Adding New Variables Using data.table
The data.table package is another powerful tool for data manipulation in R, known for its speed and efficiency.
1. Using := Operator
The := operator in data.table is used to add or modify columns by reference.
# Load data.table package
library(data.table)
# Convert data frame to data.table
data <- as.data.table(data)
# Add new variables using :=
data[, pass_new := ifelse(score >= 90, "Pass", "Fail")]
data[, age_decade := floor(age / 10) * 10]
# Display the updated data table
print(data)
Output:
id name age score pass age_group score_category score_double age_category
1: 1 Ali 25 88 No Young Medium 176 Youth
2: 2 Boby 30 92 Yes Young High 184 Adult
3: 3 Charlie 35 85 No Old Medium 170 Adult
4: 4 David 40 87 No Old Medium 174 Adult
5: 5 Eva 45 90 Yes Old High 180 Senior
pass_new age_decade
1: Fail 20
2: Pass 30
3: Fail 30
4: Fail 40
5: Pass 40
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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