R CODER

DATA MANIPULATION IN R

Import & export Data transformation String manipulation apply family dplyr
Web scraping in R

Web scraping with rvest

Import and export data

Pattern matching in R

Pattern matching with grepl() and grep()

String manipulation

Pattern matching and replacement in R

Pattern matching and replacement with gsub() and sub()

String manipulation

colSums, rowSums, colMeans and rowMeans functions in R

Row and column sums and means

Data transformation

Row and column names in R

Row and column names

Data transformation

Concatenate strings in R with paste and paste0 functions

Concatenate strings with paste and paste0

String manipulation

The nchar function in R

Count the number of characters with nchar

String manipulation

Read SQL databases in R

Read SQL databases

Import and export data

Learn how to use the lapply function in R programming language

lapply function

apply family

Read Excel file sheets into R

Read Excel files

Import and export data

Join data frames in R with the merge function

Merge data frames

Data transformation

Learn how to use the aggregate function in R

Aggregate

Data transformation

¿What is DATA MANIPULATION?

Data manipulation, also known as data wrangling, refers to the process of transforming and cleaning raw data into a structured format suitable for analysis. This process involves various operations such as filtering, sorting, aggregating, merging, reshaping, and transforming data to make it more organized, understandable, and ready for analysis. R provides several functions to perform these tasks, but dplyr is one of the most popular and widely used R packages for data manipulation.

  1. Base R

    Data manipulation in base R involves using the core functions and methods provided by R's base package for handling, transforming, and manipulating data structures such as vectors, matrices, arrays, data frames, and lists.

  2. dplyr

    dplyr is an R package designed for efficient and user-friendly data manipulation. It provides a set of functions that streamline data wrangling tasks by offering a consistent grammar for manipulating data frames and data tables.