Tableau - Citi Bike Trips Data Analysis

Phenomenon 1: Impact of Covid-19 on Citi Bike Trips

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Phenomenon 2: Identifying Target Market based on Age, Gender and Popular Location

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Analysis:

Phenomenon 1: Impact of Covid-19 on City Bikes Trips

1. A six-week lockdown implemented in the months of March & April, 2020, substantially decreased the number of trips for City-Bikes. The decrease in trips started in February, but a major dip of 36% was observed in the month of April. This dip can be attributed to the strict lockdown which was implemented in New York City because of increase in number of COVID-19 cases.

2. However, it was also observed that in the following month of May, when the lockdown restriction began to relax, a huge uptick caused by pent up demand lead to an increase in number of trips by more than a 117%, and this positive monthly increase has been observed till the last data point. This trend can be observed in the monthly change graph represented by red and green colors.

3. Monthly heatmap Maps represent the decrease and increase in activity as the monthly change. The animation can be played using sliders at the bottom of the maps.

4. One of the unsually phenomenon that was observed was the fact that while the number of trips where decreasing the average trip duration increased during the months of lockdown. Maybe it can be attributed to people preferring to travel on bikes alone instead of taxis, which can spread COVID-19 faster; however, more analysis might be required to explain this trend completely. It was also observed that 'females' average trip duration was slight longer then 'males' average trip duration. A detailed graph highlights this phenonmenon.

Phenomenon 2: Identifying Target Market based on Gender, Age & Location.

1. After looking at the data, it can be observed that male dominate the bikes trip market, as 60.83% of the riders are male, while only 28.16% of the riders are female. However it can be observed that in the months following the strict covid lockdown May - August, number of female riders have increased increasing the ratio of male to female bike riders. The bar chart shows the changing trend in later months.

2. After reviewing the data, it can be observed that a lot of riders have choose not to disclose their original age. A quick calculation shows riders of more then 100+ age going upto the figure of 140 years. However, this data seemed to contain outliers and incorrect values, so it was filtered to a maximum age of 90 years. It was also observed that people age 51 had a major sudden uptick in number of trips, which could not be explained, hence, age 51 years was also excluded from the analysis. After cleaning the data a trend can be seen, were riders in the 30's seems to be having the most number of trips and as the age increases the number of trips went down.

3. It was also observed that 12 Ave & W 40 St is the most popular start and end point of the riders.

4. From the analysis above, it can be deduced that any future marketing campaigns can benefit if the male population of age 28 - 32, located near 12 Ave & W 40 St be targed.