Programming Languages

Geospatial Data and Mapping in Python: Parts 1-3

March 1, 2022, 2:00pm
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.

Introduction to Bash + Git

October 7, 2021, 10:00am
This workshop will start by introducing you to navigating your computer’s file system and basic Bash commands to remove the fear of working with the command line and to give you the confidence to use it to increase your productivity. And then working with Git, a powerful tool for keeping track of changes you make to the files in a project.

R Geospatial Fundamentals: Vector Data, Parts 1-2

April 5, 2022, 2:00pm
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons.

Stata Fundamentals: Parts 1-3

October 26, 2022, 9:00am
This workshop is a three-part introductory series that will teach you Stata from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the Stata software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

Python Text Analysis: Topic Modeling

April 4, 2024, 10:00am
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

Python Data Visualization Pilot: Parts 1-2

September 6, 2023, 10:00am
For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook.

R Data Visualization with ggplot

October 22, 2021, 10:00am
This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.

Python Text Analysis: Topic Modeling

April 13, 2022, 3:00pm
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

Stata Fundamentals: Parts 1-3

October 10, 2023, 2:00pm
This workshop is a three-part introductory series that will teach you Stata from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the Stata software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

R Geospatial Fundamentals: Raster Data

December 3, 2021, 12:00pm
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping raster data, which typically represents geographic information in a grid of regular sized cells.