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Category: Data Manipulation in R using the dplyr Package

# Step 1: Install and load the dplyr package
install.packages("dplyr")
library(dplyr)

# Step 2: Load your dataset
data <- read.csv("your_dataset.csv")

# Step 3: View the structure of your dataset
str(data)

# Step 4: Filter rows based on a condition
filtered_data <- data %>% filter(variable_name > threshold_value)

# Step 5: Select specific columns
selected_columns <- data %>% select(column1, column2)

# Step 6: Arrange rows based on a variable
arranged_data <- data %>% arrange(variable_name)

# Step 7: Create a new variable
data_with_new_variable <- data %>% mutate(new_variable = expression)

# Step 8: Group data by a variable
grouped_data <- data %>% group_by(variable_name)

# Step 9: Summarize data within groups
summarized_data <- grouped_data %>% summarise(mean_variable = mean(variable_name))

# Step 10: Combine multiple operations using the pipe (%>%) operator
result <- data %>% 
  filter(variable_name > threshold_value) %>%
  group_by(grouping_variable) %>%
  summarise(mean_variable = mean(variable_name))

Note: Replace "your_dataset.csv," "variable_name," "threshold_value," "column1," "column2," "expression," and "grouping_variable" with appropriate values based on your specific dataset and requirements.