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LinkedIn Learning

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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