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Python Data Analysis Project

Overview

This project demonstrates a complete data analysis workflow using Python. The steps include setting up the environment, preparing the data, exploring and cleaning the data, analyzing the data, building models (if applicable), and evaluating the results. Make sure to have python and pip installed before attemption the installation below.

Setup

Prerequisites

  • Python 3.12.3
  • pip

Installation

  1. Clone the repository:
    git clone https://github.com/jtwiley1996/Python-Project.git
    cd Python-Project
  2. Create and activate a virtual environment:
    python3 -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
  3. Install the required packages
    pip install pandas matplotlib scikit-learn
  4. Prepare Data

Place your CSV file in the project directory. Ensure it is named data.csv or update the script accordingly.

Running the Analysis

  1. Place your CSV file

Make sure the data.csv file is located in the same directory as data_analysis.py.

  1. Run the script

    python3 data_analysis.py
  2. Output

The script will display the contents of the CSV file, a statistical summary of the data, and data types.

Script Details

data_analysis.py: Reads data.csv, prints the data, shows statistical summaries, and displays data types.

```bash
import pandas as pd

# Load data
data = pd.read_csv('data.csv')

# Display data
print("Data:")
print(data)

# Display statistical summary
print("\nStatistical Summary:")
print(data.describe())

# Display data types
print("\nData Types:")
print(data.dtypes)
```

##Acknowledgements

The pandas library for data manipulation and analysis.

Feel free to modify any section to better fit your project's specifics or personal preferences!