Data Wrangling - Tasks

In this section, we will practice data wrangling using R and the dplyr package from the tidyverse. Follow the steps below to manipulate and explore a dataset.

  1. Create a new R script in your scripts folder and name it 2-data-wrangling-and-visualization.R.

  2. Load the tidyverse package by adding the following line at the top of your script:

    library(tidyverse)

  3. Download the crashes file (here) and save it in your data folder.

  4. Read the crashes dataset into R using the read_csv() function and assign it to a variable named crashes:

    crashes <- read_csv("data/crashes.csv")

  5. Explore the dataset:

    • Use the head() function to view the first few rows of the dataset.
    • Use the str() function to understand the structure of the dataset.
    • Use the summary() function to get a summary of the dataset.

  6. Data Wrangling Tasks:

    • Create a new data.frame named crashes_filtered that includes only cyclists.
    • Create a new data.frame named crashes_dark that includes only crashes that occurred in dark conditions.
    • Create a new data.frame named crashes_dark_cyclist that includes only crashes that involved cyclists and occurred in dark conditions.
    • Create a summary table named crashes_by_type that shows the median age by casualty type.

Reuse