rstudio

# Step 1: Install and load required packages
install.packages("tidyverse")
library(tidyverse)

# Step 2: Load the dataset (replace "your_dataset.csv" with the actual file name)
your_dataset <- read.csv("your_dataset.csv")

# Step 3: Explore the structure of the dataset
str(your_dataset)

# Step 4: Summarize the dataset
summary(your_dataset)

# Step 5: Handle missing values (if any)
your_dataset <- na.omit(your_dataset)

# Step 6: Perform data manipulation or analysis as needed
# Example: Create a new variable 'total' by summing two existing variables
your_dataset <- your_dataset %>%
  mutate(total = var1 + var2)

# Step 7: Create visualizations (optional)
# Example: Plot a histogram of the 'total' variable
ggplot(your_dataset, aes(x = total)) +
  geom_histogram(binwidth = 10, fill = "blue", color = "black") +
  labs(title = "Distribution of Total", x = "Total", y = "Frequency")

# Step 8: Save the modified dataset (optional)
# write.csv(your_dataset, "modified_dataset.csv", row.names = FALSE)

Note: Replace "your_dataset.csv" with the actual file name and adapt the data manipulation and visualization steps based on your specific analysis requirements.