Crime_Analysis_Project

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Crime_Analysis_Project

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# Crime Data Analysis Project

This project performs Exploratory Data Analysis (EDA) on a crime dataset using Python, focusing on various aspects of crime statistics and visualizations.

## Features

- Data cleaning and preprocessing
- Multiple visualizations of crime patterns
- Analysis of victim demographics
- Geographical crime distribution
- Temporal crime analysis

## Dependencies

- pandas
- numpy
- matplotlib
- seaborn

## Data Processing

The script performs the following data cleaning steps:
- Standardizes column names
- Converts dates to datetime format
- Extracts year, month, and hour information
- Removes invalid coordinates
- Removes duplicates
- Filters invalid age entries
- Validates victim gender data

## Visualizations

1. **Temporal Analysis**
   - Crime distribution by hour
   - Crimes per year

2. **Crime Categories**
   - Top 10 types of crimes
   - Weapon usage patterns

3. **Victim Demographics**
   - Age distribution
   - Gender distribution

4. **Geographic Analysis**
   - Top 10 areas with highest crime rates

## Output

The script generates multiple visualizations and saves the cleaned dataset as 'cleaned_crime_data.csv'.

## Usage

1. Ensure all required dependencies are installed
2. Place your 'Crime_Dataset.csv' in the project directory
3. Run the script:
```python
python eda_project.py
```

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