Course Description

Running exciting analyses on interesting datasets is the dream of every data scientist. But first, some importing and cleaning must be done. In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

Course Description

It's commonly said that data scientists spend 80% of their time cleaning and manipulating data and only 20% of their time actually analyzing it. For this reason, it is critical to become familiar with the data cleaning process and all of the tools available to you along the way. This course provides a very basic introduction to cleaning data in R using the tidyr, dplyr, and stringr packages. After taking the course you'll be able to go from raw data to awesome insights as quickly and painlessly as possible!

Course Description

In this second part to Importing Data in R, you will take a deeper dive into the wide range of data formats out there. More specifically, you'll learn how to import data from relational databases and how to import and work with data coming from the web. Finally, you'll get hands-on experience with importing data from statistical software packages such SAS, STATA and SPSS.

Course Description

Importing data into R to start your analyses—it should be the easiest step. Unfortunately, this is almost never the case. Data come in all sorts of formats, ranging from CSV and text files and statistical software files to databases and HTML data. Knowing which approach to use is key to getting started with the actual analysis.

In this course, you will get started with learning how to read CSV and text files in R. You will then cover the readr and data.table packages to easily and efficiently import flat file data. After that you will learn how to read XLS files in R using readxl and gdata.

The SIParCS Program at the National Center for Atmospheric Research is aimed at university students who are interested in pursuing a career in such areas as:

• Application Optimization
• Computer Security and Formal Verification
• Data Science
• Numerical Methods
• Software Engineering
• Supercomputing Systems Operations
• Visualization

2019 Technical Projects and Program Intern Applications are now available!  Applications due January 11, 2019

These eight animated short videos explain ecological data, concepts, or techniques, including: "Ecological Forecasting: The Science of Predicting Ecosystems,"Eddy Covariance: Measuring an Ecosystem's Breath," and Mapping the Invisible: Introduction to Spectral Remote Sensing."

Students use their number sense to make observations and come up with reasonable guesses or explanations for the patterns shown. Forked version with all infectious disease graphs.

• All students should and can learn to formulate their own questions
• All educators can easily teach the skill as part of their regular practice

The Darwin's Finch Morphology database contains data, mostly morphological (e.g., beak dimensions), on individual Darwin’s finches. The data are from a number of published and unpublished sources.

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Explore in Radiant

Note: You must be a member of the BIRDD group to explore this data in Radiant.

Bibliography

• Price, F. and Donovan, S. (2006). "BioQUEST Library VII: BIRDD: Beagle Investigations Return with Darwinian Data Version 2.0 (User Notes)."  BioQUEST Curriculum Consortium.
• Lack, D.L. (1945). “The Galápagos finches (Geospizinae): a study in variation.” Occasional Papers of the California Academy of Sciences 21: 1-159.
• Lack, D.L. (1947). Darwin's Finches: an essay on the general biological theory of evolution. Cambridge, England, Cambridge University Press.
• Lack, D.L. (1969). “Subspecies and sympatry in Darwin's Finches.” Evolution 23: 252-263.
• Snodgrass, R. E. and E. Heller (1904). “Papers from the Hopkins-Stanford Galapagos Expedition, 1898-99 XVI. Birds.” Proc. Wash. Acad. Sci. 5: 231-372.
• Sulloway, F. J. (1982). “The Beagle collections of Darwin's Finches (Geospizinae).” Bulletin of the British Museum (Natural History), Zoology series 43: 49-94.
• Swarth, H. S. (1931). “The avifauna of the Galapagos Islands.” Occ. Pap. Calif. Acad. Sci 18: 5-299.

The Data Science for Social Good Fellowship is a University of Chicago summer program to train aspiring data scientists to work on data mining, machine learning, big data, and data science projects with social impact. Working closely with governments and nonprofits, fellows take on real-world problems in education, health, energy, public safety, transportation, economic development, international development, and more. For three months they learn, hone, and apply their data science, analytical, and coding skills, collaborate in a fast-paced atmosphere, and learn from mentors coming from industry and academia.

Each summer, SOARS protégés spend ten weeks conducting original research at the National Center for Atmospheric Research (NCAR) or at laboratories of other SOARS sponsors. By the end of the summer, protégés will prepare scientific papers and present their research at a colloquium. SOARS protégés can participate for up to four summers so that they can explore the breadth of geoscience and transition smoothly into graduate school.

We are an international mentorship group with a focus on helping more women become active participants and leaders in the Python open-source community. Our mission is to promote, educate and advance a diverse Python community through outreach, education, conferences, events and social gatherings.

PyLadies also aims to provide a friendly support network for women and a bridge to the larger Python world. Anyone with an interest in Python is encouraged to participate!

Data for Democracy is a worldwide community of passionate volunteers working together to promote trust and understanding in data and technology.

Data for Black Lives is a group of activists, organizers, and mathematicians committed to the mission of using data science to create concrete and measurable change in the lives of Black people.

Girls Who Code was founded with a single mission: to close the gender gap in technology.

The mission of NumFOCUS is to promote sustainable high-level programming languages, open code development, and reproducible scientific research. We accomplish this mission through our educational programs and events as well as through fiscal sponsorship of open source scientific computing projects. We aim to increase collaboration and communication within the data science and scientific computing community.

SACNAS is an inclusive organization dedicated to fostering the success of Chicanos/Hispanics and Native Americans, from college students to professionals, in attaining advanced degrees, careers, and positions of leadership in STEM.

The Carpentries project comprises Software Carpentry and Data Carpentry, communities of Instructors, Trainers, Maintainers, helpers, and supporters who share a mission to teach foundational computational and data science skills to researchers. The Carpentries subscribes to a shared Code of Conduct. 

Credit: NSF/Stephen Voss

NSF INCLUDES is a comprehensive initiative to enhance U.S. leadership in science and engineering discovery and innovation by proactively seeking and effectively developing science, technology, engineering and mathematics (STEM) talent from all sectors and groups in our society. By facilitating partnerships, communication and cooperation, NSF aims to build on and scale up what works in broadening participation programs to reach underserved populations nationwide.

Three researchers and early National Ecological Observatory Network (NEON) users talk about how NEON will enable new discoveries and collaborations in the field of ecology and beyond.

Search firms serve two roles in diversifying senior leadership. The first is to partner with organizations to identify what they are looking for in a new hire. The second is to help organizations move beyond their own networks to find the best candidates. Despite the relatively high proportion of well-educated people of color in the United States, diversity among management and leadership in a variety of sectors remains limited. In the environmental sector, particularly, people of color comprise only 12 to 16 percent of staff at environmental organizations and agencies (Taylor 2014). Organizations are increasingly turning to executive search firms to assist them in hiring for senior level positions, and often express interest in finding more diverse candidates, thereby, making search firms the gatekeepers of the networks that impact the movement of talent (Faulconbridge, Beaverstalk, Hall and Hewitson 2009).

The increasingly diverse demographics of the United States and the rising share of educational and consequent financial capital possessed by people of color are beginning to force organizations across sectors to rethink models of success and how to ensure sustainability in the future. In the environmental sector, organizations are turning attention to diversifying management and leadership to better reflect the constituencies they serve. In order to do this effectively, mainstream environmental organizations must institute readiness, recruitment, and retention (3Rs) practices that integrate diversity, equity and inclusion into their mission and work. In terms of diversity, equity and inclusion, readiness refers to an organization’s capacity and preparedness to foster diverse viewpoints, support employees and partner organizations through inclusive and equitable practices and culture. Recruitment means the active procurement of diverse talent pools, and retention means building meaningful pathways to promotion and building affinity within the organization so that all differences are valued. 3R best practices are the tools by which an organization meets its diversity challenges, especially at the highest levels, and transforms into a truly inclusive work culture. 3R practices are critical to organizations remaining relevant and developing sustainable solutions to our most pressing environmental problems.

Environmental institutions have been working on diversity efforts for the better part of five decades. This report discusses the findings of a study of three types of environmental institutions: 191 conservation and preservation organizations, 74 government environmental agencies, and 28 environmental grant-making foundations. It also reports the findings of interviews conducted with 21 environmental professionals who were asked to reflect on the state of diversity in environmental institutions. The study focuses primarily on gender, racial, and class diversity in these institutions as it pertains to the demographic characteristics of their boards and staff. It examines the recruitment and hiring of new workers as well as the types of diversity initiatives undertaken by the organizations. The report also discusses other kinds of diversities such as cultural, sexual orientation, intergenerational, and rural-urban.

The Inclusive Ecology section was established in the summer of 2016 in order to provide resources and support for all ecologists, regardless of physical/mental ability, gender identity, ethnicity, socioeconomic status, culture, nationality, family status, politics, religion, level of education, or age. During its establishment, concerns were raised that the Ecological Society of America (ESA) and its sections already strive to be inclusive, and that there are already several programs in place to address issues of diversity. Emerging patterns in our national socio-political climate have rendered establishment of this section especially timely. In the spirit of our mission, we are coordinating efforts to engage people from myriad perspectives in collegial conversation with a common goal of advancing ecological science.