Published - Sat, 15 Apr 2023

Working with Airline Safety Data

Working with Airline Safety Data

Title: Working with Airline Safety Data

Introduction: In this lecture, we will learn how to work with the airline_safety data frame included in the fivethirtyeight data package. We will explore the data, clean it up, and convert it into a tidy format using R programming language.

Step 1: Load the dataset We start by loading the airline_safety dataset using the following command:

scss
library(fivethirtyeight)
data("airline_safety")

Step 2: Exploring the dataset We can use the head() and summary() functions to get a quick overview of the dataset.

scss
head(airline_safety)
summary(airline_safety)

Step 3: Cleaning the dataset We will remove the incl_reg_subsidiaries and avail_seat_km_per_week columns from the dataset using the select() function from the dplyr package.

scss
library(dplyr)
airline_safety_smaller <- airline_safety %>% 
  select(-c(incl_reg_subsidiaries, avail_seat_km_per_week))

Step 4: Converting to Tidy Format The current format of the data frame is not tidy. We can convert it to tidy format using the tidyr package.

scss
library(tidyr)
airline_safety_tidy <- airline_safety_smaller %>% 
  pivot_longer(
    cols = c(
      incidents_85_99, fatal_accidents_85_99, fatalities_85_99,
      incidents_00_14, fatal_accidents_00_14, fatalities_00_14
    ),
    names_to = "incident_type_years",
    values_to = "count"
  )

Step 5: Viewing the Tidy Dataset We can use the head() function to view the first few rows of the tidy dataset.

scss
head(airline_safety_tidy)

Conclusion: In this lecture, we learned how to work with the airline_safety data frame using R programming language. We explored the dataset, cleaned it up, and converted it to tidy format. The resulting dataset is easier to work with and can be used for further analysis.

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Robert Kotaki

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