shru14 / 01-wrangling-dreyer-ramirez-kakade

Data Wrangling with janitor and forcats

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Cleaning and wrangling data with janitor and forcats

Summary

This repository provides materials for a session that is part of the I2DS Tools for Data Science workshop run at the Hertie School, Berlin in October 2023. The student-run workshop is part of the course Introduction to Data Science taught by Simon Munzert at the Hertie School, Berlin, in Fall 2023.

Session contents

This session will introduce you to the intricacies of factor management with R using the "forcats" package, as well as data cleaning and tidying with the "janitor" package. Both packages are essential for efficient data manipulation and ensuring clean and consistent datasets.

Main learning objectives

The goals of this session are to:

  1. Equip you with conceptual knowledge about the "forcats" and "janitor" packages.
  2. Demonstrate various functions and utilities provided by both packages.
  3. Provide you with practice material on how to efficiently wrangle and clean data with both packages.

Instructors

Further resources

License

The material in this repository is made available under the MIT license.

Statement of contributions

Elena Dreyer prepared the presentation slides for "forcats" and contributed to the practice material.

Luis Fernando Ramirez Ruiz prepared the presentation slides for "janitor" and contributed to the practice material.

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Data Wrangling with janitor and forcats

License:MIT License


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