/LondonCycleInsights

Uncover the secrets of London's bike rides with data-driven insights. From Kaggle dataset to Tableau visualizations, explore ride patterns and weather correlations. Pedal through the data for a fresh perspective on London's cycling landscape. 🚴‍♂️📊

Primary LanguageJupyter Notebook

LondonCycleInsights

LondonCycleInsights

Welcome to LondonCycleInsights, where data meets the open road! This project is a comprehensive exploration of London's bike rides, from the data gathering stage using Kaggle's London Bike Sharing Dataset to the dynamic visualizations crafted in Tableau.

Project Highlights

  • Data Exploration: Dive into the world of London bike rides with a rich dataset from Kaggle, including ride durations, start and end locations, and more.

  • Tableau Visualizations: Experience the power of Tableau with interactive visualizations showcasing moving averages, peak ride times, correlations between temperature and wind speed, and popular ride weather conditions.

Getting Started

  1. Data Source: The project relies on the Kaggle London Bike Sharing Dataset.

  2. Tableau Visualization: Access the interactive Tableau visualization here.

  3. Files Included:

  • data: Contains the final datasets used in the analysis.

    • london_bikes_final.xlsx: Excel file after data cleaning and preprocessing.
    • london_merged.csv: Merged CSV file with essential ride information.

  • images: Holds images related to the project.

    • dashboard.png: Screenshot of the Tableau dashboard.

  • LondonCycleInsights.ipynb: Jupyter Notebook file with Python code for data analysis.

  • Tableau - London Cycle Insights.twbx: Tableau workbook file with interactive visualizations.

  • requirements.txt: Lists the Python libraries and dependencies required for the project.

Analysis Insights

  • Tableau Dashboard:

    Tableau Dashboard

  • Total Rides Over Time: Explore the historical trends of bike rides in London.

  • Moving Average Rides: Gain insights into the smooth trends by examining moving averages.

  • Weather Insights: Understand the correlation between temperature, wind speed, and ride patterns.

  • Peak Ride Hours: Discover the peak hours when Londoners are most active on their bikes.

Usage

Explore the Tableau visualization to unravel insights into London's bike ride landscape. Interact with the visualizations, apply filters, and discover intriguing patterns.

Contributing

Your feedback is valuable! Contribute to LondonCycleInsights by providing insights, reporting issues, or suggesting improvements. Join us on this journey of LondonCycleInsights, where data speaks and bikes ride through the story. 🚴‍♂️🔍

License

This project is licensed under the MIT License - see the LICENSE file for details.