R and Tidyverse 1.3.0:-

R, an incredibly powerful and widely-used programming language for statistical analysis and data science and the "tidyverse" collects some of the most versatile R packages.

|>>>> ggplot2, dplyr, tidyr, readr, purrr, and tibble.

How do I use Tidyverse in R studio?

|>>> Install all the packages in the tidyverse by running $ install.packages("tidyverse")  

|>>> Run library(tidyverse) to load the core tidyverse and make it available in your current R session.

Ggplot2   | > install.packages("ggplot2") or load >library(ggplot2)

[ for data visualization. ]  ggplot2 is based on the grammar of graphics, the idea that you can build every graph from the same components: a data set, a coordinate system, and geoms—visual marks that represent data points. 

• Functionality: Geoms, Stats, Scales, Coordinate Systems, Faceting, Position Adjustments, Themes, Zooming, Labels.

dplyr | > install.packages("dplyr") or load >library(dplyr)

[ for data manipulation.] dplyr is one of my all-time favourite packages, the grammar of data manipulation, providing a consistent set of functions work with pipes and expect tidy data.  

• Functionality : select(), filter(), group_by(), summarise(), arrange(), join(), mutate() & combine tables, vector functions and manipulate cases.

tidyr | > install.packages("tidyrlibrary") or load  >library(tidyrlibrary)

[ for data tidying. ] tidyr provides a set of functions that help you get to tidy data. Each variable is in its own column and Each observation, or case, is in its own row. 

• Functionality : gather(), spread(), separate(), unite().

readr | > install.packages("readr") or load >library(readr)

[ for data import. ] Read text files into R with readr, a fast and friendly way to read rectangular data (like csv, tsv, and fwf). 

• Functionality : read_csv(), read_tsv(), read_delim(), read_fwf(), read_table(), read_log(), read tabular/non-tabular data,

 purrr |> install.packages("purrr") or load >library(purrr)

[ for functional programming. ] purrr enhances R’s functional programming (FP) toolkit by providing a complete and consistent set of tools for working with functions and vectors. 

• Functionality: Work with Lists (filter list, summerise list, transform listy, reshape list, join (to)list, reduce lists, modify function behaviour, nested data, list column workflow ]

tibble | > install.packages("tibble") or load >library(tibble)

[ for tibbles, a modern re-imagining of data frames. ] A tibble, or tbl_df, is a modern reimagining of the data.frame. Tibbles inherit the data frame class, but improve three behaviours:

• Functionality: Subsetting df, no partial matching on df, display df.

stringr | > install.packages("stringr") or load >library(stringr)

[ for string. ] stringr package provides a cohesive set of functions designed to make working with strings as easy as possible. 

• Functionality: str_sub(), str_trim(), str_length(), str_to_lower/str_to_upper(), detect matches, subset strings, manage lengths, mutate strings, join and split, order strings, regular expressions.

frocat | > install.packages("frocat") or load >library(frocat)

[ for factors. ] factors to handle categorical variables, variables that have a fixed and known set of possible values.  

• Functionality: fct_reorder(), fct_infreq(), fct_lump(), combine factors, Inspect factors, change the order of levels, change the value of levels, add or drop levels.

For using the tidyverse effectively, the best place to start and practice is R for data science.