• dplyr is an R package for data manipulation, part of the tidyverse.
• It provides a consistent and intuitive set of verbs for working with data frames.

• Fast and efficient for large datasets.
• Works seamlessly with pipes (%>%).
• Easy to read and write code.

Code:

install.packages("dplyr")  # Install the package
library(dplyr)             # Load the package

Note: dplyr is part of the tidyverse, so you can also install it via:

install.packages("tidyverse")
library(tidyverse)

• select(): Select columns.
• filter(): Filter rows based on conditions.
• mutate(): Create or modify columns.
• arrange(): Sort rows.
• summarize(): Aggregate data.
• group_by(): Group data for grouped operations.

Dataset: Use a built-in dataset like mtcars or iris.

Code:

data("mtcars")
head(mtcars)

Purpose: Choose specific columns.

Example:

mtcars %>% select(mpg, hp, wt)

Output: Show the resulting subset of columns.

Purpose: Subset rows based on conditions.

Example:

mtcars %>% filter(mpg > 20, cyl == 4)

Output: Show the filtered rows.

Purpose: Add or modify columns.

Example:

mtcars %>% mutate(kpl = mpg * 0.425)  # Convert mpg to km per liter

Output: Show the new column.

Purpose: Reorder rows.

Example:

mtcars %>% arrange(desc(mpg))  # Sort by mpg in descending order

Output: Show the sorted data.

Purpose: Compute summary statistics.

Example:

mtcars %>% summarize(avg_mpg = mean(mpg), max_hp = max(hp))

Output: Show the summary.

Purpose: Perform operations by group.

Example:

mtcars %>% group_by(cyl) %>% summarize(avg_mpg = mean(mpg))

Output: Show the grouped summary.

Purpose: Chain multiple operations.

Example:

mtcars %>%
  filter(cyl == 6) %>%
  select(mpg, hp) %>%
  arrange(desc(mpg))

Output: Show the final result.

Purpose: Combine datasets.

Key Functions:

• left_join(), right_join(), inner_join(), full_join()

Example:

left_join(df1, df2, by = "key_column")

• Use na.omit() to handle missing data.
• Combine dplyr with ggplot2 for visualization.
• Practice with real-world datasets.

• R for Data Science
• dplyr documentation: ?dplyr
• Online tutorials and cheat sheets.