Python Fundamentals Part 2

This four-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.

Part 2 Topics:

  • Lists
  • Loops
  • Conditionals
  • Functions
  • Scope

Knowledge requirements: Python Fundamentals: Part 1 or equivalent prior knowledge

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Python Fundamentals Part 1

This four-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.

Part 1 Topics:

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R Fundamentals Part 4

In the final part, we will review data importation, subsetting, and visualization. Students will then be given the majority of time to reproduce a workflow on two different datasets, ask questions, and review the solutions as a group.

Registration note: To participate in multiple parts of this series, please be sure to register for each day separately.

 

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R Fundamentals Part 3

Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.

Registration note: To participate in multiple parts of this series, please be sure to register for each day separately.

 

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R Fundamentals Part 2

R Fundamentals Part 2: Subsetting and Reshaping

Students will be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Terms like subset, bracket notation, and logical vectors will be defined and reintroduced in Part 2.

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R Fundamentals Part 1

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!

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Geospatial Data in R: Part 3, Raster Data

Geospatial data are an important component 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. 

Geospatial Data in R, part 3: Working with raster data

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Geospatial Data in R: Part 2

Geospatial data are an important component 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. 

Geospatial Data in R, part 2: Geoprocessing and analysis

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Geospatial Data in R: Part 1

Geospatial data are an important component 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. 

Geospatial Data in R, part I: Getting started with spatial data objects

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