Please view my Tableau Public Workbook at the below link:
https://public.tableau.com/app/profile/diane3563/viz/CitiBikesProject_16417057086980/CitiBikesStory
Congratulations on your new job! As the new lead analyst for the New York Citi Bike Program, you are now responsible for overseeing the largest bike sharing program in the United States. In your new role, you will be expected to generate regular reports for city officials looking to publicize and improve the city program.
Since 2013, the Citi Bike Program has implemented a robust infrastructure for collecting data on the program's utilization. Through the team's efforts, each month bike data is collected, organized, and made public on the Citi Bike Data webpage.
However, while the data has been regularly updated, the team has yet to implement a dashboard or sophisticated reporting process. City officials have a number of questions on the program, so your first task on the job is to build a set of data reports to provide the answers.
Your task in this assignment is to aggregate the data found in the Citi Bike Trip History Logs and find two unexpected phenomena.
Design 2-5 visualizations for each discovered phenomena (4-10 total). You may work with a timespan of your choosing. Optionally, you may merge multiple datasets from different periods.
I chose to look at Citibikes data from a "pre"-COVID and "post"-COVID perspective. While the pandemic is far from over, many people do consider life to have slowly returned to normal throughout 2021 with the adven of the vaccines. I am specifically interested in how the pandemic may have influenced rider behavior and whether those behaviors are changing again in response to a waning pandemic. The following are the questions I investigated during this analysis
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How many trips have been recorded total during the chosen period? How does this # differ "pre" & "post"-COVID?
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By what percentage has total ridership grown?
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How has the proportion of short-term customers and annual subscribers changed from "pre" to "post"-COVID?
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How does the average trip duration change by age?
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What is the average distance in miles that a bike is ridden?
Next, as a chronic over-achiever:
- Use your visualizations (does not have to be all of them) to design a dashboard for each phenomena.
- The dashboards should be accompanied with an analysis explaining why the phenomena may be occuring.
City officials would also like to see one of the following visualizations:
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Basic: A static map that plots all bike stations with a visual indication of the most popular locations to start and end a journey with zip code data overlaid on top.
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Advanced: A dynamic map that shows how each station's popularity changes over time (by month and year). Again, with zip code data overlaid on the map.
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The map you choose should also be accompanied by a write-up unveiling any trends that were noticed during your analysis.
Finally, create your final presentation
- Create a Tableau story that brings together the visualizations, requested maps, and dashboards.
- This is what will be presented to the officials, so be sure to make it professional, logical, and visually appealing.
Remember, the people reading your analysis will NOT be data analysts. Your audience will be city officials, public administrators, and heads of New York City departments. Your data and analysis needs to be presented in a way that is focused, concise, easy-to-understand, and visually compelling. Your visualizations should be colorful enough to be included in press releases, and your analysis should be thoughtful enough for dictating programmatic changes.
Your final submission should include:
- A link to your Tableau Public workbook that includes:
- 4-10 Total "Phenomenon" Visualizations
- 2 Dashboards
- 1 City Official Map
- 1 Story
Your final product will be assessed on the following metrics:
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Analytic Rigor
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Readability
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Visual Attraction
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Remember, data alone doesn't "answer" anything. You will need to accompany your data visualizations with clear and directed answers and analysis.
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As is often the case, your clients are asking for a LOT of answers. Be considerate about their need-to-know and the importance of not "cramming in everything". Of course, answer each question, but do so in a way that is organized and presentable.
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Since this is a project for the city, spend the appropriate time thinking through decisions on color schemes, fonts, and visual story-telling. The Citi Bike program has a clear visual footprint. As a suggestion, look for ways to have your data visualizations match their aesthetic tones.
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In answering the question of "why" a phenomenon is occurring, consider adding other pieces of information on socioeconomic or other geographic data. Tableau has a map "layer" feature that you may find handy.
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