Citi Bike Data Visualization 2019 for Jersey City

Data Source:

https://s3.amazonaws.com/tripdata/index.html

Tools:

Tableau
Python (jupyter notebook)

Data Preparation:

Data cleaning was not necessary.

Output:

https://public.tableau.com/profile/suellen.maltz#!/vizhome/CitiBike_15937069585820/Story1?publish=yes

Contents:

1. Top 10 stations for starting and ending a journey.
2. Bottom 10 stations for starting and ending a journey.
3. Number of trips by gender.
4. Peak hours during summer and winter.
5. Ruch hours during the whole year.
6. Map based on start time

1. Top 10 stations for starting and ending a journey.

Both stations are similar at start or end of a journey, since many people uses the bike to commute to work or study meanings it does makes sense that the numbers do not change much.

2. Bottom 10 stations for starting and endinga journey.

Both stations are similar at start or end of a journey, since many people uses the bike to commute to work or study meanings it does makes sense that the numbers do not change much.

3. Number of trips by gender.

Male users are higher than females (around 3-time).

4. Number of Trips for Peak hours

8:00AM and 18:00PM are the peak time for users. There are still a great number of trips between the two time, but way less than peak hours.

5. Ruch hours during the whole year.

8:00AM and 18:00PM are also the peak time.

6. Map based on start time.

Grove St Path station has the highest number of trips for all users. Hamilton Park is the second. JCBS is the smallest sation (you barely can see in the map, but is there)