Introduction to R

About This Course

R is one of the leading programming languages for statistics and data analysis. In this introductory class, participants will learn practical skills necessary for reading data into R from external sources, manipulating the data, and visualizing it. The course will also cover other basic programming concepts as they are implemented in R, including data types and structures, variable assignment, functions, and packages.

After your completion of the bootcamp, you will be able to pull data from different sources (small dataset and large datasets), clean and manipulate data more efficiently, automate repetitive data manipulation processes, use rich visualization libraries to deliver your findings as reports and notebooks, and everything from one Open Source platform. Consider it as your analysis swiss-knife in the Data Scientists toolbox.

What You’ll Learn In This Course

You will learn about data wrangling, the art of getting your data into R in a useful form for either further analysis, visualization, and/or modelling. Data wrangling is very important and time consuming: without it you cannot work with your own data! There are three main parts to data wrangling which we will cover in detail:

  • Import
  • Tidy
  • Transform

The course will include the following:

  • Installing and updating R libraries
  • Navigating RStudio Integrated Development Environment (IDE)
  • Understanding different data types working with R
  • Reading/storing data from/in different file types
  • Applying “tidyverse” tools in data processing
    • Organizing tabular data using tidyr functions
    • Transforming data using dplyr functions (filter, summarize, join multiple tables)
    • Transforming and manipulating strings with stringr package
    • Transforming and using different date formats in analysis using lubridate functions
    • Applying grammar of graphics with ggplot2
  • Creating reproducible analysis as notebooks and reports (html and/or pdf) in Rmarkdown
Scroll to Top
Bitnami