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Learn Logical Indexing | Data Frames
R Introduction

bookLogical Indexing

Logical indexing allows you to filter rows of a data frame based on conditions. Instead of remembering row numbers, you specify logical expressions, and only rows where the condition is TRUE are returned.

Example

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name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) # People older than 30 test[test$age > 30, ] # Males only test[test$gender == 'M', ]
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The condition should be placed in the row index position inside square brackets ([condition, ]).

Task

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Using the mtcars dataset, extract the following data:

  1. The cars that pass a quarter-mile in less than 16 seconds (qsec column).
  2. Cars with 6 cylinders (cyl column).

Solution

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SectionΒ 5. ChapterΒ 4
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bookLogical Indexing

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Logical indexing allows you to filter rows of a data frame based on conditions. Instead of remembering row numbers, you specify logical expressions, and only rows where the condition is TRUE are returned.

Example

123456789
name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) # People older than 30 test[test$age > 30, ] # Males only test[test$gender == 'M', ]
copy

The condition should be placed in the row index position inside square brackets ([condition, ]).

Task

Swipe to start coding

Using the mtcars dataset, extract the following data:

  1. The cars that pass a quarter-mile in less than 16 seconds (qsec column).
  2. Cars with 6 cylinders (cyl column).

Solution

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Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 5. ChapterΒ 4
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