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Data Analysis with Python: Police Dataset

This repository contains a data analysis project in Python focused on exploring and analyzing a police dataset. The project employs various data manipulation, cleaning, and analysis techniques using pandas and other Python libraries.

Overview

In this project, we delve into a real-world police dataset, examining traffic stop data to uncover insights related to gender disparities, violation distributions, and stop durations. The analysis involves data cleaning, filtering, and grouping methods to derive meaningful conclusions.

Project Structure

  • data/: Folder containing the dataset used for analysis.
  • notebooks/: Jupyter notebooks with step-by-step analysis.
  • src/: Source code and scripts used in the analysis.
  • results/: Directory for storing visualizations and findings.

Key Techniques Used

  • Data cleaning and preprocessing
  • Filtering and value counts
  • Grouping and summarizing data
  • Mapping and datatype manipulation
  • Statistical analysis and visualization

Getting Started

  1. Clone the repository:

    git clone https://github.com/username/DataScience_Project3_PoliceDataset_Analysis.git

  2. Navigate to the project directory:

    cd DataScience_Project3_PoliceDataset_Analysis

  3. Explore the Jupyter notebooks in the notebooks/ directory for detailed analysis steps.

Feel free to explore, contribute, or reach out with any feedback or questions!