This data analysis aims to answer the following questions, based on a 356,530 bicycling trips from december 2019 to 2020 in New York City. In this dashboard (https://public.tableau.com/shared/XK479TSDD?:display_count=n&:origin=viz_share_link) you are going to find the effects of COVID-19 in the use of this sort of transport and also you will know:
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How many trips have been recorded total during the chosen period?
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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?
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What are the peak hours in which bikes are used during summer months?
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What are the peak hours in which bikes are used during winter months?
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Today, what are the top 10 stations in the city for starting a journey? (Based on data, why do you hypothesize these are the top locations?)
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Today, what are the top 10 stations in the city for ending a journey? (Based on data, why?)
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Today, what are the bottom 10 stations in the city for starting a journey? (Based on data, why?)
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Today, what are the bottom 10 stations in the city for ending a journey (Based on data, why?)
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Today, what is the gender breakdown of active participants (Male v. Female)?
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How effective has gender outreach been in increasing female ridership over the timespan?
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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?
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Which bikes (by ID) are most likely due for repair or inspection in the timespan?
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How variable is the utilization by bike ID?
The dashboard contains at the end 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.