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Tags: data visualization

All Categories (1-20 of 45)

  1. Pratima Jindal

    https://qubeshub.org/community/members/16787

  2. Coding Club: A Positive Peer-Learning Community

    22 Apr 2020 | Teaching Materials | Contributor(s):

    By Gergana Daskalova1, Sandra Angers-Blondin1, John Godlee1, Izzy Rich1, Beverly Tan1, Declan Valters1, Haydn Thomas1, Pedro Miranda1, Gabriela Hajduk1, Kat Keogan1, Isla Myers-Smith1, Kyle Dexter1, Christina Coakley1

    University of Edinburgh

    Free and self-paced tutorials and courses for learning to code out of the University of Edinburgh

    https://qubeshub.org/publications/1816/?v=1

  3. Data Visualization

    23 Mar 2020 | Teaching Materials | Contributor(s):

    By Anna Monfils

    Central Michigan University

    This is an introduction to the idea of data visualization and the importance of presenting data for understanding.

    https://qubeshub.org/publications/1776/?v=1

  4. Communicating with Data: Digital Data Resources

    22 Mar 2020 | Teaching Materials | Contributor(s):

    By Anna Monfils1, Debra Linton1

    Central Michigan University

    Students access, clean, configure, and standardize a dataset and create a relevant and scientifically valid data visualization to communicate science.

    https://qubeshub.org/publications/1779/?v=1

  5. Get Started With GIS in Open Source Python Workshop

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Leah Wasser1, Jenny Palomino1, Joe McGlinchy1

    Earth Lab - University of Colorado, Boulder

    There are a suite of powerful open source python libraries that can be used to work with spatial data. Learn how to use geopandas, rasterio and matplotlib to plot and manipulate spatial data in...

    https://qubeshub.org/publications/1441/?v=1

  6. Writing Clean Code in R Workshop

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Max Joseph1, Leah Wasser

    Earth Lab - University of Colorado, Boulder

    When working with data, you often spend the most amount of time cleaning your data. Learn how to write more efficient code using the tidyverse in R.

    https://qubeshub.org/publications/1442/?v=1

  7. Introduction to Earth Data Science Textbook

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Jenny Palomino, Leah Wasser

    Introduction to Earth Data Science is an online textbook for anyone new to open reproducible science and the Python programming language. There are no prerequisites for this material, and no prior...

    https://qubeshub.org/publications/1440/?v=1

  8. Earth Analytics in R Course

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Leah Wasser

    Earth Lab - University of Colorado, Boulder

    Earth analytics is an advanced, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...

    https://qubeshub.org/publications/1439/?v=1

  9. Earth Analytics Bootcamp Course

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Jenny Palomino1, Leah Wasser

    Earth Lab - University of Colorado, Boulder

    The Earth Analytics Bootcamp is a three-week introductory-level course taught by instructors in Earth Lab and is a part of the Professional Certificate in Earth Data Analytics - Foundations at CU...

    https://qubeshub.org/publications/1438/?v=1

  10. REMNet Tutorial, R Part 4: Creating Taxa Plots in R 5.2.19

    28 Aug 2019 | Teaching Materials | Contributor(s):

    By Jessica Joyner

    CUNY Brooklyn College

    Video on making taxa bar plots in R from the Research Experiences in Microbiomes Network

    https://qubeshub.org/publications/1313/?v=1

  11. Marney Pratt

    https://qubeshub.org/community/members/12436

  12. ClarLynda Williams-DeVane

    https://qubeshub.org/community/members/12061

  13. The nose knows: How tri-trophic interactions and natural history shape bird foraging behavior. Introduction to data visualization.

    28 May 2019 | Teaching Materials | Contributor(s):

    By pamela scheffler

    Students investigate the role of olfaction and infochemicals on bird foraging behavior.. In this module students learn to analyze and present graphic data in ways that simplify interpretation.

    https://qubeshub.org/publications/1221/?v=1

  14. Investigating human impacts on stream ecology: Intro to R

    08 May 2019 | Teaching Materials | Contributor(s):

    By Kristen Kaczynski

    California State University - Chico

    This resource uses the Human Impact on Stream Ecology data set, background and questions and provides students an very general introduction to using R. Students perform basic summary statistics and...

    https://qubeshub.org/publications/1144/?v=1

  15. Histograms and Boxplots

    21 Jan 2019 | Teaching Materials | Contributor(s):

    By Suann Yang

    SUNY Geneseo

    This lesson, created for an introductory ecology course, focuses on helping novice R users to import a data file, apply base R plotting functions, and use R Markdown to generate a reproducible report.

    https://qubeshub.org/publications/1019/?v=1

  16. Caitlin Hicks Pries

    https://qubeshub.org/community/members/10140

  17. Summer Internships in Parallel Computational Science

    Collections | 14 Dec 2018 | Posted by Alycia Crall

    https://qubeshub.org/community/groups/edsin/collections/opportunities-in-the-field

  18. DataCamp

    05 Nov 2018 | Teaching Materials

    DataCamp: The Easiest Way to Learn Data Science Online

    https://qubeshub.org/publications/913/?v=1

  19. Tools: New tools for new science

    30 Oct 2018 | Teaching Materials | Contributor(s):

    By Harry Shum

    Microsoft

    A collection of computational, modeling and data analysis tools developed at Microsoft Research Labs.

    https://qubeshub.org/publications/891/?v=1

  20. Dendroclimatology

    17 Sep 2018 | Teaching Materials | Contributor(s):

    By Jeremy M Wojdak1, R. S. Maxwell1

    Radford University

    Dendroclimatologists can reconstruct climate records further into the past than written records, by examining tree rings. Students "reverse-engineer" this process by considering growth rates of a...

    https://qubeshub.org/publications/544/?v=2