN7BJf0HsOA/MwczrJ3c4K5/6oB4MTLPH674wHe3LaEYR36cuNJF6U5OhGpLyUn5LhUV+9hwcJ7WL36SYLBXMaP+xk5OepmLCKH8vmMob0CDO0VYGeFx1sr48xcFWP+xgRd8o1Jg4JMOCFAXlbbT1J4nuNvb0ZYvsXj+okhhvcO4JxjwaaXeX7J/7GnajM9Cwfz+TG/ZmiPs/CZuiOLSFK/AQV0u8Fj2YwIZ62cyviKcTy79xkeW/NbTmrfi4t7j+UTPUbQLpiT7lCbxfbVceY9HSErz4hOXsMXVvyT6niEbw+5hKv6TcJvmd1DT6Q1MedcumNoNmZWDKxbt24dxcXF9T5u4aJ7iUUr6dptJF27jCCk7rQkEhGWLX+MxYvvIx6PMHjQ5Qwd+mWysgrTHZpIJmuWb/Ufty2dvf5p3l33JD0LBtOjcBA9CgfTKa8/iz8M8PryGCU7PIJ+GN03wOQTA/Tt5GuTc3A453h4VpS3Vsa54rQQ55wcZM3OD3h28R18uHcp3QtO4MKTb2Rw1/Ftsv4irUCLbktr27U+wdJXIlTucsS6l/F8l2nMjy8n7AsypWgYl/Qew6kd++Nro1/QNy6IsWR6lJwujlcHPsv0PXM4uX0fbhn+WYrbdU13eCKZrsFtqXpO1ENp6Vo2bnyNpcsexsxH+/YD6dZ1JF27jaJrlxGEw/npDrHZOOdYv/5lPph3J/v2baVXz0mMHPktCgqK0x2aiLRw4UAOQX8W8zZNZ9a6fwPgMz9d2/Wld9fBDO45ms27R/DB+kJmlcTp3dHH5MEBRvQJ0K4N9aZ46oMYb62Mc/7QIMN6f8h9s+5k6da3KMzuylWjfsHI3uerp4SI1EunYj8Tv5DN+g/irH67gE9tv4Zrh1Uzq8tbvLBtDi9umkuPnI5c1HsM5/cc2WaW0nTOUfJOjFUzY/iK9vHbTnezt7Scb5x4Idf0P1OTX4q0Uuo5UU/xeA07dy1m+7YP2L59Hjt2LsLzooDRvv0JdOs2kq5dR9K1y6lttvfAzp2LeH/u79m5cxHt2w9k9Kib6N59TLrDEpGPtIpf+5xz7Nm3mU1lK9lcuoLNpSvZVLqCippdqfIcQvYZqmsuoCrSFXD06eRnSJGfIT389O/iI+BvncmKl5fEeGJOlLH947TL+xNz1j9NOJDDWYOvZ+KAqwj5s9Idooi0kra0rsg+x4rXo2xaHCecZwyY7GNZ4RKmfTib93etBuCkwl6c1X04ZxUNo2dup+M+Zzp4nmPJS1E+XBBnR9F67i68j0GFPbhlxGfpn9893eGJyEca3JYqOfExJRIRdu5awvbt89i+7QN27FxEIpGciKd94QC6dhtFUfcxdOs2mmArH/NXWbmFefP+j3Xrp5Od3YkRw79G//4X4VNWWqSlaZUfqPcrr9nF5tKPEhYf7l3BzvI84vEx4E0gGhuEw0c4AIO7JxMVQ3r46ZJvrWL4wzurY9w/M0qPDhuocTeQcBEm9LucqSd+ibxw+3SHJyIfadVt6d7NCZa+HKVsm0eHXj6GTA1RkVfKq1sWMGPrQpaVbgRgUEFPzi4axlndh9M7r3XMF5aIOeY9HWFHSYL3u85ieqfpfGnwJ7huwFnqLSHS8ig5cTRN9U8AIJGIsXv3UrZt/yCVrFhAPF6Dzxegc+dhFBWNpUfRODp0GIy1knF/0WglS5bcz9Jlj2DmY8iQz3HykGtbfbJFpA1r1R+oD6cyspelW99kyZY3WL5tMZHoyZh3Os4bT3U02UutU55xUipRcWJ3PznhlpeomLc+wt2vRQmFFhPKuonhPSdx/snfoHNe73SHJiKHavVtqXOODxfGWflGlGgN9BkRoOikAGawK1rG3N2rmb17BSvLN+PMo1deZ8Z3G8zpXU+kV7tOmM/w+SEQAvMd+elIOI+y6D72RiqpikfondeZglBu49bFc0SroabCY+H0Gsq3Op7vPo2y4k3cMuKzDCzo0ajnE5FG0/aTE5b8Zn8r8EUgF3gbuME5t6EexxbTTB+oE4koO3YsYMuW99iy9T327FkBQDhcSPfuYygqGktR0Thyc7o0aRz1VVNTSmnZGspK11Fatpay0rXs3rOcaLSCfv3O59QR3yA3t1u6wxSRo2v1H6iPJhKvYsW2WSze8jrLts6kKpKP804nyz+V8qoBxBLJD97dCowu7Xx0zk9dtzM65/volGfHPRzEOUdNDBIeJFzyfsIDz4G3/9pB3EtQXr2XsupdbNhdxhvLBmP+Ek7q9Xc+OeyrFHcc2kjPiog0gTbTlsaqHatmRlk/Lw4f8yO/CyRIBOLE/TGi/gg1vhqqrJpK20cl+6jx1xDxRYj6IsR8cdqFw3TLLaSoXXt6tutIn/zOdMjJxR/w4fOTvATA5zfiEUdNpSOyzxGpTF32pbZVelRXOmJVDlzyJYlbnP/0eoIJI3vyhYFTCfo0fZ5IC5YRyYkfAjcA5wKbgd8DY4HhzjnvGMcWk4YP1ADV1bvZunX2gWRFdXVybHVhYX+Kuo+le/cxZGd3xOcP4fcF8ftD+Hwh/P5Q6nbwuLstO+eoqdlzIPmQvE4mI2pq9hzYLxDIobCwH4UF/Rg06HI6dRpyXOcVkWbTZj5QH0vci1Gy430Wb3mdJVvfpLx6L84bSrvQxTivP1WRAvZF2pHwgh/FjSMnXEW77H3kZ1WTn11Nfk4NuaEEnsshnsgmlsgmlggRjYeIxILUxAJUx3xUR4yqqGNfFD7Ov81gYDPXTdzGacUTW8UQFJEM1+ba0n17PapLHc45PA9IJVTxktfOQXnNPpaXbmLF3k1s3rcHvxcg7IWTl0QWeeSQ53LJdlmEE1kEEyECiSAW82ON9JQ5HNFQDfuClez1lVLqL6MyUEFloIKKYAW5neHbY85jcGGvRjmfiDSpjEhOrAd+45y7O3W/ENgGnOOce+sYxxaT5g/UkEwS7C1dnUxUbHmP7dvnpSbXPDrfgaRF8toaOJt7PFZFJFp24H4wmHcgCVFQ2I/Cgr4UFvYnJ6erPjyLtE5t7gN1fXjOY+OexclExZY3Kavejuc8El6ChFeI5xXheT1SlyJc6rZzR5q82MOsAqwCs3LMKjCrwO+rIuivxu+rJpoox7kY4IElAI/sYA554XzaZRWQFy4kP6uQdlntKcjqwIg+XckN6xc+kVYiI9vS2nbVlLFx3y4KQ7m0D+WRH8rBf4Rhyc45EjGIRxxeguQl7qiKxthQtpMPK3azqXw3WytL2V1VAZ6PgAuQbWGqrTqVgKikIlhONBChe257euZ2pEdOJ3rmdqJXbvK6KKcDWf5QMz8TInIc2nZywswKgFLgNOfc+7W2LwX+4py7s9a2QqDuJ8+ewMyW9k8gHq9m166lRKOVeF6URCJKwovhpa4TiUjydiJGwovipa6P0VHkEH5/mIKC4gPJiJzszkpCiLQtjf4H3Zra0sNxzuHw8JyH58WT1y6B5xLsiyTYWQGVNXGCgQh+XzV+3z58VkXMqyYaryGa+Og6lqghGq8m7sVol9WRDjlFdMgpon1Od9rndCOgD80ibYXa0iYSTcRZW7mNFaWbWF2+mZAvSM/cjgeSEF2z2x8xCSIirU6D29LW9jNOfuq6tM720lpl+30b+HmTR9QIAoFsunUble4wREQOp9W0pYdjZhh+fOYHX/CgsrwwdK37n0NEpGm06ra0sYT8AQYX9GRwQc90hyIiLVBrS06Up64L6mwvrFW23x3AA3W29QRmNn5YIiJtltpSEZHjp7ZUROQYWlVywjlXZmYbgFHAXDjQTW4AsKDOvqXU6WGhIQwiIg2jtlRE5PipLRURObZWlZxIuQe42cxeA7YAvwVWklxS9Fj8AJs2bWq66ERE0qRv377FwCbnXLyJT6W2VETaLLWlIiLH7+O0pa1qQkwAM/MBvwK+COSSTErc4JxbX49jT0fd50Skbetbn/bweKgtFZEMoLZUROT4NagtbXXJieNhZmFgNLAVSDTg0P1jAicCmZTezsR6Z2KdITPr3Vbr3OS/9qktbbBMrHcm1hlU77ZU75bclkLbfM6PJRPrDJlZ70ysM7TNejeoLW2Nwzo+NudchPoN/zhIrTGBm5o6i96SZGK9M7HOkJn1zsQ6Nxa1pQ2TifXOxDqD6k2G1ft4fdy2FDLzOc/EOkNm1jsT6wyZW+/atJCwiIiIiIiIiKSVkhMiIiIiIiIiklZKToiIiIiIiIhIWik5UT+lwC+osz51BsjEemdinSEz652JdU63TH3OM7HemVhnUL0zrd7plInPeSbWGTKz3plYZ8jceh+QUat1iIiIiIiIiEjLo54TIiIiIiIiIpJWSk6IiIiIiIiISFopOSEiIiIiIiIiaaXkhIiINDkz85nZbWa23cwqzWy6mfVJd1xNycxuMbNEqr77L4+lO67GZmZXmtlMMys3s0MmsjKzs81soZlVmdkqM7siHXE2pqPV2cyKzcyZ2b46r31BuuJtDGb2GzNbmqrzFjO7z8w61tmnzb3WLY3aUrWlbenvKxPbUlB7ejRKToiISHP4PnAVcAbQDdgITDOztv5/aKZzLq/W5ap0B9QE9gJ/Br5dt8DMioFngTuBQuA7wANmNqYZ42sKR6xzLUPqvPZlzRRbU0kA1wAdgeFAL+CB/YVt+LVuadSWqi1tS39fmdiWgtrTI9JqHSIi0uTMbD3wG+fc3an7hcA24Bzn3FvpjK2pmNktwGTn3OQ0h9IszGwy8LpzzmptuwU4zzk3pta2x4F9zrkvNHuQjewIdS4G1gF9nXPr0xJYMzCzC4FHnXP5qfu30IZf65ZCbWnbp7b0wLZiMqAtBbWntbX1LKuIiKRZqgtmH2Du/m3OuVJgDclfDNqyUWa208w2mNmjZtY33QE1s2HUet1T5tL2X3eAd8xsl5nNMrNPpTuYJnAWsLDW/Ux+rZuF2lK1pXW2ZcrfV1tvS0Ht6QFKToiISFPLT12X1tleWqusLfo3MAToAowD4sCrZpaX1qiaVz6Z97rvAsYDfUl21f0/4DEzOz+tUTWi1NjnLwHfqrU5E1/r5qa2VG1pbW39dW/zbSmoPa1LyQkREWlq5anrupNYFdYqa3Occ0uccxtc0hbgi0B3kh+2MkU5mfe6Vzrn3nXORZ1z1c65R4GHSY4vbvXM7ErgL8DFzrl5tYoy7rVOA7Wlaktra+uve5tuS0Ht6eEoOSEiIk0qNXnVBmDU/m2pcdIDgAXpiitNHGDH3KvtWEit1z1lFHrdWyUz+yLJyesudM69XqdYr3UTU1t6kDbxN9UA+vtKajOvu9rTw1NyQkREmsM9wM1mNjDVFfe3wErg7fSG1XTM7DNm1jl1uwvwV2AnMCutgTUyM/ObWRYQSt3PSl18wIPAUDO73syCZnYBcBHJX4paraPV2cwmmtlJZhYws5CZfQb4HNCqlz40sxuB35CcePGdw+zSJl/rFkhtqdrSNvP3lYltKag9PRqt1iEiIk0u9eHqVyS74+aS/CB9Q1uegdvMniU5PjqX5HJpbwE/dc6VpDWwRmZm1wH3H6boTOfcG2Z2NvB74ARgE/AT59zjzRhioztanUn+iv1fJJd5jACrgNudc/9qtgCbgJk5kmP9I3WKTnLObUzt0+Ze65ZGbanaUtrQ31cmtqWg9vRolJwQERERERERkbTSsA4RERERERERSSslJ0REREREREQkrZScEBEREREREZG0UnJCRERERERERNJKyQkRERERERERSSslJ0REREREREQkrZScEBERkY/FzN4ws7+lO476MrPrzCye7jhERGpTWyqSpOSEiIiIZCQz+4mZrU93HCIirZnaUmksSk6IiIhIq2JmoXTHICLS2qktlZZGyQkRERE5Lmb2UzPbZmZ7zOwhM8tLbTcz+56ZrTWzqJmtMbNv1zl2vZn9pM62v5nZG7Xuv2Fm95nZL81sK7CxHjH5UvvvMLNKM3scaF+r/Drgl0AfM3Opyy3H8TSIiBwXtaWS6QLpDkBERERatcuA+4HJQG/gn8AG4KfA10h+aP0W8DpwFnCHmVU45+5r4HmuAB5JPYa/Hvt/E/hOKoZ3gU8CP69V/jgwGLgaGJ3aVtnAmEREGovaUsl4Sk6IiIjI8djgnLspdXtF6le1s0l+oP4h8Cfn3F9T5avNbBDwY6ChH6i3Al9zznn13P9m4A7n3IOp+781s9NIfrDGOVdtZpVAwjm3rYGxiIg0NrWlkvE0rENERESOx8I697cAXc0sH+gJvFWn/E2g2MxyGnieD+r7YTp17h7ArDpFbzfwnCIizUVtqWQ8JSdERETkeETr3Hc07POFB1idbcHD7LevIUGJiLQyaksl4yk5ISIiIo3OOVcObALOqFM0CVjnnKtK3d8BFNXZZ0QjnHszML5O0YQ696PUb8y1iEhaqC2VTKI5J0RERKSp/A9wu5mtBt4ApgBfBb5ea59Xga+Z2VMkJ3/7CtAH2HOc574d+KWZrQDeAy4mOX67tnVANzMbB6wGqmp90BcRaSnUlkpGUM8JERERaSp3Az8DfgQsA34A/LDO7PK/AZ4nOeP7TKAM+FcjnPuPwJ3AH4AFwDjgv+vs83TqXM8DO4HvN8J5RUQam9pSyQjmnEt3DCIiIiIiIiKSwdRzQkRERERERETSSskJ+djM7BYzK0l3HHWZ2WQzW2JmMTN7I93xHE5Lfe6OxMzeNrN7jrHPranxiCIiTcrMJppZ5VEuE9Mdo4hIS6e2VFoaTYgpbdHdwPvAeWi5pIOkkjWTDlM0zjn33lEOvRiIN0lQIiINNxcYfpTyzc0ViIhIK6a2VFoUJSekLToBuM0592G6A2mhHgW+W2fb7sPtaGYh51zUOXe8Mz2LiDQa51w10Gp6n4mItERqS6Wl0bAOqRczyzKzu82szMz2mtndQLjOPqea2YtmtiPVFex9Mzu3VvktZrbyMI/9dzObUc84BpnZ87W6m00zswGpsslm5kius/yQmTkzu+4Yj/dLM3un1v0zU8fdWmvbr8zs3Vr3B5jZf8ysNPVcvGxmp9R53JGp7ZVmttPMnjSzPkeJo0Nq6MTrZpZfn+fiOFQ757bVucRScbxtZn81s9vMbCuwttb2A8M6zCw7tV+Zme0xs7uAUJ06jTazl1L1rzCzOWZ2Tq3yW81sad3gzOwhM3upqSovIiIiIiItj5ITUl//A3wa+DzJJYT2cfDaygD5JJcvOhM4FXgJeNbMBqbK/wb0N7MDwwrMrB1wBfDXYwVgZtnAy0AWyaEJk4A8YLqZhYBZQPfU7t9I3X78GA/7OjDazPJS96eQXAJpSq19pgCvpWLoCrwN7AAmAmOBlcAbZtY5tc9JwJvAu8Co1PEJ4BUzyzpMvXoD7wBbgHOdc+VHqP+xxgVWmtmLx6hvfVwFFKTiPu8I+/wWuAT4HDAeiJJcT7u2diR7aUwCRgIzgAPJJOBeYLCZTahVx0LgMurxfhARERERkbZDS4nKMZlZLslu/990zt1ba/tcoNA5N+Aoxy4EnnDO/Sp1/1mg3Dl3Ter+DcCtQA/nXPQYcXwR+BPQ2zm3K7WtK7AeuME591BqmwM+55z7Rz3qlgWUApc6515I9aJ4CrgN6AAYsIdk0mCGmd2Suj221mMYyS5xf3LO3WFmDwBZzrkra+0TBvYCn3XOPZ16nGuAS4EXgSeBbznnvKPEmg30OEaVqp1zRxwfmJpzYgIQqbV5lnPunFT520BH4CRXq3FIbV/inPtKqmfHTuArzrn7a+0zH8h2zg0+yvmXAg85536Tuv8CsMM5d13q/teBnwK99vfmEBERERGRtk9zTkh99Cc5hGNWne1vAxfuv5PqOfALkr+4dyP5/soCag9n+AvwbzP7pnNuL/Bl4MFjJSZShgDL9icmAJxz21NDRYY0uFbJ42tSQzammNlbwGjgcuB64AySyYkEyZ4NpMpHmlllnYfKJjnXxf59Bhxmn6xa+wB0Bt4C7nXO3VyPWBtrXOBTwI9q3a+uUz63dmLiMAaQHMJR9/3wDnD2/jtm1oWP3g9dSb4fsjn0/fComX3LOVcGfAl4QIkJEREREZHMouSENKYHgN7A94F1JL/0/pOD5yJ4keSQiM+lkgEjgaubN8xDvEayB8MMYK1zbouZvUbyS7UB7zrnalL7+lL7feMwj1NWa5+HgV8fZp/aE0/VDVKzAAAgAElEQVSWAouAT5rZH51zm44WpCWXczrWsI2ZzrkjDcXYr9w5d7QkR2OtcPIwySTV90j2bqkG/s3B74fnSPYoudrM5gDDSA7rEBERERGRDKLkhNTHGpJzCowHak9gOKHOfmcA33fOPQsHhoP0A5bs38E555nZvSR7TAwC3nLOHTJJ5hEsBb5iZp3qDOsYBNze4Fp95HWSv/BfTjLxAMmExU9JJieerLXvXOA6YFOthEVdc4GhwJpj9ECIkUyKPA68aWZTnHMbjrL/sZZ7gkN7QTSFEpKxjyc538Z+4+vsdwZwo3NuGhyYX6SYZD0AcM4lzOxvJN8Pw4DXnXNrmi50ERERERFpiTQhphyTc24fcA9wq5ldnFox47ckkwK1rST5C/gpZjYceIzkyhl13QcMJtmFvyETHz5Kcq6Dxy25MshIkj0zNnPsiS+PZjZQRXJyx9dS294ATiH5hfm1Wvv+H8k6PZOaoLLYzE5Preix/8v5bcCJwD/M7DQz62vJVUD+aGb9ap84NXzhCpJf2N+sW15n32rnXMkxLk2+HnVqws57gdvM7MLU++F2ksM9alsJXGNmJ5vZCJKvlR3mIf9G8rm+Dk2EKSIiIiKSkZSckPr6IfA0ya76c4BC4K46+1xP8j01J7XvdOD9ug/knNtKsjt/Jclu/vWSmnPhHJKTOb5FckWMfSQnqKzPnBVHetwYyfkS/CR7UZCaD2NR6vHn1Np3O8nVSnaR7FGxEniE5DwKW1P7LCfZiyCP5Ioly0h+mc8mOZSj7vnjwGdJzuHxppmdUHefFuhm4HmSCaPZQC7JBFZt15Kcq+R9ks/Vs8D8ug+UGs7yIlBOcj4MERERERHJMFqtQ9IiNb/AO865m9Idi6Sfmc0DZtRnYlAREREREWl7NOeENCsz60RyhY9TgSuPsbu0cakVXi4hOazjU2kOR0RERERE0kTJCWluO0muznCjc25t7QIzexGYeITj6rMKxSHM7B7gmiMUb3DOfawlSOX4mVmA5Mote4BvHGMyUBERERERacM0rENaDDPrQXJehsOp/jiTPZpZFyD/CMUxfSEWERERERFJv4xKTqR+qe1JchnIeLrjEREREREREZHMG9bRE1i3bt26dMchItIUDrdUq4iIiIhIi6elREVEREREREQkrZScEBEREREREZG0avbkhJlNMrOZZlZpZnvM7JlaZWeb2UIzqzKzVWZ2RZ1jO5rZ42ZWnjr2HjMLN3cdRERERERERKTxNGtywszOAJ4F7gE6A92AX6XKilNldwKFwHeAB8xsTK2HeATIA/oAJwOjgNubJ3oRERERERERaQrNulqHmc0C3nHO3XyYsluA85xzY2ptexzY55z7Qip5sQ44yTm3PFV+HvBvoKNzrqYe5y8mNSFmcXHx8VZHRKSl0YSYIiIiItIqNVvPCTPLBcakbs81s91m9q6ZnZXaZRgwt85hc4Hhtcqr9icmapXnAAMPc75CMyuufSG5WoeIiIiIiIiItCDNuZRoe5LJkGuA84ElwHXANDM7GcgHltU5pjS1ndR16WHKqbVPbd8Gfn7cUYuIiIiIiIhIk2rOOScqUtd/d87Nd87FnHP3khyq8QmgHCioc0xhajtHKafWPrXdAfStc5l4XDUQERERERERkUbXbD0nnHNlZrYWqDvJxf77C4Fz65SNAhbUKs81s8HOuRW1yquBVYc5Xyl1elqYaTi2iIiIiIiISEvT3EuJ3gV8wcxOMTO/mV0PFAMvAg8CQ83sejMLmtkFwEXAXwCcc+uBl4DfmVl7MysCfgncX5/JMEVERERERESkZWrOOScA/kByKdCXUtdLgQtSiQfM7GLg98CfgU3A9c652bWOvyZVtgFIAE8A322u4EVERERERESk8TXrUqLppqVERaSN09g1EREREWmVmntYh4iIiIiIiIjIQZScEBEREREREZG0UnJCRERERERERNJKyQkRERERERERSSslJ0REREREREQkrZScEBEREREREZG0UnJCRERERERERNJKyQkRERERERERSSslJ0REREREREQkrZScEBEREREREZG0UnJCRERERERERNJKyQkRERERERERSSslJ0REREREREQkrZScEBEREREREZG0UnJCRERERERERNJKyQkRERERERERSSslJ6TVcOWOql9Uk1iXSHcoIiIiIiIi0oiUnJBWI740gVfiEXkwivNcusMRERERERGRRqLkhLQa3upkjwlvjUf8XfWeEBERERERaSuUnJBWI7HGwzfIh6/YR/SJKC6i3hMiIiIiIiJtgZIT0iq4qMPb4OE/wU/4mhBujyP2QizdYUk9uYQjsS6Bc0ooiYiIiIjIoZSckFbBW+9BAvwDfPgH+fGP9hN9Loa3x0t3aHIMLuKouSNC9c9qiM+MpzscERERERFpgZSckFYhUZJMQvgG+AEIXxkCD6L/Uu+JlsxVOKp/XUNiYQLrZEQei+Iq1HtCREREREQOpuSEtAqJkgTW2fAVGAC+Lj6C5waJvx0nsVaTY7ZE3m6Pqlur8TZ4ZH0zTNZ3sqAaIo9F0x2aiIiIiIi0MGlLTpjZU2bmzGxyrW1nm9lCM6sys1VmdkWdYzqa2eNmVm5me8zsHjMLN3vw0uy8Eg//gIPfrqGLg1g+RB6Jai6DFiaxyaP6v2twex3ZN2cRGB3A38tH8Lwg8Zlx4suVUBIRERERkY+kJTlhZp8HcupsKwaeBe4ECoHvAA+Y2Zhauz0C5AF9gJOBUcDtTR+xpJO3x8Ptdfj6+w/abtlG6PIQ3iqP+Bx92W0pEqsSVN9aDQnI/nEW/hM/et1CnwxinY3I/RFcTAklERERERFJavbkhJn1BG4Fvlyn6DpgsXPuPudc1Dn3HDANuCF1XDHwCeB7zrm9zrktwE+B680sq5nClzTwUvNN+E849O0aOCOAr7eP6D+juKi+7KZbfF6c6t/UYO2M7J9l4e9TJ6EUNsLXhnBbHbHnNV+IiIiIiIgkNWtywswM+Dtwq3NuY53iYcDcOtvmAsNrlVc555bXKc8BBh7mXIVmVlz7AvQ8/lpIc0uUJCAIvt6Hvl3NZ4SuDuF2OWLT9WU3nWJvxaj5YwRfDx85P83G1+XwzUtgWIDAGD/RZ2N427TaioiIiIiIHEdywpKGmFm7Bhz2VcCcc389TFk+UFpnW2lq+9HKqbVPbd8G1tW5zGxArNJCJEo8fMU+LGCHLQ+c5Mc/0k90WgyvVF92m5tzjui0KJF7o/iH+Mn+URaWf/jXar/QNSEIQOSBiOYLERERERGR+icnzOx/zeyLqdsGzAAWA5vMbFw9ju9PchjGl46wSzlQUGdbYWr70cqptU9tdwB961wmHitOaVlc3OGtP3QyzLrCV4UgpqVFm5vzHNFHokSfiBEY5yfrO2Es6+iJCQBfoY/wFSESSz3iszRfiIiIiIhIpmtIz4nLgaWp258AhgLjgIeA2+px/ESgI/CBme0ys12p7c+Y2d3AQpITXNY2CliQur0QyDWzwXXKq4FVdU/mnCt1zq2vfQE21SNOaUG8jR7EwD8gOXdBWbTmsL+0+7r6CJ4TID4zTmK9vuw2Bxd3RO6JEHspTvATAcJfCR+xd8vhBKYE8PXzEX00gqtU7wkRERERkUzWkOREVz76cn8u8C/n3GySq2sMP+JRH3kC6Jfad/8Fkj0pfgQ8CAw1s+vNLGhmFwAXAX8BSCUXXgJ+Z2btzawI+CVwv3OupgH1kFYksTo5TMM3wMeq0l2c+8KD3DjreTZU1B3hA6FLQpCnpUWbg6t21PxvDfF3E4Q+EyR0dQjzHTkxsa2qgqfXLyfufZQ4Mp8R/kIIVwmRx6PNEbaIiIiIiLRQDUlO7AW6pW5PAd5I3TbAf7gDanPOVTnnNtW+pIp2plbfWAdcDNxEcpjGHcD1qQTIfteQ7CmxgWQvjg+A7zagDtLKeGsSWAfD18HHCx+uwjCW7t3BVTOe4M9LZ1MT/2gYh+Ua4U+H8FZ4JOaq90RTqrk3QmK5R/j/hQhdGCI50utQu2qq+N+Fb/PpVx7jtvlv8u+1Sw8q9/fxE/xEgPgbcRKr9JqJiIiIiGSqQAP2nQ7ca2bzSc7f8FJq+xBg/cc5uXPO6tx/leRwkSPtvwu44uOcS1qnRImHr78Pzzle3byGcV178aMRk7hzyXs8sGo+0z9czXeGTmBS92LMjMDkALFXYkT+GcU/3I8F6z/MQOonsTxB4v0EoU8HCU4MHnaf8miEf6xewD/XLCbmJbiw9yA2VJZx38p5XNhnEHnB8IF9Q5eGiM9JELk/QvYvsxs0NERERERERNqGhvScuJHkahcdgE875/b3qx9JcsiGSKPyyhxup8M/wM+i3dvYUb2PqT0H0DErh1+MmsI9Ey8mNxji+7Nf4jvvvsimyjLMb4SuDuN2OGIva3LMxuY8R+TRKNbRCJ5/aGKiKh7j7ys/4JMvP8KDq+ZzRvdiHj/7M/z41MncdMp4yqI1PLRqwUHHWJYR/nwIb5Mj9qJeMxERERGRTFTvnhPOuQqSCYq623/SqBGJpHglyW7+/gE+XtlcQtgf4IzuxQfKT+1UxMNnfprH1yzh3hVzuXLGE1w7cASfP2k4/uF+ok/HCJwexFegX+IbS/ydON56j/BXw1joo+c1kojz5LplPLByHnujNZzRrZgbThrNCQUdD+xzYvvOnNNzAI+tWcxl/YbQJTvvQFng1AD+UfHkazYmgK/Lx17lWEREREREWqEGfQMws45mdqOZ/cnMOqa2jTWzPk0TnmSyRIkHfvB6w4zNazm9W29yAgf/Wh/w+bn6hGH86+wrmVzU90CSYunUXcmlRf+jiRYbi6txRP8Vw9fPR2BscpqZuJfg6XXL+PQrj/GHxbMYUNCRv0/6FP877tyDEhP7ffWk00h4Hn9dPveQsvDnQuCDyIOa0FREREREJNPUOzlhZicDK0j2nvgKUJAqupDkqhkijSpRksDXx8f88q3siVRzTo8BR9y3c3Yut44+m/+bcCFB8/G1Nc/x3pDNxN6IkdjoNWPUbVf0hRhuryN8dQjPHNM/XM1nXn2c2xa8RZesPO46/SLuOv0iTu7Q9YiP0SM3n8v6DeG5DStZW77noDJfBx+hy0IkFiWIz9HkmCIiIiIimaQhPSduBx4FTgBqL905HZjYmEGJuITDW+vhH+Dj5U0l5AaCjOvW+5jHndalJ4+cdTlfHzKG3/d9j8pAlI2P7W6GiNuusmgNi0q2UjMtwqqBe/jylmeYMu3v/GzuDML+ILePPY/7Jn2S0Z171OvxvjDoVLIDQe5aOvuQsuDUAL5iH9GHo7gq9Z4QEREREckUDVmtYzTwDeecq7Ns4Id8tMSoSKPwNnkQBdfPeH3LWs7o3pcsf/3erkGfn2sHjuDcniewYPUmRi7vzrode+nbpX0TR926xbwEGypKKSnfTUnZngPXO2r28YO54+np5fK/A9+lwJ/FJcUnMqJTEZO6F+M7wjKiR1IYzubagcP587I5zN+1lRGduh8oM58Rvj5E9S01RP8VJXxt+CiPJCIiIiIibUVDkhMGHG7dwF5AeeOEI5LkrU4OxVhYuJ2KHVHO6dm/wY/RNSePURf0IrwMHpm2gK9fP5aAz9/YobZ6lbEIP37/Vd7fsZm4Sz7vAfPRN789IzsXMaqyiDM39iZ2LjxyxeVYA5MRh3Nl/1P499ql/GnJe9w36ZMHPaa/n5/g1ACxV+IEJgTwD9BrJiIiIiLS1jUkOTED+BrwjdR9Z2Yh4CfAy40dmGS2xBoPKzCer1pFfjDMaV16fqzH6XByDnvzKxi0sgP3rZjHDSeNbuRIW7eaRJzvvjudRXu2c2X/UxhU2IkTCjrSJ6+AgM+Pc47qX9Xg2nkUXprTKIkJgKxAkC+fOIpfzX+T17esY0qPfgeVhy4LEX8/QeShKNm3ZGE+rbgiIiIiItKWNWTOiR8AnzazWUAYuAtYDZwM/KgJYpMMlihJQD94a9t6pvToR/Bj9ngwn5E7LszYHT15fMliFu/Z3siRtl5xL8F/zX6ZBbu38otRU/jWKeM4t9cJ9M/vcKCHSWJuAm+lR+iyEJbduAmCC3oPom+79ty1dDZx7+AJMC3bCH0mhLfOIz4z3qjnFRERERGRlqfeyQnn3BpgGPASH/WUeBA41Tn3YRPEJhnKVTjcNseGruVUxWNM7XnkVTrqI3BagEDCx7m7+3PL3BlUx2ONFGnrlXAet3zwOu9s38gPh5/BOYd5jl3MEflnFF9PIzCpIZ2s6ifg8/GNIWP5cF8ZT69ffmj5eD++AT6iT2hyTBERERGRtq4hS4kGnHM7nHO/cM5d6Jw73zn3M+fcDjPr1JRBSmZJrEn+iv5G9no6hLM5tdaEiR+Hb4AP62h8vnQYm/aV88cl7zZGmK2Wc47fLXyblzeV8PUhY/hU35MOu1/s5ThuhyP02RDmb5phFad3682Ijt3524oP2BeLHlRmZoQ/F8JVQPTp6BEeQURERERE2oKGDOt46HAbzawD8GrjhCOSnG8CgyfdMs7u0R+/NeRteijzGYHT/OStDHJ9z1N5ct0y3tm2oZGibX3uXjaHJ9ct4/MnDOfagSMOu48rd0SfieIf5idwSuP3mtjPzPjmyWPZE6nmkZKFh5T7+/kJnBEg9nIcb6vXZHGIiIiIiEh6NeRb33Azu732BjMrBF4BdjZqVJLRvJIEld2ilPuiTP0Yq3QcTmBsABJw7b5hDMjvwK3z3qQ0Ut0oj92aPLxqAQ+sms+nik/i60PGHHG/6JNRiED4qlCTx3Ryh65MKerHI6sXsqum6pDy0OUhCEHkH+o9ISIiIiLSVjUkOXEecKWZfQ/AzPJJzj1RAVzUBLFJBnKeI7HGY2mHnXTNzuOUDt0a5XF9fX1YZ4P3Hb8YdRblsRp+vWAmzmXOXAZPr1vGn5a+x9Qe/fn+8NOPuPKGt9kj9nqc4JQAvh7H12ulvr425DSinsd9K+YeUuYrMEKfCpFYlCC+QJNjioiIiIi0RQ2ZEHMDcD7wYzP7KvAiEAUucM7VNFF8kmG8LQ6q4c3sDUzt0R9fIy1daWYExgRILE0wwNeBG04czWtb1vLih6sb5fFbulc2lfA/C95ifNde3DJqylGHykQejUIWhC5t+l4T+/XOK+RTxSfy9PrlbKgoPaQ8ODWAdTcij0RxscxJKImIiIiIZIoG/SzqnFsIXAr8IXXsuc65fU0RmGQmryQ5GeaS9juOe5WOugJj/JCA+Nw4V58wjOEdu/O7hW+ztaqiUc/T0ry7fSM/n/sawzp259ennXPUZVnji+IkFiUIXRLC2jXNJJhH8sXBIwn7A9y9bM4hZRYwwteEcNscsZe02oqIiIiISFtz1OSEmb1c9wL8F1CaOvbJWttFjluixGNfOIZ1NQYXNu4iML4+PqybEZ8dx28+fj7yTByO//7gdbxmGt7hnGPzvnJWl+3mw8oydtXsozIWIe41zWSPC3Zt5fuzX6Z/fgd+P+5csgLBI8eWcEQfjWJdjODUppsE80g6ZuVwzQnDeG3LWhbv2X5IeWBoAP9wP9FnYnilmhxTRERERKQtOdY3kM0N3C5yXKKr4ywp3MHUXgOOOCfCx2VmBE4LEJsWwytz9CjI57tDJ/DLeW/wWMkirj5hWKOeD5LJiI2VZczbtYUPdm1h/q4t7DzMpI8AQZ+PLH+AbH+QsD9AdiCQvB8IUhDKom+79vRr156++e3pmZtP4Cg9IABWle7iO++9SNfsXP444QLyguGj7h9/M4632ZF1YxgLNm+vif0+O2AY/167lDuXvMtfJ15yyHsgfE2Iqh9WE308RtYNR6+PiIiIiIi0HkdNTjjnrm+uQERclcO2OpYO3skFPU9sknMExgaIPRsj8X4c39lBLuw9iDe3rufPy2Yztmsv+ud3OK7Hd86xrmIv83ZtZd6uLczftZXdkWQyolNWDqd2KmJEp+60D2VTk4hTnYhRE49Tk0hequOxQ27vi8XYWFnGy5tKPqqH+eidV0Df/Pb0a9eBvvnt6duuPb3zCgj6/GyoKOWb7zxHXiDEXRMuokM4++hxVzmi/47iG+TDP+roSY+mlBMI8uUTR/GbBTOZuW0DZ3QvPqjc19VH8NwgsediJM4K4B+QvlhFRERERKTxNH/fbZEjSKzxMGeU9qo57iTBkfh6GlZkxGbHCZ4dxMz40YhJfHbGE/xs7gzun3QpIX/9v/DGvQTrKkqZfyAZsYW90eT8sF2ychndpQenduzOqZ2L6JVbcFy9QarjMTZUlrK2fC/rKvayrnwvq0p38drmtewflOI3o1duAeWxCGbGnyZcSNecvGM+dvTZGK4Csj4bavQeKw11SZ/BPFayiLuWzmZ8194EfAePPgtdHCT+dpzIw1Gyf56F+dIbr4iIiIiIHL+jJidSc0lc7pwrO9a8Es65cxo1Msk45SuqCQB9hzZNYgI+WrUj9nRy3gJfoY8O4Wx+PGIS331vOveumMvXh4w55DjnHLsjVZSU7aGkfDery/awpnw36yr2EkvNF9EtO49xXXtzaqciTu3UnR65+Y36RT87EGRwYWcGF3Y+aHtNIs7GilLWVnyUtKiIRbjplPH0aVd41Md0niP6VIzY8zECpwfw90t/T4SAz8/XTxrDD+a8zE/ef5UL+wxiTJeeBybytGwj9Jkgkb9Eib8TJzjxyPNoiIiIiIhI61CfOSe8WrdFmsyeZVVU58eY3L9fk54nOCZA7KkY8TkJQuckf5Wf2L2YS/oM5uFVCxjduQd5wdCBRERJ+R5KynZTGv1oxdzOWTkMKOjIaV16ckJ+R4Z17EZRbn6Txn0kWf4AAws7MbCBE4i6SkfN3RESixIEJgYIX9d8S4cey+SivlzVfyjTNq7gtS1ryQuG+P/t3Xt8XHWd//HX58yZmdzb0tIWW9r0Rku5CFgoUEAE5CJQXV0RXN0fLCqKq7i6KrggrLi64KII7iIgC3hDlMdDgUVAkUvLXW4V0NJS2pTeb6ShSeZy5nx+f8wEwgBtUpJMJnk/H4/zyJzzPcn5nJwkj8e8870cPr6ZYyZM5aCxE0kdGpK/JyJ3c55wTojVqveEiIiIiEg1M+/lKgVmVgtMK+0uc/fOPq+qn5hZM7B8+fLlNDc3V7YYeQN3Z/2nW1k0eT3HXTCr36/X8Y0OqDXqLnh9Lob2fI5P3HcLq9vbXjtWkwiZ1rQL05p2YcaI0Uxv2oVpTaMZma7p9xr7U2FFgcwPs3irk/5kivB9YcWHc7yVXKHAnzeu4t7VL/HA2hW05bPUh0kOGz+Zk+OZzP7RLiQ/kCR92uAJVips8D1EEREREZEe6PGcE2aWAr4LfA7omiY/a2Y/Bs5z92w/1CfDxJqX2hiRTVE3c2DeZIZzQ3K35Ik3xwSji70n6pMpvjf3OB5Yu4KpjaOYNmIXJtQ3kbDtrrhbdfIL8mRvyGGNRu35NSSmVX4ox9tJJRLMGz+ZeeMnc25c4ImNa/jT6mXcv2Y5d+df5LzmeRx1VzNP7LmG9+w9YbtLpYqIiIiIyODVm3ddVwKfAM4B9ilt5wCnAVfs6JPN7BIze97M2sxsjZldZ2ajy845xswWmVmHmS0xs1PK2keb2c2lr7HFzH5sZlpPcAhY/NQGAGYeMHZArhfOLeZy0eOFNxyfPmI0Z856D++bMJVJDSOHVDDheSdzfZbstTkSMwLqLq4d1MFEuWSQ4JBxu3P+AUdy1wf+kR/NO4mVx7WRDQp0/CLLsb+/kUufWUgUF3b8xUREREREZFDpzTuvU4F/cvdr3f2vpe1a4FOlth0pUAw3RgP7AbsDN3Q1loZc3EYx6BgJfBm4wcy6z074C6ABmAzsDcwBLuvFPcgg1fFCns5knl2n1g/I9YLxAcHkgOixaECuV2nx5pjOb2eI7o1InpSk5ms1WFP1jgAIgwQHjZ3IOYfNo+kjtRyybiKfzr+HW5Y/z1cfvZtMlK90iSIiIiIi0gu9CSdywItvcXwZsMN3Au7+DXd/2t3z7r6BYgjx3m6nnA486+7XuXvO3f8PuB04C14LL44D/tXdX3H3NcAFwBlmVt0TAAxzy9q2MHFdI+2TogFdFjI8OEG8LCbeGO/45CoWPV+g44JO4jUxNeekSX8shSWqN5golz4+hY03PvzoTM7b+wgeXr+SLz78e7blNdJMRERERKRa9Cac+AnwZes2a17p9ReB63bi2kcDi7rtvxt4ouycJyj2suhq73D3v5W11wF7lH9xMxtpZs3dN2DiTtQp/ezel5YxdetIRu5Zu+OT+1B4UNfQjqHZe8Ldyf1fjswlGYImo+5btYRzejzNTNWw0Ej/Qwpf55y4ZAYXH3gMz25Zz9kP3s4r2aqZr1dEREREZFjb7jsVM7um224AfBR4v5k9Xjp2IMVhGrf05qKluSQ+xRt7TjQBfy07tbV0vKu99S3a6XZOd18CLuxNXTLw3J3lz24hQUDNrIGdPiQYGxBMDYgeK5A6cUAv3e+808lck6XwRIFwboL0p9JYzdDpLVEu3C8ksV9E7tc53jdiMvUHH8e5j/2BsxbcypXzTmJcXUOlSxQRERERke3YUc+JGd22acBTQAswrrStBJ4Gpvb0gmZ2KnA1MN/dn+rW1AaMKDt9ZOn49trpdk53lwNTyrbDe1qnDIwXtm5i19V1ACSmDvzkjOHckHh5TLx+6AztiNfGdFzYSeGpAqmPp0h/fmgHE11qzk6T2DMge3WOA5/cjSvmncTGTAefXvA7Vm4rzzVFRERERGQw2W7PCXd/X19ezMzOBL4HnOTuD5U1LwKOLzs2B3imW3u9mc1y98Xd2juBJeXXcvdWynpadBuRIoPEH1a9yOwtu+LjwBoH/vmEcxPkboLosYjU/IFZxrQ/FV4o0Hl5BjOoPa+GxKzqWY3jnbJao+YrNWSvzpL7VZ7ZW3fhquNP5hmCQQgAABXVSURBVJxH7uAzC27linknsseIMZUuU0RERERE3sKArZNoZl8ELgGOfYtgAuBGYF8zO8PMkmZ2InAyxV4WuPsK4G7ge2Y2yszeBVwMXO/umQG5CelTsTv3vLyMfVvHkZxRmbkQgtEBwYzi0I5ql384ovM/M1ijUXtR7bAKJrpY0kifnSb5/pD8nRHNNzdyzaEfIhkk+OzC21i0eW2lSxQRERERkbcwYOEE8EOKwzLuN7Nt3bZJAO6+HJgP/AvFYRqXA2e4+2PdvsYnKPaUaAGeB54EvjKA9yB96Lkt62EzNHamSEwfyB/FNwrnhsQrY+K11Tm0w93J3Zoje1WWYFpA3TdrCcZW7vtZaRYYqU+mSH00SfRwgbHX1nDtQR9kl3Qt//zQHTyy/uVKlygiIiIiImUG7B2Mu5u7J929oWxb2e2ce9x9X3evdfcZ7n5z2dfY5O6nuHuTu49y97PUa6J6/eLFRby7dRwAQSXDiYMSYBA9Wn2rdnjkZH+SI3dLnvDQBLVfr8EaNHzJzEjNT5E+M0XhuQJNPwy5Zv8PMrlhBF955E7uWb2s0iWKiIiIiEg3w/ffq1JRD65r4b41y/lwvCekIZhYuR/FYFRAsEdA9Fh1hRPe4WT+K0O0ICL5oSTpz6axpIKJ7pJHJqn5Upr45Zj0JXDVrJPZa9RYzn/8Hn634m87/gIiIiIiIjIgFE7IgMtEeb636EGmNI5ij027kJgaYInKvqlOHhwSr3YKq6pjaEe8KabzW50UFsekP50i/ZGUJnx9G+EBIbVfr8HbnOC7MVdMOoG54ybynacf4LrFT/LclvUsa9vC6vY2Nmc66IjyFLw6fg5ERERERIYKc/dK1zBgzKwZWL58+XKam5srW8ww9j/PP8YNS57m6rnzmfGNESRPSJL+WGVXyoi3Oh1f6CD5wSTpjwzuVTsKywtkLsvieafmizWEew2/iS93RuHlmMz3MnjWSZ6T4t+33b/d4R3pIEE6EVIbJqlJhNSGIelESGMyTVMyTVOquDUm04xIpWlK1tCYer2tMZkmDAY8/1VCJSIiIiJVqTJLJMiwtaxtCz9buoiTJs1k323j6CxkSMyofAeeYISR2DMgejQi9eHkoO2FED0VkfnvbHFFjnNrSVRwOEy1SeweUPvNGjovzZD/rxwXfe5ITj1iH17NZ+ksRGSiiEwhT6YQ0RlFZAql/SgqthciOqM8GzvbWda2mbZcjvYot91r1ocppjSO4qTJMzl24jQakukBulsRERERkeqicEIGjLtzyTMLqQ+TfGHvg4luKc7xEEwbHP/5D+eGZK/PEa+MSUzu25rcHRyIgQKQLK4q0Ru5P+TJ/TxH0BxQ8+U0wUgFE70VjAmou6CWzssy5K7Msec/jiY8OtzpMCqKY7bls2zNZWnLZ3k1l6Utn2FrLsur+Sxbcxme2LiG/3xmAT949mGOetcU5k+exf5j3kUwSAMwEREREZFKUDghA+aOlS/wzOa1/Nv+76X+zgS5u/KEh4UEIwbHm7TwwJDsjTmixwoEkwLIgL/qeFtpe9Vf33+V149t82LgUABix2NeDyG863jZxQKwBrBGw5qs+LHRoOt1t2PWZORvz5G/OyJxQIKaz6WxmsHxPatGxV4nNWSuzJK9MUfuzjzJw8Liz+KuvQt8wiBgZLqWkenatz3H3flb60Zua1nM3S+/yJ0vL2VCfRMnT57JiZNmMq624Z3ekoiIiIhI1dOcEzIgWrMZPnrPr2iuH8mVG08gui0iPCwk/elUr3sQ9KfOSzMU/looThWbf5uTkhTDg64AoQEIrfg5CbCA4usASNhrr63UjoF3BR9l4Qftb19b8riQ1McH1/ermnnkRI9GRAsiCn8rpkfBrIDk4SHhgSFW2/ff50yU5741y7mtZTFPblpDgDF33ETmT57F4eObSSXecY8d/XCIiIiISFVSOCED4ttP3c8dLUv4bdvHaLgnJDwyJH3G4HujXXixQP7+CKs3rOnNPRusySBNv81J4VGxJ8Ybema86gSjjHCOOjr1l3hTTPRgRP7BCF/vkILwwAThYUkSs4N++TldtW0rt698gTtaXmBDpp0RqRpO2H0G8yfPYvqI0Tv7ZQfXL5SIiIiISA8pnJB+98ymtXxmwa1cufIE9npyDMljQlKfHHzBhIi7Ey+NyT8YET0WQQfYLkY4LyR5eEiwW9/P81HwmMc3rOLWFYtZsHYFkcf84qiPMmPnAgr9UomIiIhIVVI4If0qigt88k+3cMojs3n/0qkkjy8NTdBkgDLIec6JnioQLYwoPFsAh2BaQPKokPCQEEv2/c9wa7aTBWtbOHnyzJ39HdEvloiIiIhUJYUT0q9+uvhp0j83TmyZQfKkJKlTBu8ynSJvJ26NiR4qEC3ME692rAmSRycJj04OmgldSwZVMSIiIiIiPaVB7NJv1rS10fTzJMe0TCH5oSSpDyuYkOoUjAxInRiQ/EBI4fmY/N15cr/Nk7s9T3hoSPLYsM+XnxURERERGU4UTki/iPMxK36wmWNappCdH9PwkVSlSxJ5x8yMcO8E4d4J4rXFkCK/sLjiR2LPgOTxSRL7JTSfioiIiIhIL2lYh/Q5j5xVl21h1HM1PH/MJub+v8mVLkmk33i7k78vT/6PEb7FsXFG8rgkycNDrGbAQwqlIiIiIiJSlRRO9MCCtStoSKbYf/RuGpawA5532q/ohGecXx30V07//AGEgbq7y9DnkRM9USB/d574xRjqIPnekPDQkGBsgNUNyN8O/YESERERkaqkYR098JPFT7C4dRMzR4zh1On78P4J00kl9Ia7nOeczOVZeNa5fL/HmP/x2QomZNiw0EgeHJI8OKTwYoH8XXnyd0fk74yKJ9RBMCbAxhjBGMPGBAS7Wmk/gHoUfoqIiIjIsKWeEz2QifLc9fJSblr2LMtffYXR6Tr+fupe/N2U2eySru2naqtLvCkmc1WWwtIC39//UVJHJjlv//dWuiyRioq3xMRLY+JNjm9640cyZSfX8FpokT49RTA62JlLKt0QERERkaqkcKIHor9EWJ1hU43HN67mpmV/4ZH1L5MKEhy3+wxOm7YP00eM7qeqBzd3J1oYkf1ZDoAbDl7E7eOX8Ov3n8qIVE2FqxMZnNwd2ouhnm/0svDCqT23BmvcqZxB4YSIiIiIVCUN6+iB3K/zxC0xtptxwGHjOGjeCbTsvZVfLXuW37+8hNtbFnPQrhM4dfq+HDpuEsEw6Zodb3Wy/5ul8FSBYFbAvce38NOVf+GifY5SMCGyHWYGDZBoSEBzpasREREREak89ZzoAe90oscj8gsj4hdiMEjMDggPC2nfN+LWtYv5zUvPsSHTzqSGEZw6bR9OnDST2jDZT3dSedGfIzLXZyED2+ZHXDbuER5Yt4I5u07gv+edpLHzIpWhXzwRERERqUoKJ3op3hATPRiRfyjCNzjUQHhgiM0z7mto4aaX/sLfWjdSFybZf/RuHDh2AnN2ncD0ptFDokeFtzvZn+WIHoooTHJ+fuRz/GzbImrDkE/M2I+PT993SIcyIoNc9f+REREREZFhSeHETnJ34iUx+YUR0WMRZMDGGOGhCZbt08ptmRf484bVvNy+FYBRqRres+sEDixtE+qbqq53QfRcgey1WeJW55mD13P++HuJgpiPTNmLM2YewChNDipSadX1R0VEREREpEThRB/wrBM9WSB6MKLwXAEcgikBwe4BHaPzLKndzOPBGv6UX8ba/DYAxtc2FIOKUs+KMTX1fVZPX/Osk7s5R/6PEa+OznHh/g+wqGkdJ+y+B5/Zcw7vqm+qdIkiUqRwQkRERESqksKJPhZviYkejogWFfC1jm/t9v01KIx2No/qZHndKzwdrmNp7RZebmijcWyamaPGMKVxFFMbRzGlaRQT6ptI2E4tJ9hnCi8WyFydxdc5v5+5lCtm/ZmDJkzk7NkHDdsVSkQGMYUTIiIiIlKVqi6cMLMA+DZwJlAPPAic5e4tPfjcZvo5nCjnHU68LiZeW/zoa2PidU68Nobc6+dlwwIb6ttZVdvG+rptrK9rZ1NDB4wJaByfYtzYRqY0jWJq0ygm1jcRBom3v2bO8dbSttWJS69pdwh4fUvYa68tABJdbcXj8caY/B/zbKnt5DsHPEQ0y/nnvQ5m/zG79ee3TER2nsIJEREREalK1biU6NeA04AjgNXA94HbzWw/d48rWtlbsDojMTVBYuobj3vs+CtOvM7xtTHJdTF1G1PsvrGJwlon0fnG9xiZRMS6um0sq9vII3UryI0qUJ9KMSpTy8jONE0daerbk9S2hySzbw4uPHCoMzx2iHltsxgsfvv3M3+Y9BK3z1vKGfsdwBG7NVfdPBkiIiIiIiIy+FVjz4kVwCXuflVpfySwDjjW3Rfs4HObGeCeEzvL2514U4xvduKNTn5DRPv6HIWNMcktATWZYq6UCSNeqcmwuaaDTekONtd0sqUmw5aa0ut0hi01nbSls8T2Ns/aIcBIEtAYpGkMUzQGKRrSKY6ePp0PTNqj4sNLRKRHlB6KiIiISFWqqp4TZjYCmAw80XXM3VvNbBmwH7Cg27kjgZFlX2LiQNTZF6zeSNQnincLpEhSz+urYXhnMWhoqDXGMIIZQBTHdEZ52qMc7VGe9nyO9ijHtnxxP1coUJ9MUh+mqE+mqA9ff90QJkknQvWMEBERERERkQFXVeEE0LUsRGvZ8dZubV2+BFzY7xVViNW+OUQIg4DGVJrGVLoCFYmIiIiIiIjsnGoLJ9pKH0eUHR/Zra3L5cANZccmAgv7viwRERERERER2VlVFU64+1YzawHmUBraURq+MR14puzcVsp6WGjIgoiIiIiIiMjgU1XhRMmPga+a2b3AGuBS4AWKS4ruSAJg1apV/VediEiFTJkypRlY5e5RZSsREREREemdalytIwD+AzgTqKcYSpzl7it68LmHoWEdIjK0TenJ30MRERERkcGk6sKJd8LM0sCBwFqg0ItP7Zqr4nBgOHW7GI73PRzvGYbnfQ/Ve1bPCRERERGpOtU4rGOnuXuWng3/eINuc1WsGk7/kRyO9z0c7xmG530Px3sWERERERmsgkoXICIiIiIiIiLDm8IJEREREREREakohRMiIiIiIiIiUlEKJ3qmFfj30sfhZDje93C8Zxie9z0c71lEREREZFAaVqt1iIiIiIiIiMjgo54TIiIiIiIiIlJRCidEREREREREpKIUToiIiIiIiIhIRSmc2AEzC8zsO2a23sy2mdldZja50nX1FzO7yMwKpXvt2m6qdF19zcxONbOFZtZmZm+aeMXMjjGzRWbWYWZLzOyUStTZ17Z332bWbGZuZu1lz39EpertC2Z2iZk9X7rnNWZ2nZmNLjtnSD5vEREREZFqoXBix74GnAYcAYwHVgK3m9lQ/t4tdPeGbttplS6oH7wC/A/wpfIGM2sGbgOuAEYCXwZuMLO5A1hff3nb++5mr7Lnv3WAausvBeATwGhgP2B34IauxiH+vEVEREREqoJW69gBM1sBXOLuV5X2RwLrgGPdfUEla+sPZnYRcKS7H1nhUgaEmR0J3Ofu1u3YRcAJ7j6327GbgXZ3/6cBL7IfvM19NwPLgSnuvqIihQ0AMzsJ+KW7N5X2L2KIP28RERERkcFuKP/3/x0rdWefDDzRdczdW4FlFP8DO1TNMbONZtZiZr80symVLmiAvZtuz7zkCYb2M+/uITPbZGYPm9nfVbqYfnA0sKjb/nB/3iIiIiIiFadwYvuaSh9by463dmsbam4B9gLGAocAEXCPmTVUtKqB1cTweuZdNgGHAlMoDn34EXCTmX2golX1odJcEp8Czul2eLg+bxERERGRQUPhxPa1lT6WTwg4slvbkOLuz7l7ixetAc4EdqP4pnW4aGMYPfMu7r7N3R9x95y7d7r7L4GfUZyvoeqZ2anA1cB8d3+qW9OwfN4iIiIiIoOJwontKE0E2ALM6TpWmnNiOvBMpeqqAAdsh2cNHYvo9sxL5jC8nnmXIfHszexMihOBnuTu95U163mLiIiIiFSYwokd+zHwVTPbozS04VLgBeDBypbVP8zsY2a2a+n1WOAaYCPwcEUL62NmljCzGiBV2q8pbQFwI7CvmZ1hZkkzOxE4meJ/3ava9u7bzA43s9lmFppZysw+BnwSqOqlZM3si8AlFCexfegtThmyz1tEREREpFpotY4dKL1Z/Q+KwxvqKYYSZw3V1QzM7DaKc03UU1x2cgFwgbu/WNHC+piZnQ5c/xZN73P3+83sGOD7wAxgFXC+u988gCX2i+3dN8UeQedRXDI3CywBLnP33wxYgf3AzJzi3CnZsqbZ7r6ydM6QfN4iIiIiItVC4YSIiIiIiIiIVJSGdYiIiIiIiIhIRSmcEBEREREREZGKUjghIiIiIiIiIhWlcEJEREREREREKkrhhIiIiIiIiIhUlMIJEREREREREakohRMy7JjZ/Wb2k0rX0VNmdrqZRZWuQ0REREREpL8onBCpMmZ2vpmtqHQdIiIiIiIifUXhhMgAMbNUpWsQEREREREZjBROyLBlZheY2Toz22JmPzWzhtJxM7N/NbOXzCxnZsvM7Etln7vCzM4vO/YTM7u/2/79ZnadmV1sZmuBlT2oKSidv8HMtpnZzcCobu2nAxcDk83MS9tF7+DbICIiIiIiUnFhpQsQqZC/B64HjgQmAb8CWoALgLMpBgDnAPcBRwOXm9mr7n5dL69zCvCL0tdI9OD8LwBfLtXwCPAh4MJu7TcDs4B/AA4sHdvWy5pEREREREQGFYUTMly1uPu/lF4vLvVQOIZiOHEucKW7X1NqX2pmM4F/A3obTqwFznb3uIfnfxW43N1vLO1famYHUQwpcPdOM9sGFNx9XS9rERERERERGZQ0rEOGq0Vl+2uAcWbWBEwEFpS1PwA0m1ldL6/zZE+DidK1JwAPlzU92MtrioiIiIiIVBWFEzJc5cr2nd79PsSAlR1LvsV57b0pSkREREREZDhSOCHSjbu3AauAI8qa3gssd/eO0v4G4F1l5+zfB9deDRxa1jSvbD9Hz+avEBERERERqQqac0Lkzb4LXGZmS4H7gaOAzwGf73bOPcDZZvZbihNpfhaYDGx5h9e+DLjYzBYDjwLzKc6F0d1yYLyZHQIsBTq6hSYiIiIiIiJVRz0nRN7sKuCbwDeAvwJfB84tW6njEuAOiqtnLAS2Ar/pg2v/ELgC+AHwDHAI8K2yc35XutYdwEbga31wXRERERERkYoxd690DSIiIiIiIiIyjKnnhIiIiIiIiIhUlMIJkQFiZoeb2bbtbIdXukYREREREZFK0LAOkQFiZrXAhO2cstrdOweqHhERERERkcFC4YSIiIiIiIiIVJSGdYiIiIiIiIhIRSmcEBEREREREZGKUjghIiIiIiIiIhWlcEJEREREREREKkrhhIiIiIiIiIhU1P8HKwC4hpxgJtUAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = sns.FacetGrid(data=bike_counts_total, col='day_of_week', hue='date_dt',\n", " col_wrap=3, height=2.5, aspect=2)\n", "g.map(plt.plot, 'hour_dt', 'bikes')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here it would be helpful to add a legend and clean up the subplot titles." ] }, { "cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 143, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = sns.FacetGrid(data=bike_counts_total, col='day_of_week', hue='date_dt',\n", " col_wrap=3, height=2.5, aspect=2)\n", "g.map(plt.plot, 'hour_dt', 'bikes')\n", "g.add_legend(fontsize = 10)\n", "g.set_titles('{col_name}', y=0.9) #`y` adjusts the relative y-position of the title" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Saving plots\n", "\n", "A figure that has been assigned to an object (like `g` above) can be saved to a file using the command `savefig()`. Specify the format for the image with the extension: `.jpg`, `.png`, `.pdf`, etc." ] }, { "cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [], "source": [ "g.savefig('counts_by_weekday_vs_hour.png', dpi=300)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### A final example\n", "\n", "Lastly, let's try to find out if the counts changed at all between 2010 and 2017. To do this, make a new column called `year` using the datetime accessor `.dt.year` on the `date_dt` column." ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [], "source": [ "bike_counts_total['year'] = bike_counts_total['date_dt'].dt.year" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can use `year` as a variable to partition our data by." ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 146, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = sns.FacetGrid(col = 'day_of_week', hue = 'year', col_wrap = 3, \n", " data = bike_counts_total[(bike_counts_total[\"day_of_week\"] != \"Saturday\") & (bike_counts_total[\"day_of_week\"] != \"Sunday\")])\n", "g.map(plt.scatter, 'hour_dt', 'bikes' )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What about the rain? Let's keep only the days that had \"No Rain\" as the weather condition. " ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "weather\n", " No Rain 144\n", " Rain 6mm 24\n", "Rain 4mm 24\n", "dtype: int64" ] }, "execution_count": 147, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# first assign the weekday dataframe to a variable\n", "bike_counts_total_weekday = bike_counts_total[(bike_counts_total[\"day_of_week\"] != \"Saturday\") & (bike_counts_total[\"day_of_week\"] != \"Sunday\")]\n", "\n", "bike_counts_total_weekday.groupby(\"weather\").size() # how many weather conditions are there?" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
date_dtday_of_weektemperatureweatherhour_dtbikesyear
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [date_dt, day_of_week, temperature, weather, hour_dt, bikes, year]\n", "Index: []" ] }, "execution_count": 148, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total_weekday_sun = bike_counts_total_weekday[bike_counts_total_weekday[\"weather\"] == \"No Rain\"]\n", "bike_counts_total_weekday_sun.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Hmmm... we got nothing. What is the actual name of the \"No Rain\" weather condition?" ] }, { "cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "' No Rain'" ] }, "execution_count": 149, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total_weekday.groupby(\"weather\").size().index[0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There's actually a space at the beginning. A formatting mistake I didn't catch." ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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date_dtday_of_weektemperatureweatherhour_dtbikesyear
482010-09-20Monday19No Rain0282010
492010-09-20Monday19No Rain1212010
502010-09-20Monday19No Rain242010
512010-09-20Monday19No Rain352010
522010-09-20Monday19No Rain472010
\n", "
" ], "text/plain": [ " date_dt day_of_week temperature weather hour_dt bikes year\n", "48 2010-09-20 Monday 19 No Rain 0 28 2010\n", "49 2010-09-20 Monday 19 No Rain 1 21 2010\n", "50 2010-09-20 Monday 19 No Rain 2 4 2010\n", "51 2010-09-20 Monday 19 No Rain 3 5 2010\n", "52 2010-09-20 Monday 19 No Rain 4 7 2010" ] }, "execution_count": 150, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bike_counts_total_weekday_sun = bike_counts_total_weekday[bike_counts_total_weekday[\"weather\"] == \" No Rain\"]\n", "bike_counts_total_weekday_sun.head()" ] }, { "cell_type": "code", "execution_count": 151, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 151, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = sns.FacetGrid(col = 'day_of_week', hue = 'year', col_wrap = 3, \n", " data = bike_counts_total_weekday_sun)\n", "g.map(plt.scatter, 'hour_dt', 'bikes' )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">#### Challenge\n", ">\n", ">1. If you didn't do it already in the previous challenge, add a new column to the `bike_counts` dataframe called 'weekend', and fill this column with True if `day_of_week` is Saturday or Sunday, False otherwise. \n", ">2. Create a new dataframe with only the highest bike count for each day, for each direction. (Hint: group by 'date_dt' and 'direction', then use the function `.idxmax()` to get the indices for the highest value in the `bikes` column. Use this index to select only those rows from the original dataframe (with the new 'weekend' column).)\n", ">3. Create a two-panel cat plot split by 'direction' and coloured by 'weekend', with `kind = 'count'`.\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### More general resources on plotting\n", "\n", "- [Ten Simple Rules for Better Figures](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833)\n", "- [Finding the Right Color Palettes for Data Visualizations](https://blog.graphiq.com/finding-the-right-color-palettes-for-data-visualizations-fcd4e707a283)\n", "- [Examples of bad graphs](https://www.biostat.wisc.edu/~kbroman/topten_worstgraphs/)\n", "- [More examples of bad graphs and how to improve them](https://www.stat.auckland.ac.nz/~ihaka/120/Lectures/lecture03.pdf)\n", "- [Wikipedia has a great article on misleading graphs](https://en.wikipedia.org/wiki/Misleading_graph)\n", "- [Usability article about how to design for people with color blindness](http://blog.usabilla.com/how-to-design-for-color-blindness/)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Learning more\n", "\n", "Links to online tutorials, local coding-related groups, places to practice, and some fun add-ons.\n", "\n", "### Tutorials/Courses:\n", "\n", "* A very handy [pandas cheat sheet](https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf)\n", "* [The (Official) Python Tutorial](http://docs.python.org/2.7/tutorial/)\n", "* [Full Stack Python](http://www.fullstackpython.com)\n", "* [Udacity - Learn Object Oriented Python](http://www.udacity.com/course/programming-foundations-with-python--ud036)\n", "* [Software Carpentry - Python for Data Analysis](http://swcarpentry.github.io/python-novice-gapminder/)\n", "* [Codecademy](https://www.codecademy.com/learn/learn-python)\n", "\n", "### Local groups, meetups, and workshops:\n", "* [UofT Coders](https://uoftcoders.github.io/)\n", "* [Map and Data Library workshops](https://mdl.library.utoronto.ca/technology/workshops-training/workshop-schedule)\n", "* [St. George Library workshops](https://libcal.library.utoronto.ca/calendar/libraryworkshops/?cid=2020&t=d&d=0000-00-00&cal=2020)\n", "* [Graduate Professional Skills Program](http://www.sgs.utoronto.ca/currentstudents/Pages/Research-Related-Skills-Offerings.aspx)\n", "* [freeCodeCamp Toronto](https://www.facebook.com/groups/free.code.camp.to/)\n", "* [Civic Tech Toronto](http://civictech.ca/)\n", "* [Canada Learning Code](https://www.canadalearningcode.ca/experiences/?location=Toronto&program=ladies_learning_code)\n", "\n", "### Web Development with Python:\n", "\n", "* [Django](https://www.djangoproject.com/)\n", "* [Hello Web App](https://www.hellowebapp.com/)\n", "* [Flask](http://flask.pocoo.org/)\n", "\n", "### Fun challenges:\n", "\n", "* Advent of Code\n", "* [LeetCode](https://leetcode.com/)\n", "* [Project Euler (mathy challenges)](https://projecteuler.net/)\n", "\n", "### Fun libraries:\n", "\n", "* [PyAutoGUI (make your mouse and keyboard move!)](https://pyautogui.readthedocs.io/en/latest/)\n", "* [Dash (web apps and interactive plots)](https://plot.ly/products/dash/)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Resources and tools for specific data types\n", "\n", "Python is so general-purpose and popular that many amazing packages exist to work with almost any type of data. \n", "\n", "**To [install new packages](https://conda.io/docs/user-guide/tasks/manage-pkgs.html)**, open a terminal or Anaconda prompt and type `conda install package-name`. Example: `conda install scipy`\n", "\n", "### Text-based data\n", "* [Natural Language Tool-Kit (NLTK)](https://www.nltk.org/)\n", "* [A short introduction to natural language processing from UofT Coders](https://uoftcoders.github.io/studyGroup/lessons/python/intro-nlp/lesson/)\n", "\n", "### Web scraping\n", "* [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/)\n", "* [Requests](http://docs.python-requests.org/en/master/)\n", "* [Selenium](https://www.seleniumhq.org/)\n", "* [Web scraping tutorials](https://automatetheboringstuff.com/chapter11/)\n", "\n", "### Geospatial data\n", "* [GeoPandas](http://geopandas.org/)\n", "* [basemap](https://jakevdp.github.io/PythonDataScienceHandbook/04.13-geographic-data-with-basemap.html)\n", "* [A long list of other geospatial libraries](https://carsonfarmer.com/2013/07/essential-python-geo-libraries/)\n", "\n", "### Scientific (especially numerical) data\n", "* [Scipy](https://www.scipy.org/) - a package with lots of stats and probability (comes with Anaconda)\n", "* [numpy](http://www.numpy.org/) - matrices, arrays (comes with Anaconda)\n", "* [pandas](https://pandas.pydata.org/) - anything spreadsheet-like (comes with Anaconda)\n", "\n", "### Genetic data\n", "* [BioPython](https://biopython.org/) \n", "\n", "### Machine learning\n", "* [scikit-learn](http://scikit-learn.org/stable/)\n", "* [Theano](http://deeplearning.net/software/theano/)\n", "* [TensorFlow](https://www.tensorflow.org/)\n", "* [PyTorch](https://pytorch.org/)\n", "* [UofT Coders lesson on machine learning in Python](https://uoftcoders.github.io/studyGroup/lessons/python/scikit-learn/lesson/)\n", "\n", "### Image processing\n", "* numpy (no really!)\n", "* [UofT Coders lesson on image processing in Python](https://uoftcoders.github.io/studyGroup/lessons/python/image-processing/lesson/)" ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:py3]", "language": "python", "name": "conda-env-py3-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.0" } }, "nbformat": 4, "nbformat_minor": 2 }