</>
Skip to content
R lessons (40/41)

R — dplyr

filter

library(dplyr)
data %>% filter(age > 25)

select

data %>% select(name, age)

mutate

data %>% mutate(age_next = age + 1)

arrange

data %>% arrange(desc(age))

summarize

data %>% summarize(avg_age = mean(age))

Mini Practice

  1. Filter data
  2. Select columns
  3. Add new columns
  4. Summarize data

Up Next

Continue with tidyr - Data tidying.

Related Topics

ggplot2tidyr

Frequently Asked Questions about dplyr

What is dplyr in R?

dplyr is a fundamental concept in R. This lesson explains it step by step with clear examples, making it easy for beginners to understand.

How do I learn dplyr?

Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn dplyr.

Why is dplyr important in R?

dplyr is essential for R development. Understanding this concept will help you write better code and solve real-world problems more effectively.