https://github.com/sehgal-vishal/citi-bike-data-analysis

The goal of this project is to analyze the usage patterns of Citi Bike in New York City
https://github.com/sehgal-vishal/citi-bike-data-analysis

advanceexcel business-analytics citibike cleaning-data dataanalysis pivot-tables visualisation

Last synced: 4 days ago
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The goal of this project is to analyze the usage patterns of Citi Bike in New York City

• Host: GitHub
• URL: https://github.com/sehgal-vishal/citi-bike-data-analysis
• Owner: sehgal-vishal
• Created: 2024-09-13T15:31:12.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-13T15:50:59.000Z (2 months ago)
• Last Synced: 2024-09-14T06:38:03.887Z (2 months ago)
• Topics: advanceexcel, business-analytics, citibike, cleaning-data, dataanalysis, pivot-tables, visualisation
• Homepage:
• Size: 256 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Project Overview: NYC Citi Bike Usage Dashboard

Objective: The goal of this project is to analyze the usage patterns of Citi Bike in New York City. The insights derived from this analysis will assist stakeholders in making informed, data-driven decisions aimed at improving the bike-sharing service, optimizing resources, and enhancing customer satisfaction.

Key Investigations: The analysis focuses on several critical questions:

Most Popular Pick-Up Locations: Identifying the locations with the highest bike pick-up activity across NYC.

Average Trip Duration Across Age Groups: Examining how the duration of bike trips varies among different age demographics.

Age Group Rental Frequency: Determining which age groups are the most frequent users of Citi Bike.

Usage Patterns by User Type: Exploring differences in bike rental patterns between one-time users and subscribers, especially across different days of the week.

Impact of Age on Trip Duration: Analyzing how a user's age influences the duration of their bike trip

Outcomes: This dashboard offers a comprehensive view of Citi Bike usage patterns, enabling stakeholders to:

Identify peak usage times and popular locations for targeted resource allocation.

Understand demographic preferences and tailor marketing efforts accordingly.

Make informed decisions on fleet expansion, station placements, and service enhancements.

The dashboard's interactive filters allow users to explore various dimensions of the data, ensuring that the insights are both actionable and relevant to different stakeholder needs.

Conclusion:

The Citi Bike NYC Usage Dashboard serves as a powerful tool for visualizing key metrics and trends in the Citi Bike data, ultimately guiding decision-makers in improving the bike-sharing service and enhancing user satisfaction across New York City.