How can data be summarized and plotted using Dplyr within a function defined by the user?

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1. Load required libraries:

library(dplyr)
library(ggplot2)

1. Define a function that takes a data frame as input and a column name as the grouping variable:

data_summary <- function(data, group_var){
  # Group Data by the given Grouping Variable
  data %>%
    group_by(!!sym(group_var)) %>%
    summarize(
      mean_val = mean(value),
      median_val = median(value),
      max_val = max(value),
      min_val = min(value)
    ) %>%
    # Create a Boxplot for the Summary Statistics
    ggplot(aes(x = !!sym(group_var), y = value)) +
    geom_boxplot(outlier.shape = NA) +
    geom_jitter(alpha = 0.3) +
    labs(x = group_var, y = "Value")
}

1. The function first groups the data by the specified column ('group_var') and then calculates summary statistics (mean, median, max, and min) for each group using dplyr functions. Finally, the function creates a boxplot of the summary statistics using ggplot2 functions.

2. Test the function with some data:

# Create Sample Data Frame
df <- data.frame(
  group = rep(LETTERS[1:3], each = 20),
  value = rnorm(60)
)

# Call the Function
data_summary(df, "group")

This code creates a sample data frame with 3 groups and 20 observations per group. The 'data_summary' function is then called with this data and the column name 'group' as the grouping variable. The function outputs a boxplot illustrating the summary statistics for each group.