Data Science: R Basics

Chapters

1Getting Started with R and RStudio

2R Language Fundamentals

3Data Types and Structures

Atomic types numeric integer logical character Complex and raw types Vectors lists matrices data frames Type inspection functions Creating atomic vectors Factors vs characters S3 vs S4 vs R6 overview Attributes names dim class Copy on modify semantics Memory vs reference behavior Missing data basics Overview of tibbles Data frame vs tibble differences Subsetting semantics Object size and memory usage

4Vectors and Factors

5Matrices, Arrays, and Lists

6Data Frames and Tibbles

7Importing, Exporting, and Reading Data

8Data Cleaning and Transformation with dplyr

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 Types and Structures

Data Types and Structures

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Understand atomic types and the primary data structures used in R for data analysis.

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Vectors lists matrices data frames

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