Visualization

What are Time Series Made of?

December 10, 2024
Bruno Smaniotto
by Bruno Smaniotto. Trend-cycle decompositions are statistical tools that help us understand the different components of Time Series – Trend, Cycle, Seasonal, and Error. In this blog post, we will provide an introduction to these methods, focusing on the intuition behind the definition of the different components, providing real-life examples and discussing applications.

Cloud SQL Databases for Social Media Data

December 10, 2024, 10:00am
This is a hands-on workshop on analyzing Social Media Data using Cloud Databases, specifically Google Cloud Platform's BigQuery. In this session, you'll learn how to leverage existing Reddit and other publicly available datasets in the cloud, import additional data, and perform meaningful analyses relevant to social science research.

SQL Database Fundamentals for Data Analysis

December 9, 2024, 10:00am
This workshop introduces the fundamentals of SQL, with a focus on using SQLite (the most ubiquitous database on the planet) for data science tasks. We'll explore how SQL can be used to query and manipulate relational databases. This hands-on workshop includes exercises based on real-world datasets.

A Recipe for Reliable Discoveries: Ensuring Stability Throughout Your Data Work

November 19, 2024
Jaewon Saw
by Jaewon Saw. Imagine perfecting a favorite recipe, then sharing it with others, only to find their results differ because of small changes in tools or ingredients. How do you ensure the dish still reflects your original vision? This challenge captures the principle of stability in data science: achieving acceptable consistency in outcomes relative to reasonable perturbations of conditions and methods. In this blog post, I reflect on my research journey and share why grounding data work in stability is essential for reproducibility, adaptability, and trust in the final results.

Python Fundamentals: Parts 1-3

December 9, 2024, 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.

Exploring Rental Affordability in the San Francisco Bay Area Neighborhoods with R

November 5, 2024
Taesoo Song
by Taesoo Song. Many American cities continue to face severe rental burdens. However, we rarely examine rental affordability through the lens of quantitative data. In this blog post, I demonstrate how to download and visualize rental affordability data for the San Francisco Bay Area using R packages like `tidycensus` and `sf`. This exercise shows that mapping census data can be a straightforward and powerful way to understand the spatial patterns of housing dynamics and can offer valuable insights for research, policy, and advocacy.

R Fundamentals: Parts 1-4

December 9, 2024, 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.

R Copilot Assisted Coding Workshop

November 19, 2024, 10:00am
This workshop provides a beginner-friendly introduction to coding with GitHub Copilot, a popular AI coding assistant. We will start from the basics so you can take advantage of AI assistants to improve your coding and avoid common pitfalls. First, we’ll cover how to install and set-up Visual Studio Code, a free code editor through which we will use GitHub Copilot. Then, we will go through the different features of GitHub Copilot and how to use them to help us code in R.

Python Data Visualization: Parts 1-2

November 13, 2024, 9:00am
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

November 5, 2024, 2:00pm
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.