R CODER

DATA MANIPULATION IN R

Import & export Data transformation String manipulation apply family dplyr
Reshape data from wide to long with pivot_longer in R

Reshape data with pivot_longer() and pivot_wider() from tidyr

Data transformation

The table() and prop.table() functions in R

Tables with table() and prop.table()

Data transformation

Remove leading and trailing whitespaces in R with trimws()

Remove leading and trailing whitespaces with trimws()

String manipulation

Lowercase and uppercase in R with tolower(), toupper() and chartr()

Lowercase and uppercase with tolower() and toupper()

String manipulation

The substring() and substr() functions in R

Extract and replace substrings with substring() and substr()

String manipulation

rbind() and cbind() functions in R

rbind() and cbind() functions

Data transformation

The strsplit() function in R

Split strings with strsplit()

String manipulation

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

¿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.