Crime Data Analysis Project

Project Overview

This project analyzes crime data from Jefferson County, KY, spanning the years 2020 to 2024. The main focus is on processing, cleaning, and visualizing crime data, specifically related to auto thefts. The analysis merges crime data with ZIP code information and standardizes fields to prepare the data for insights and reporting.

The motivation for this project stems from a personal experience: my vehicle was stolen during the first week of December 2024. I became curious about the rates of theft, how common this was in my area, and quickly decided to structure my project around this issue.

Data Sources

• Crime Data: Raw crime data from 2020 to 2024 provided in CSV format.

• https://data.louisvilleky.gov/datasets/LOJIC::louisville-metro-ky-crime-data-2020/about

• https://data.louisvilleky.gov/datasets/LOJIC::louisville-metro-ky-crime-data-2021/about

• https://data.louisvilleky.gov/datasets/LOJIC::louisville-metro-ky-crime-data-2022/about

• https://data.louisvilleky.gov/datasets/LOJIC::louisville-metro-ky-crime-data-2023/about

• https://data.louisvilleky.gov/datasets/LOJIC::louisville-metro-ky-crime-data-2024/about

• ZIP Codes: ZIP code data for filtering relevant locations (Jefferson County, KY).

• https://www.unitedstateszipcodes.org/zip-code-database/

Feature 1: Read TWO data files (JSON, CSV, Excel, etc.).

File Structure

• main.py: The main script that orchestrates data processing.

• preprocessing.py: Contains modular functions for loading, cleaning, and processing data.

• data/raw_data/: Folder containing raw crime data files.

• data/processed_data/: Folder containing processed data outputs.

Feature 2: Clean your data and perform a pandas merge with your two data sets, then calculate some new values based on the new data set.

Steps to Reproduce

1. Clone the repository:

open new Git bash terminal in code editor

git clone https://github.com/matthewlondon/Capstone.git

2. Set up a virtual environment:

cd Capstone

python -m venv venv

source venv/bin/activate

if using Windows:

source venv/Scripts/activate

Feature 4: Utilize a virtual environment and include instructions in your README on how the user should set one up.

3. Install dependencies:

pip install -r requirements.txt

4. Run the main.py script:

python src/main.py

5. Open the exploration.ipynb file:

6. Run all scripts to view matplot and seaborn visualizations:

• Most Common Days for Reported Auto Thefts
• Auto Theft Trends Over the Years
• Top 10 ZIP Codes for Auto Thefts
• Trends by Day of Week and Top 10 Locations
• Yearly Trends by ZIP Code
• Personal Analysis of My Car Theft Incident
• Incidents per 100 People by ZIP Code

May encounter "cannot resolve (library) from source. Check if python interpreter is Python or venv(python). If not venv(python), attempt to select kernel. If no venv(python) is in the drop down, clear cache and reload the window. In VSCode, use Ctrl + Shift + p, and search "Python: Clear Cache and Reload Window" then select kernel as venv(python).

Feature 3: Make 3 matplotlib or seaborn (or another plotting library) visualizations to display your data.

Processed Data Outputs

• cleaned_crime_data.csv: Contains the cleaned and processed crime data.
• jefferson_zip_df.csv: Contains filtered ZIP code data for Jefferson County, KY.

Data Dictionary

Cleaned Crime Data

Column Name	Description	Data Type
zip	ZIP code of the crime location.	String
incident_number	Unique identifier for each incident.	String
date_reported	Date when the crime was reported.	DateTime
date_occurred	Date when the crime occurred.	DateTime
offense_classification	Standardized offense classification (e.g., AUTO THEFT).	Category
location_category	Category describing the crime location.	Category
was_offense_completed	Whether the offense was completed (YES/NO/UNKNOWN).	Category
value_range	Estimated monetary range associated with the offense.	Category
week_day_reported	Day of the week the crime was reported.	Category
week_day_occurred	Day of the week the crime occurred.	Category

Jefferson County ZIP Data

Column Name	Description	Data Type
zip	ZIP codes in Jefferson County, KY.	Integer
latitude	Coordinates	Float
longitude	Coordinates	Float
irs_estimated_population	2020 population estimates based on exemption filings	Integer

Visualizations

- Most Common Days for Reported Auto Thefts
- Auto Theft Trends Over the Years
- Top 10 ZIP Codes for Auto Thefts
- Trends by Day of Week and Top 10 Locations
- Yearly Trends by ZIP Code
- Personal Analysis of My Car Theft Incident
- Incidents per 100 People by ZIP Code

Contact

Matthew London - mmatthewlondon@gmail.com