R CODER

DATA MANIPULATION IN R

Import & export Data transformation String manipulation apply family dplyr
Select columns in R with dplyr

Select columns with dplyr

dplyr

Filter rows in R with dplyr

Filter rows with dplyr

dplyr

Order rows in R with dplyr

Order rows with the arrange() function from dplyr

dplyr

Rename columns in R with dplyr

Rename columns with the rename() function from dplyr

dplyr

Create and modify columns in R with dplyr

Create and modify columns with the mutate() function from dplyr

dplyr

The summarise() function from dplyr

Create statistical summaries with the summarise() function from dplyr

dplyr

Group data by one or more columns with group_by from dplyr

Group data with the group_by() function from dplyr

dplyr

Join data frames in R with left_join and other dplyr joins

Join data frames with dplyr: left_join, inner_join, anti_join and more

dplyr

Create categories with multiple conditions using case_when from dplyr

case_when() and if_else() in dplyr: conditional values

dplyr

Select rows by position or top values with slice from dplyr

Select rows by position with slice() in dplyr

dplyr

Find, count and remove NA values in R

Missing values (NA) : find, count, remove and replace

Data transformation

Remove duplicated rows in R with duplicated and distinct

Remove duplicates with unique(), duplicated() and distinct()

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.