Session Ready
Exercise

Comparing speeding outcomes by gender

When a driver is pulled over for speeding, many people believe that gender has an impact on whether the driver will receive a ticket or a warning. Can you find evidence of this in the dataset?

First, you'll create two DataFrames of drivers who were stopped for speeding: one containing females and the other containing males.

Then, for each gender, you'll use the stop_outcome column to calculate what percentage of stops resulted in a "Citation" (meaning a ticket) versus a "Warning".

Instructions
100 XP
  • Create a DataFrame, female_and_speeding, that only includes female drivers who were stopped for speeding.
  • Create a DataFrame, male_and_speeding, that only includes male drivers who were stopped for speeding.
  • Count the stop outcomes for the female drivers and express them as proportions.
  • Count the stop outcomes for the male drivers and express them as proportions.