{"id":21181356,"url":"https://github.com/najtompkins/citibike_analysis","last_synced_at":"2026-05-17T12:32:59.538Z","repository":{"id":211318394,"uuid":"728812439","full_name":"najtompkins/citibike_analysis","owner":"najtompkins","description":"Tableau Proficiency - Visual Analysis of CitiBike rides from July-September 2023.","archived":false,"fork":false,"pushed_at":"2023-12-21T21:02:13.000Z","size":41528,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-14T19:23:25.921Z","etag":null,"topics":["python3","tableau-dashboards","tableau-public","visualization-tools"],"latest_commit_sha":null,"homepage":"https://public.tableau.com/app/profile/nathan.andrew.tompkins/viz/CitiBike2_16981002014400/Story1?publish=yes","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/najtompkins.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-12-07T18:45:32.000Z","updated_at":"2023-12-21T20:47:24.000Z","dependencies_parsed_at":"2023-12-07T19:48:53.018Z","dependency_job_id":null,"html_url":"https://github.com/najtompkins/citibike_analysis","commit_stats":null,"previous_names":["najtompkins/citibike_analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/najtompkins/citibike_analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/najtompkins%2Fcitibike_analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/najtompkins%2Fcitibike_analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/najtompkins%2Fcitibike_analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/najtompkins%2Fcitibike_analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/najtompkins","download_url":"https://codeload.github.com/najtompkins/citibike_analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/najtompkins%2Fcitibike_analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33138325,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-17T09:28:26.183Z","status":"ssl_error","status_checked_at":"2026-05-17T09:27:52.702Z","response_time":107,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["python3","tableau-dashboards","tableau-public","visualization-tools"],"created_at":"2024-11-20T17:49:52.565Z","updated_at":"2026-05-17T12:32:59.502Z","avatar_url":"https://github.com/najtompkins.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CitiBike Riders Analysis\n\n-- For full repository, click [here](https://github.com/najtompkins/citibike_analysis). --\n\n\u003cimg align=\"right\" src=\"images/citi_bikes.jpg\" alt=\"City Bikes\" width=\"40%\" height=\"40%\"\u003e\n\nThe purpose of this analysis is to demonstrate proficiency in Salesforce's Tableau Public by presenting an analysis performed on CitiBike's own historical records found at [https://s3.amazonaws.com/tripdata/index.html](https://s3.amazonaws.com/tripdata/index.html). The visual analysis and insights of CitiBike rides span the summer months of July-September 2023.\n\n*Note:*\n*This analysis was performed as part of the 2023 UCF Data Analytics and Visualization Bootcamp.*\n\n## Tableau Workbook Access\nFor the interactive Tableau Story, click [here](https://public.tableau.com/app/profile/nathan.andrew.tompkins/viz/CitiBike2_16981002014400/Story1?publish=yes).\n\nFor the Tableau .twbx download, click [here](citibike_analysis.twbx).\n\n## Data Overview\n- **Total Number of Rides Recorded:** 312,868\n- **Total Number of Bike Stations:** 81\n- **Average Length of Each Ride:** 2-3 Minutes\n- **Peak Riding Hours:** 4-6 pm\n- **Peak Riding Days:** Weekdays (especially midweek)\n- **Rider Categories:** *Member, Non-Member*\n- **Most Popular Station:** \"JC115,\" at Christopher Columbus Dr. and Grove St.\n- **Most Popular City Area:** Jersey City, New Jersey\n\n## Observations and Recommendations\n\n1. Jersey City \u003cbr\u003e\n   \u003cimg align=\"right\" src=\"images/jersey_city.png\" alt=\"City Bikes\"\u003e\n   1.1 The data reveals that the most popular cluster of stations can be found in Jersey City, New Jersey. This could be because, according to [walkscore.com](https://www.walkscore.com/NJ/Jersey_City), \"Jersey City has an average Walk Score of 87 with 247,597 residents\" and \"has excellent public transportation and is somewhat bikeable.\" Over 89,686 (28%) of all rides beginning or ending at these stations. \u003cbr\u003e\n   1.2 *Consider investing in increased cleanliness/maintenance for these stations, as well as developing a marketing strategy to solidify CitiBike as a part of the Jersey City Identity.* \u003cbr\u003e\n\n3. Peak Evening Hours \u003cbr\u003e\n   2.1 Our riders start and end their rides most frequently between the hours of 4 pm and 6 pm, peaking on midweek evenings. This same pattern holds for the hours of 6 am to 9 am, though to a lesser degree. This may indicate that workers are more likely to walk to their place of work but ride home after their shift.\n   ![Hours Heatmap](images/peak_hours.png)\n   ![Hours Line Chart](images/peak_hours_line.png)\n\n4. Peak Morning Hours \u003cbr\u003e\n   3.1 The data above also indicates that midweek is the height of both evening and **morning** rides. Early morning commuting increases midweek between 6 am and 9 am. Could our riders be \"treating\" themselves by choosing our bikes as a more premium transportation option in the middle of the week for both morning and evening commuting?\n   3.2 *Consider developing a \"commuter\" type rewards system or membership tier, especially for riders who ride every day and develop a \"commuter streak.\"*\n\n5. Membership Notes \u003cbr\u003e\n   4.1 In September, over 73% of all rides were taken by CitiBike members, an increase of 4.5% in July. Jersey City likewise saw member ride growth; the percentage of Membership in the Jersey City Area grew from 60% to 67%, indicating a growing user base. This growth is also reflected in membership rides from July to September.\n   4.2 *Consider increasing membership by offering the above-mentioned reward system or membership option, coupled with value-adding discounts for rides outside of commuting hours.*\n   4.3 *Consider Adding a \"Location\" label for each member. \"John Doe: Jersey City CitiBike Rider.\" This may add to the sense of local identity mentioned in the recommendation 1, Observation 1.*\n   ![Membership Change](images/membership_change.png)\n\n6. Electric Bike usage decline \u003cbr\u003e\n   5.1 While not a stark decline, it is observed that electric bike usage declined by 2% over these months. Do our users want healthier rides (classic bikes), or could this indicate technological issues with our electric option which leave our users dissatisfied with having a single bike option?\n   5.2 *Consider increasing electric-bike marketing as value to the user, cost-benefit for electric/classic bike ratio, and evaluate maintenance logs for the most-used bikes.*\n   ![Bike Type Usage](images/bike_type_perc.png)\n\n## Summary\n\u003cimg align=\"right\" src=\"images/sunset_bike.png\" alt=\"City Bikes\" width=\"50%\" height=\"50%\"\u003e\n\u003ch3\u003eOur riders find value in our bikes as a commuting tool, particularly in a very public-transport-accessible and walkable city like Jersey City. Our peak hours are midweek from 6-9 am and in the evening from 6-8 pm. Members account for nearly 71% of all rides, but value in the product can be increased by targeting our busiest stations for improved maintenance, cultural presence, and more importantly, a more varied number of membership options that encourage daily usage of our bikes.\u003c/h3\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnajtompkins%2Fcitibike_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnajtompkins%2Fcitibike_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnajtompkins%2Fcitibike_analysis/lists"}