Manipulate your data. Data wrangling - R programmning for beginners

This video tutorial covers various data manipulation techniques using the Tidyverse package in R. It begins with an introduction to Tidyverse and its installation, followed by lessons on renaming and reordering variables, changing variable types, and filtering and arranging data. The tutorial also explores conditional changes using the ifelse function and demonstrates how to reshape data from wide to long format. Each section provides practical examples and tips to enhance data manipulation skills in R.

What is the primary purpose of the Tidyverse library?

• To manage databases

• To perform data manipulation and analysis

• To write machine learning algorithms

• To create visualizations

Which function is used to rename a variable in Tidyverse?

• filter

• rename

• select

• mutate

How can you reorder variables in a dataset using Tidyverse?

• Using the arrange function

• Using the select function

• Using the mutate function

• Using the filter function

What is the purpose of the 'as.factor' function in R?

• To convert a variable to a logical type

• To convert a variable to a numeric type

• To convert a variable to a character type

• To convert a variable to a factor type

Which function allows you to select variables based on their names or positions?

• arrange

• mutate

• select

• filter

What does the 'filter' function do in Tidyverse?

• It selects specific rows based on conditions

• It creates new variables

• It selects specific columns

• It changes the type of a variable

How can you change the content of a variable using Tidyverse?

• Using the filter function

• Using the mutate function

• Using the arrange function

• Using the select function

What is the purpose of the 'pivot_wider' function?

• To filter data

• To convert data from wide to long format

• To convert data from long to wide format

• To arrange data

Which function would you use to convert a dataset from long to wide format?

• select

• mutate

• pivot_wider

• pivot_longer

What is a key benefit of reshaping data from long to wide format?

• It reduces the number of rows

• It enhances data security

• It increases the number of columns

• It simplifies data visualization