Data Analysis on Cars Dataset

This repository contains a Python script for performing data analysis and visualization on a dataset of cars. The analysis includes dataset exploration, statistical summaries, and visualizations to understand the distribution and relationships within the data.

Files in the Repository

• data_analysis_cars.py: Python script for data analysis and visualization.
• cars.csv: Dataset file containing information about cars.
• requirements.txt: List of Python dependencies required to run the script.
• mpg_distribution.png, hp_vs_wt.png, mpg_by_cylinders.png: Output visualization files.

Requirements

To install the required Python libraries, use the requirements.txt file:

pip install -r requirements.txt

Script Overview

The data_analysis_cars.py script:

1. Loads the dataset using Pandas.
2. Cleans data by removing non-ASCII characters from the Model column.
3. Displays dataset information, shape, and a preview.
4. Calculates summary statistics: mean, median, standard deviation.
5. Generates visualizations:
   • Histogram of MPG distribution.
   • Scatter plot of Horsepower vs. Weight by Cylinders.
   • Boxplot of MPG by Cylinders.

How to Run

1. Clone the repository:

   git clone https://github.com/shivamr021/data-decisions-python.git

2. Navigate to the directory:

   cd data-decisions-python

3. Install dependencies:

   pip install -r requirements.txt

4. Run the script:

   python data_analysis_cars.py

Acknowledgments

This project is part of the IBM SkillsBuild Winter Certification Program with CSRBOX. Thanks to IBM and CSRBOX teams for this valuable learning opportunity.