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Comparing violations by gender

The question we're trying to answer is whether male and female drivers tend to commit different types of traffic violations.

In this exercise, you'll first create a DataFrame for each gender, and then analyze the violations in each DataFrame separately.

Diese Übung ist Teil des Kurses

Analyzing Police Activity with pandas

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Anleitung zur Übung

  • Create a DataFrame, female, that only contains rows in which driver_gender is 'F'.
  • Create a DataFrame, male, that only contains rows in which driver_gender is 'M'.
  • Count the violations committed by female drivers and express them as proportions.
  • Count the violations committed by male drivers and express them as proportions.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

# Create a DataFrame of female drivers
female = ri[____]

# Create a DataFrame of male drivers
male = ri[____]

# Compute the violations by female drivers (as proportions)
print(female.____)

# Compute the violations by male drivers (as proportions)
print(male.____)
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