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Analyzed Citi Bike data to uncover trends in ride duration, peak usage, and station demand, offering recommendations to optimize bike availability

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Tableau_Citi_Bike

Short Project Overview

Analysis of Citi Bike usage from February to April 2024. Please see 'Tableau_Citi_Bikes' file for visualization or check my Tableau Public Book.

Key Findings (Tableau)

  1. Long Duration Rides: Classic bikes show more long-duration rides (over 20 hours) compared to electric bikes, especially for casual users. These rides often don't correspond with longer distances, indicating possible user errors (e.g., forgetting to check out) or technical glitches.
  • Recommendation: Investigate potential system issues or user behavior. Implement alerts or reminders to prevent extended rides, improving bike availability and reducing unexpected charges..
  1. Peak vs. Long Rides: High usage during peak commuting hours doesn’t align with longer ride durations. Longer rides occur during midday, early morning, and weekends, suggesting leisure or exercise.
  • Recommendation: Expand stations near parks and promote biking for both commuting and leisure, particularly during non-peak hours.
  1. Low Demand in February: February shows the lowest demand, making it ideal for scheduling maintenance to minimize service disruptions.

  2. Most Popular Stations: This dashboard shows New Jersey is the most popular starting and ending point for rides, with few, if any, trips from New York to New Jersey.

  • Recommendation: Optimize bike distribution by ensuring sufficient bikes in New Jersey during peak hours and increasing availability at popular end stations in both New Jersey and New York to prevent shortages and congestion. Additionally, promote cross-city trips and analyze time-of-day patterns to further balance bike supply and demand.

Methodology

  • Data Cleaning: Pandas
  • Visualization: Tableau

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Analyzed Citi Bike data to uncover trends in ride duration, peak usage, and station demand, offering recommendations to optimize bike availability

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