Data Manipulation with data.table in R Course

Name: Data Manipulation with data.table in R
Rating: 4.7 (20 reviews)

Data Manipulation with data.table in R

BasicSkill Level

4.7+

Updated 08/2024

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

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Course Description

The data.table package provides a high-performance version of base R's data.frame with syntax and feature enhancements for ease of use, convenience and programming speed. This course shows you how to create, subset, and manipulate data.tables. You'll also learn about the database-inspired features of data.tables, including built-in groupwise operations. The course concludes with fast methods of importing and exporting tabular text data such as CSV files. Upon completion of the course, you will be able to use data.table in R for a more efficient manipulation and analysis process. Throughout the course you'll explore the San Francisco Bay Area bike share trip dataset from 2014.

Prerequisites

Intermediate R

Introduction to data.table

This chapter introduces data.tables as a drop-in replacement for data.frames and shows how to use data.table's i argument to filter rows.

Welcome to the course!

50 XP

data.table pop quiz

50 XP

Creating a data.table

100 XP

Introducing bikes data

100 XP

Filtering rows in a data.table

50 XP

Filtering rows using positive integers

100 XP

Filtering rows using negative integers

100 XP

Filtering rows using logical vectors

100 XP

Helpers for filtering

50 XP

I %like% data.tables

100 XP

Filtering with %in%

100 XP

Filtering with %between% and %chin%

100 XP

Start Chapter

Selecting and Computing on Columns

Just as the i argument lets you filter rows, the j argument of data.table lets you select columns and also perform computations. The syntax is far more convenient and flexible when compared to data.frames.

Selecting columns from a data.table

50 XP

Selecting a single column

50 XP

Selecting columns by name

100 XP

Deselecting specific columns

100 XP

Computing on columns the data.table way

50 XP

Computing in j (I)

100 XP

Computing in j (II)

100 XP

Advanced computations in j

50 XP

Computing in j (III)

100 XP

Combining i and j

100 XP

Start Chapter

Groupwise Operations

This chapter introduces data.table's by argument that lets you perform computations by groups. By the end of this chapter, you will master the concise DT[i, j, by] syntax of data.table.

Computations by groups

50 XP

Computing stats by groups (I)

100 XP

Computing stats by groups (II)

100 XP

Computing multiple stats

100 XP

Chaining data.table expressions

50 XP

Ordering rows

100 XP

What are the top 5 destinations?

100 XP

What is the most popular destination from each start station?

100 XP

Combining i, j, and by (I)

100 XP

Computations in j using .SD

50 XP

Using .SD (I)

100 XP

Using .SD (II)

100 XP

Start Chapter

Reference Semantics

You will learn about a unique feature of data.table in this chapter: modifying existing data.tables in place. Modifying data.tables in place makes your operations incredibly fast and is easy to learn.

Adding and updating columns by reference

50 XP

Adding a new column

100 XP

Updating an existing column (I)

100 XP

Updating an existing column (II)

100 XP

Grouped aggregations

50 XP

Adding columns by group

100 XP

Updating columns by group

100 XP

Advanced aggregations

50 XP

Adding multiple columns (I)

100 XP

Adding multiple columns (II)

100 XP

Combining i, j, and by (II)

100 XP

Start Chapter

Importing and Exporting Data

Not only does the data.table package help you perform incredibly fast computations, it can also help you read and write data to disk with amazing speeds. This chapter focuses on data.table's fread() and fwrite() functions which let you import and export flat files quickly and easily!

Fast data reading with fread()

50 XP

Fast reading from disk

100 XP

Importing a CSV file

100 XP

Importing selected columns

100 XP

Importing selected rows

100 XP

Advanced file reading

50 XP

Reading large integers

100 XP

Specifying column classes

100 XP

Dealing with empty and incomplete lines

100 XP

Dealing with missing values

100 XP

Fast data writing with fwrite()

50 XP

Writing files to disk

100 XP

Writing date and time columns

100 XP

Fast writing to disk

100 XP

Start Chapter

Data Manipulation with data.table in R

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FAQs

How does data.table compare to dplyr for data manipulation in R?

The data.table package is designed for high-performance operations on large datasets. Its concise syntax can be faster than dplyr, especially for groupwise computations and big data.

What dataset is used throughout the course exercises?

You will work with the San Francisco Bay Area bike share trip dataset from 2014, applying data.table operations to real transportation data across all five chapters.

Does the course cover importing and exporting data with data.table?

Yes. The final chapter teaches fast methods for reading and writing tabular text data such as CSV files using data.table's optimized import and export functions.

What are the main operations I will learn with data.table?

You will learn to filter rows, select and compute on columns, perform groupwise operations, chain expressions together, and use set functions for efficient data manipulation.

Do I need experience with dplyr before taking this course?

No. You only need Intermediate R and Introduction to R. The course teaches data.table as a standalone tool, though familiarity with data frames is helpful.

Join over 19 million learners and start Data Manipulation with data.table in R today!

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Data Manipulation with data.table in R

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Course Description

Prerequisites

Introduction to data.table

Selecting and Computing on Columns

Groupwise Operations

Reference Semantics

Importing and Exporting Data

Earn Statement of Accomplishment

Don’t just take our word for it

FAQs

How does data.table compare to dplyr for data manipulation in R?

What dataset is used throughout the course exercises?

Does the course cover importing and exporting data with data.table?

What are the main operations I will learn with data.table?

Do I need experience with dplyr before taking this course?

Join over 19 million learners and start Data Manipulation with data.table in R today!

Create Your Free Account

Grow your data skills with DataCamp for Mobile

Course Description

Earn Statement of Accomplishment

Don’t just take our word for it

FAQs

What dataset is used throughout the course exercises?

Does the course cover importing and exporting data with data.table?

What are the main operations I will learn with data.table?

Do I need experience with dplyr before taking this course?

Join over .css-nklxlk{color:var(--wf-brand--main, #03EF62);}19 million learners and start Data Manipulation with data.table in R today!

Create Your Free Account

Grow your data skills with DataCamp for Mobile

Join over 19 million learners and start Data Manipulation with data.table in R today!