Police Dataset Analysis

This Jupyter Notebook contains an analysis using Pandas DataFrames of a police dataset containing information from January 2005 to December 2012.

Steps:

1. Data Loading: The dataset is loaded from a CSV file using pd.read_csv().

2. Data Cleaning: The column 'country_name' is removed as it contains only missing values.

3. Speeding Analysis: The number of men and women stopped for speeding is compared using value_counts().

4. Search Analysis: The relationship between gender and search conducted during a stop is analyzed using groupby() and sum().

5. Stop Duration Analysis: The mean stop duration is calculated after mapping the duration categories to numerical values.

6. Age Distribution Analysis: The age distributions for each violation are compared using groupby() and describe().

Libraries Used:

• Pandas
• NumPy

Instructions:

• Make sure to have the Police Data.csv file in the specified path.
• Run the notebook cells sequentially to perform the analysis.