Classwork 6

Data Transformation with R

Part 1. filter(), arrange(), and distinct()

For Part 1, consider the nycflights13::flights data.frame.

library(tidyverse)
library(nycflights13)
flights <- flights

For detailed descriptions of the variables in this data frame, load its help documentation using the following command:

# Documentation for the `flights` data.frame from the `nycflights13` package
?flights   # displays the description of variables in the `flights` data.frame

Question 1

• Find all flights that had an arrival delay of two or more hours.
• Find all flights that flew to Houston (IAH or HOU).
• Find all flights that departed in summer (July, August, and September).
• Find all flights that arrived more than two hours late, but did not leave late.

Answer:

Question 2

• How many flights have a missing dep_time?

Answer:

Question 3

• Sort flights to find the most delayed flights.

Answer:

Question 4

• Was there a flight on every day of 2013?

Answer:

Part 2. select() and rename()

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:

Question 2

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

Answer:

Question 3

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

Answer:

Discussion

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