Programming Languages

Bash + Git: Introduction

October 19, 2022, 2:00pm
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.

Python Data Wrangling and Manipulation with Pandas (5pm-8pm)

March 29, 2022, 5:00pm
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

Git for Research Transparency and Reproducibility Training (RT2)

June 6, 2024, 3:15pm
This is a custom Git workshop for the 2024 Research Transparency and Reproducibility Training (RT2).

Stata for Research Transparency and Reproducibility Training (RT2)

June 7, 2024, 3:15pm
This is a custom Stata workshop for the 2024 Research Transparency and Reproducibility Training (RT2).

Processing Videos in Python with OpenCV

November 28, 2023
Leah Lee
by Leah Lee. Videos and images are quickly becoming the most common type of data we store and interact with. Computer vision technologies derive useful information from these forms of data and are now commonly used in health care, agriculture, transportation, and security. OpenCV is a powerful tool for image processing and computer vision tasks. In this blog post, we will explore how we can use OpenCV in Python to carry out basic computer vision tasks. Specifically, we’ll focus on the simple task of identifying an object from a video and labeling a frame with a box around the object.

Mapping Census Data with tidycensus

November 6, 2023
Alex Ramiller
by Alex Ramiller. The U.S. Census Bureau provides a rich source of publicly available data for a wide variety of research applications. However, the traditional process of downloading these data from the census website is slow, cumbersome, and inefficient. The R package “tidycensus” provides researchers with a tool to overcome these challenges, enabling a streamlined process to quickly downloading numerous datasets directly from the census API (Application Programming Interface). This blog post provides a basic workflow for the use of the tidycensus package, from installing the package and identifying variables to efficiently downloading and mapping census data.

Using Forest Plots to Report Regression Estimates: A Useful Data Visualization Technique

October 17, 2023
Sharon Green
by Sharon Green. Regression models help us understand relationships between two or more variables. In many cases, results are summarized in tables that present coefficients, standard errors, and p-values. Reading these can be a slog. Figures such as forest plots can help us communicate results more effectively and may lead to a better understanding of the data. This blog post is a tutorial on two different approaches to creating high-quality and reproducible forest plots, one using ggplot2 and one using the forestplot package.

Using Artificial Intelligence to Help Write Code

February 28, 2023
Daniel Tan
by Daniel Tan. ChatGPT is a natural language processing model that has applications in a wide variety of research settings. It is a chatbot-style tool that was created by OpenAI using a deep learning model that allows it to generate human-like responses to a wide variety of questions and prompts spanning a multitude of topics. Because it has been trained on a large body of text, ChatGPT is a particularly useful tool for programming. This post explores ways to use ChatGPT to help write code in Stata, a statistical software package that is widely used in academic and policy research.

A Brief Introduction to Cloud Native Approaches for Big Data Analysis

March 20, 2023
Millie Chapman
by Millie Chapman. Satellites, smart phones, and other monitoring technologies are creating vast amounts of data about our earth every day. These data hold promise to provide global insights on everything from biodiversity patterns to human activity at increasingly fine spatial and temporal resolution. But leveraging this information often requires us to work with data that is too big to fit in our computer's "working memory" (RAM) or even to download to our computer's hard drive. In this post, I walk through tools, terms, and examples to get started with cloud native workflows. These workflows allow us to remotely access and query large data from online resources or web services, all while skipping the download step!

James Hall

Consultant
Department of Statistics

James Hall is a graduate student in the Statistics MA program at University of California, Berkeley. He is a husband and father to three awesome kids. Originally from Baltimore, MD, James earned his bachelors in Mathematics at the United States Military Academy at West Point, NY in 2011, and served as a U.S. Army officer. He’s served as a leader at multiple levels within large organizations with a professional focus on visualizing and communicating complex analysis to decision makers. James’ experience and coursework give him expertise in navigating different statistical methods,...