Programming Languages

R Data Wrangling and Manipulation: Parts 1-2

November 1, 2022, 2:00pm
It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful tasks.

Python Geospatial Fundamentals: Parts 1-2

April 2, 2024, 4:00pm
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.

Geospatial Data and Mapping in Python: Parts 1-2

October 5, 2021, 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.

Python Fundamentals: Parts 1-3

September 11, 2023, 2:00pm
This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

R Fundamentals: Parts 1-2 (5pm-8pm)

March 28, 2022, 5:00pm
Evening workshop 5-8pm. This workshop is a two-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio 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.

CANCELED: R Geospatial Fundamentals: Vector Data, Parts 1-2

November 14, 2022, 10:00am
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.

R Fundamentals: Parts 1-4

October 25, 2021, 9:00am
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio 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 Fundamentals: Parts 1-3

October 24, 2023, 2:00pm
This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Python Web Scraping

April 5, 2022, 1:00pm
In this workshop, we cover how to extract data from the web using Python. We focus on two approaches to extracting data from the web: leveraging application programming interfaces (APIs) and web scraping.

Python Text Analysis Fundamentals: Parts 1-2

March 8, 2023, 2:00pm
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.