Common data wrangling methods (like filtering, sorting, and adding columns) in JavaScript, Python, SQL, R, and Excel. All examples use mock data.

"This methodology will not find every bug in every program, but it is highly effective for the sort of short programs that beginner programmers are assigned as homework. These techniques then scale up to finding bugs in non-trivial programs."

OpenRefine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.

"an open source textbook aimed at introducing undergraduate students to data science. [...] In this book, we define data science as the study and development of reproducible, auditable processes to obtain value (i.e., insight) from data." Uses R's tidyverse packages and Jupyter notebooks.

Exploratory Desktop provides an advanced, interactive, and reproducible data wrangling and analysis experience powered by R and visualization.

Introduction from the R core team

Swirl teaches you R programming and data science interactively, at your own pace, and right in the R console

Follow the tutorials taught in Data Carpentry to learn R.

"Shiny is a framework for creating web applications using R code. It is designed primarily with data scientists in mind, and to that end, you can create pretty complicated Shiny apps with no knowledge of HTML, CSS, or JavaScript. "

"a list of typical errors and warnings. When clicking on the bullet points of the list, you are headed to detailed instructions on how to deal with the corresponding error or warning message."

"Hundreds of charts are displayed in several sections, always with their reproducible code available. The gallery makes a focus on the tidyverse and ggplot2."

"This lesson is an introduction to programming in Python for people with little or no previous programming experience. It uses plotting as its motivating example [...] This lesson references JupyterLab, but can be taught using a regular Python interpreter as well. Please note that this lesson uses Python 3 rather than Python 2."

Exercise-based guide to coding in Python.

"Full Stack Python is an open book that explains concepts in plain language. "

"Achieve mastery through challenge. Improve your skills by training with others on real code challenges." Suitable for those with some Python experience.

"The Python Package Index (PyPI) is a repository of software for the Python programming language." The documentation for packages is often quite thorough and community forums can be very helpful.

"The Python Graph Gallery is a collection of hundreds of charts made with Python. Each example is accompanied by its corresponding reproducible code along with comprehensive explanations. The gallery offers tutorials that cater to beginners to help kickstart their journey, as well as advanced examples that demonstrate the potency of Python in the realm of data visualization."

"Here you'll find how to get started with Excel — everything from performing simple calculations to making pivot tables to specifying custom print areas and customizing your view."

This is chapter 13, Excel, of Using Microsoft 365 with Windows 8. It provides an illustrated walkthrough of basic Excel features.

Microsoft documentation for Excel. Click "Next: Intro to Excel" to continue tour of Excel features with step-by-step illustrated instructions for Excel 365 on both Windows and Mac.

"You can master Excel by reading these tips and tricks on how to add a drop-down list in an Excel cell to finding duplicates, how to delete blank rows in Excel, and more" List of 83 links to tutorials on common Excel tasks.

LinkedIn Learning video. Use your OU email and password to sign in. Search LinkedIn Learning for similar videos for Excel 2019 and 2016
More information from OU IT on LinkedIn at https://itsupport.ou.edu/TDClient/35/Norman/KB/ArticleDet?ID=13&SIDs=110

LinkedIn Learning, learning path - a series of videos on a specific topic. Use your OU email and password to sign in. More information from OU IT on LinkedIn at https://itsupport.ou.edu/TDClient/35/Norman/KB/ArticleDet?ID=13&SIDs=110

"MATLAB is available to faculty, staff, and students on the Windows, Mac OS X and Linux operating systems. MATLAB is licensed for teaching, learning and academic research and may be installed on university owned and personal machines.
This software is also available to current Earth & Energy students through the Virtual lab."

"The best way to learn how to program is to do something useful, so this introduction to MATLAB is built around a common scientific task: data analysis. Our real goal isn’t to teach you MATLAB, but to teach you the basic concepts that all programming depends on. [...] GNU Octave is a free and open-source alternative to MATLAB which shares its syntax (see more about compatibility). Thus, if you don’t have access to MATLAB, you can easily set up Octave on your computer and still work through the lesson." OU IT provides a campus MATLAB license.

"Get started quickly with the basics of MATLAB." - 2 hour online tutorial that can be accessed using OU's site license for MATLAB.

Use your OU email to log into LinkedIn Learning to watch videos about using SAS.

Provides detailed reference material for using SAS/STAT software to perform statistical analyses, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, nonparametric analysis, mixed-models analysis, and survey data analysis, with numerous examples in addition to syntax and usage information. This document also provides information about the Power and Sample Size Application and extensive information on using ODS Statistical Graphics.

Choose the software you are using and it takes you to documentation and user guides.

"offers an intuitive qualitative data analysis experience that helps you uncover deeper research insights." Available with license through OU IT.

"a free and open-source tool for qualitative research. You can import your research materials, highlight and tag quotes, and export the results!"

Powerful proprietary desktop software for GIS.

Click the blue "Access Software" button on the page. The OU Libraries link on the page is no longer functional as OU has moved to a single-sign-on licensing format for ArcGIS.

Free and open source programming environment. Requires installation of additional packages to enable most GIS applications.

Information and downloads for the Python programming language.

Open source Python 3.7 platform for data science.

A free and open-source GIS software including both a graphical user interface and options for accessing command line resources.

Step-by-step instructions and documentation for ArcGIS software including ArcMap.

Tutorials for ArcGIS produced by the software company. Request an OU-linked ESRI account using the OU licensing link above.

ESRI free video tutorial on scripting with Python for ArcGIS.

Links compiled by QGIS maintainers for QGIS training materials and tutorials in multiple languages.

r-spatial.org is a website and blog for those interested in using R to analyse spatial or spatio-temporal data.

"This book is about using the power of computers to do things with geographic data. It teaches a range of spatial skills, including: reading, writing and manipulating geographic data; making static and interactive maps; applying geocomputation to solve real-world problems; and modeling geographic phenomena."

This page features projects on which OU Libraries has assisted with GIS work and contains a link to the Digital Scholarship Lab for consultations.

Contact a Digital Scholarship specialist for GIS assistance.

A searchable question and answer website for GIS users. If you can't find your answer, you can create a reproducible example and ask your own question.

Well-curated directory with robust searching and filtering capabilities

List of tools for working with datasets

Bioconductor provides tools (in R) for the analysis and comprehension of high-throughput genomic data.

"Qiita (canonically pronounced cheetah) is an entirely open-source microbial study management platform. It allows users to keep track of multiple studies with multiple ‘omics data. Additionally, Qiita is capable of supporting multiple analytical pipelines through a 3rd-party plugin system, allowing the user to have a single entry point for all their analyses. Qiita’s main site provides database and compute resources to the global community, alleviating the technical burdens, such as familiarity with the command line or access to compute power, that are typically limiting for researchers studying microbial ecology. Qiita’s platform allows for quick reanalysis of the datasets that have been deposited using the latests analytical technologies. This means that Qiita’s internal datasets are living data that is periodically re-annotated according to current best practices. "

"Illustrator is ideal when working with logos, complex illustrations, or anything that will appear in a variety of printed formats because the vector graphics will not lose quality when their sizes are altered."

"intended to help researchers learn how to use the free vector-based graphical software Inkscape."