R

Tom van Nuenen, Ph.D.

Consulting Drop-In Hours: By appointment only

Consulting Areas: Python, R, SQL, LaTeX, HTML / CSS, Javascript, Julia,Data Manipulation and Cleaning, Data Science, Data Visualization, Digital Humanities, Machine Learning, Mixed Methods, Natural Language Processing, Python Programming, Qualitative methods, R Programming, Surveys, Sampling & Interviews, Text Analysis, Web Scraping,Regression Analysis,Bash or Command Line, Excel, Gephi, Git or Github, NVivo, Qualtrics, RStudioFairness, Perceptions of AI, Hermeneutics

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R Data Visualization

February 16, 2023, 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.

Aaron Culich

Consulting Drop-In Hours: By appointment only

Consulting Areas: Python, R, SQL, APIs, Cloud & HPC Computing, Databases & SQL, Bash or Command Line, Git or Github

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R Fundamentals: Parts 1-4

January 24, 2023, 2:00pm
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 Geospatial Fundamentals: Vector Data, Parts 1-2

February 16, 2023, 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 Geospatial Fundamentals: Raster Data

February 23, 2023, 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 raster data, which typically represents geographic information in a grid of regular sized cells.

R Machine Learning with tidymodels: Parts 1-2

February 22, 2023, 1:00pm
Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. During this two part workshop, we will discuss basic features of supervised machine learning algorithms including k-nearest neighbor, linear regression, decision tree, random forest, boosting, and ensembling using the tidymodels framework. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.

R Data Wrangling and Manipulation: Parts 1-2

February 9, 2023, 10:00am
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.

Peter Amerkhanian

Graduate Student Researcher (GSR), Instructor
Goldman School of Public Policy (GSPP)

I’m a D-Lab GSR and a graduate student in The Goldman School’s Master of Public Policy/The I School’s Graduate Certificate in Applied Data Science. I have 5 years of experience working on data problems in government and nonprofits. I’m interested in social policy, program evaluation, and computational methods. Python is my principal language, but I’ve developed experience using and teaching a variety of other tools, including R, Excel, Tableau, and JavaScript. I deeply enjoy teaching data science methods and am excited to be a part of the D-Lab.

R Fundamentals: Parts 1-4

January 10, 2023, 2:00pm
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.