The “summarize” Function in R

• Package: dplyr

• Purpose: To create summary statistics or aggregations of data in a data frame or tibble.

• General Class: Data Manipulation

• Required Argument(s):

• data: The data frame or tibble to summarize.

• Notable Optional Arguments:

• ...: Additional arguments that specify the summary statistics or aggregations to be calculated.

• Example (with Explanation):

• # Load necessary packages
  library(dplyr)
  
  # Create a sample data frame
  data <- data.frame(
  category = c("A", "B", "A", "B", "A"),
  value = c(10, 15, 8, 12, 9)
  )
  
  # Summarize the data by calculating mean and total count for each category
  summary_result <- data %>%
  group_by(category) %>%
  summarize(mean_value = mean(value), count = n())
  
  # Display the summarized data
  print(summary_result)

• In this example, the summarize function from the dplyr package is used to calculate summary statistics for each category in the sample data. The data is grouped by the category variable, and the mean of the value variable and the count of observations in each category are calculated. The result is a summarized data frame providing insights into the distribution of values within each category.