Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Logical Indexing | Data Frames
R Introduction: Part II

bookLogical Indexing

Good! Accessing columns by their names is convenient. Can we filter the rows we want to output?

Indeed, we can. First, we can use indices (like it was for vectors or matrices). But usually, we do not know the positions of the rows but know some conditions we want to satisfy. For example, we may want to extract data for only Males or only people older than 30. You can do it by specifying necessary conditions within square brackets. You need to use the double sign == for equality.

Assume we have data frame data and want to filter to rows having the value 30 in column age. This can be done using the following syntax: data[data$age == 30,]. Note that you put condition as the first index within the square bracket. For example, for the same training data as before, let's extract the data of people older than 30 and males only.

# Data
name <- c("Alex", "Julia", "Finn")
age <- c(24, 43, 32)
gender <- c("M", "F", "M")
# Creating a data frame
test <- data.frame(name, age, gender)

# People older than 30
test[test$age > 30, ]
# Males only
test[test$gender == 'M', ]
1234567891011
# Data name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") # Creating a data frame test <- data.frame(name, age, gender) # People older than 30 test[test$age > 30, ] # Males only test[test$gender == 'M', ]
copy

As you can see, that's correct.

Завдання
test

Swipe to show code editor

Using the mtcars dataset, extract the following data:

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

Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Секція 2. Розділ 4
# Extract the 'fastest' cars
___
# Extract the cars with 6 cylinders
___
toggle bottom row
some-alt