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R Essential Training: Wrangling and Visualizing Data

via LinkedIn Learning

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Overview

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Learn how to wrangle data and create meaningful visualizations with R, the programming language powering modern data science.

Syllabus

Introduction

Make your data make sense
Using the exercise files

1. What Is R?

R in context
Data science with R: A case study

2. Getting Started

Installing R
Environments for R
Installing RStudio
Navigating the RStudio environment
Entering data
Data types and structures
Comments and headers
Packages for R
The tidyverse
Piping commands with %>%

3. Importing Data

R's built-in datasets
Exploring sample datasets with pacman
Importing data from a spreadsheet
Importing XML data
Importing JSON data
Saving data in native R formats

4. Visualizing Data with ggplot2

Introduction to ggplot2
Using colors in R
Using color palettes
Creating bar charts
Creating histograms
Creating box plots
Creating scatterplots
Creating multiple graphs
Creating cluster charts

5. Wrangling Data

Creating tidy data
Using tibbles
Using data.table
Converting data from wide to tall and from tall to wide
Converting data from tables to rows
Working with dates and times
Working with list data
Working with XML data
Working with categorical variables
Filtering cases and subgroups

6. Recoding Data

Recoding categorical data
Recoding quantitative data
Transforming outliers
Creating scale scores by counting
Creating scale scores by averaging

Conclusion

Next steps

Taught by

Barton Poulson

Reviews

4.7 rating at LinkedIn Learning based on 452 ratings

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