Data Science: R Basics

Chapters

1Getting Started with R and RStudio

2R Language Fundamentals

3Data Types and Structures

4Vectors and Factors

5Matrices, Arrays, and Lists

6Data Frames and Tibbles

7Importing, Exporting, and Reading Data

8Data Cleaning and Transformation with dplyr

Introduction to tidyverse The pipe operator select to choose columns filter to subset rows arrange to sort rows mutate to add transform columns transmute to keep new columns only summarise and across group by and ungroup window functions joins inner left right full semi and anti joins bind rows and bind cols case when and if else rowwise operations

9Reshaping Data with tidyr

10Working with Dates, Strings, and Categories

11Exploratory Data Analysis and Visualization with ggplot2

12Control Flow, Functions, and Apply Family

13Reproducibility, Projects, and Packages

14Basics of Statistical Modeling in R

15Working with Larger Data and Performance

Courses/Data Science: R Basics/Data Cleaning and Transformation with dplyr

Data Cleaning and Transformation with dplyr

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Transform, filter, summarize, and join data using a consistent grammar.

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Introduction to tidyverse

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