How to install data.table library and to use data.table instead of data.frame in R

This recipe helps you install data.table library and to use data.table instead of data.frame in R

Recipe Objective

R programming language struggles while dealing with large data sets. Most of the dataset contains more than 400,000 rows and Rstudio takes hours to execute one line of code. This language is does not efficiently uses memory to load big datasets as it loads everything to RAM at once. ​

To overcome this problem, Matt Dowle wrote "data.table" package in 2008. This package is mainly designed to avoid the above problem by being concise and painless. It is an advanced version of data.frame which enhances the data.frame. It even works well when data.frame syntax is used. The syntax is quite similar to SQL.

Explore the Must Know Python Libraries for Data Science and Machine Learning.

Syntax: DT[i , j, by = ] ​

where (DT refers to the data.table): ​

  1. i = (equivalent to where clause in SQL) you put the row condition out here
  2. j = (equivalent to select clause in SQL) you put the column conditions out here
  3. by = (equivalent to group by clause in SQL) where you put any categorical variable on which grouping needs to take place.

The reasons why you should use data.table instead of data.frame are: ​

  1. It provides an alternative way to load the data faster by using fread() function
  2. It is considered to be faster in than dplyr package for data manipulation tasks such as aggregating, merging and grouping
  3. It also provides a faster way to write files by using fwrite() function
  4. It enhances the user experience by having in-built automatic indexing, overalapping joins and rolling joins

To use this package you, first need to install and load the package as it's not an in-built one. ​

install.packages(data.table)

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