select() and rename()

Classwork 6

For this Classwork 6, consider the following data.frame, nyc_payroll_new.

library(tidyverse)
nyc_payroll_new <- read_csv("https://bcdanl.github.io/data/nyc_payroll_2024.csv")

For detailed descriptions of the variables in this data.frame, please refer to the following link: Citywide Payroll Data (Fiscal Year)

Question 1

Create a new data.frame, df that keeps only the following five variables—Fiscal_Year, Agency_Name, First_Name, Last_Name, and Base_Salary—from the data.frame nyc_payroll_new.

Answer:

Here, we use the select() function from one of the packages in tidyverse to choose only the specified variables (Fiscal_Year, Agency_Name, First_Name, Last_Name, and Base_Salary) from the nyc_payroll_new data.frame. The result is assigned to a new data.frame name df containing only these variables, reducing the dataset for further analysis.

Question 2

Given the data.frame df with a variable named Agency_Name, how would you rename it to Agency?

Answer:

The rename() function allows us to change the name of an existing variable. In this case, we rename the Agency_Name variable to Agency in the df data.frame. The result is a new data.frame, df_renamed, where Agency_Name is now simply Agency.

Question 3

How would you remove the Fiscal_Year variable using select()?

Answer:

To remove a column from a data.frame, we use the select() function with the - sign before the variable name. In this case, select(-Fiscal_Year) removes the Fiscal_Year variable from the df data.frame, resulting in df_dropped, which contains all variables except Fiscal_Year.

Discussion

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