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Extract columns of data frame in R, The pull() function in R’s dplyr package allows users to extract columns from a data frame or tibble.

Extract columns of data frame in R

This article provides two examples of how to apply the pull() function with variable names and indices.

We will also cover the necessary steps to create example data and install/load the dplyr package.

Step 1: Creating Example Data

To demonstrate the usage of the pull() function, we will use the following data frame:

data <- data.frame(x1 = 1:5,
                   x2 = LETTERS[1:5])
print(data)

This data frame contains five rows and two columns (x1 and x2).

Step 2: Installing and Loading the dplyr Package

Before we can use the pull() function, we need to install and load the dplyr package:

install.packages("dplyr")
library("dplyr")

Example 1: Apply pull() Function with Variable Name

In the first example, we will extract the x1 column by specifying its variable name within the pull() function:

pull(data, x1)

The output will be:

1 2 3 4 5

This shows that the pull() function successfully returned the x1 column as a vector.

Example 2: Apply pull() Function with Index

In the second example, we will extract the first column of the data frame by specifying its index within the pull() function:

pull(data, 1)

The output will be:

1 2 3 4 5

This demonstrates that the pull() function can also extract columns using their indices.

Conclusion

The pull() function in R’s dplyr package is a convenient tool for extracting columns from data frames or tibbles.

You can use either the variable name or the index of the column you wish to extract.

Always remember to install and load the dplyr package before using the pull() function.

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