https://github.com/amid68/ford-gobike-data-exploration

An exploratory data analysis (EDA) of the Ford GoBike System dataset.
https://github.com/amid68/ford-gobike-data-exploration

Last synced: 5 months ago
JSON representation

An exploratory data analysis (EDA) of the Ford GoBike System dataset.

• Host: GitHub
• URL: https://github.com/amid68/ford-gobike-data-exploration
• Owner: Amid68
• License: mit
• Created: 2024-09-07T14:33:19.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-07T14:36:28.000Z (almost 2 years ago)
• Last Synced: 2025-02-24T14:42:06.292Z (over 1 year ago)
• Size: 626 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Ford GoBike Data Exploration

## Project Overview

This project is an exploratory data analysis (EDA) of the **Ford GoBike System** dataset from February 2019, consisting of over 183,000 bike trips in the San Francisco Bay Area. The goal is to uncover insights about trip durations, user demographics, and patterns of bike-sharing behavior through various univariate, bivariate, and multivariate visualizations.

## Tools & Libraries Used

- **Python**

- **Pandas**

- **NumPy**

- **Matplotlib**

- **Seaborn**

- **Jupyter Notebook**

## Key Features Explored

1. **Univariate Exploration**: 

   - Distribution of trip durations, user types, and user age.

2. **Bivariate Exploration**:

   - Relationships between trip duration and user type, gender, and age.

3. **Multivariate Exploration**:

   - Combined insights on trip duration, gender, and user type using facet grids and plot matrices.

## Key Insights

- **Subscribers** tend to take shorter, more consistent trips compared to **Customers**.

- **Male** users dominate the dataset, but **Female** users tend to have slightly longer trip durations.

- There is no strong correlation between **age** and trip duration, although younger users tend to take more trips.

## Conclusion

The analysis revealed meaningful insights into the behaviors and demographics of the Ford GoBike users, highlighting differences between subscribers and customers, gender usage patterns, and trip duration trends.