Compute and Add new Variables to a Data Frame in R
In data analysis and manipulation, adding new variables to a data frame is a common task. This allows you to create new insights, summarize data, or prepare it for further analysis. In R, this can be efficiently done using the mutate() function from the dplyr package, but you can also achieve it using base R functions.
Before we delve into computing and adding new variables, let’s create a sample data frame to work with:
# Create a sample data frame
data <- data.frame(
id = 1:5,
name = c("Ali", "Boby", "Charlie", "David", "Eva"),
age = c(25, 30, 35, 40, 45),
score = c(88, 92, 85, 87, 90)
)
# Display the data frame
print(data)
Output:
id name age score
1 1 Ali 25 88
2 2 Boby 30 92
3 3 Charlie 35 85
4 4 David 40 87
5 5 Eva 45 90
How to Add Variables to a Data Frame in R
In data analysis, it is often necessary to create new variables based on existing data. These new variables can provide additional insights, support further analysis, and improve the overall understanding of the dataset. R, a powerful tool for statistical computing and graphics, offers various methods for computing and adding new variables to a data frame. This article will guide you through different approaches to achieve this in R, using built-in functions as well as packages like dplyr.
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