This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area.
The dataset consists of 183412 Ford GoBike and contains 16 features representing different data such as (age, gender, user type, duration, and others). The dataset can be found it here. https://video.udacity-data.com/topher/2020/October/5f91cf38_201902-fordgobike-tripdata/201902-fordgobike-tripdata.csv
This project is divided into two parts, the first part I created graphs showing the dataset using the Python language, and the second part was presented using slides.
In the exploration, I found that there were many trips of different ages, ranging from 20 to 100, but most users were between 20 and 50 years old, and as for gender, there were many males and females, but the males beat the females, and finally the type of user the subscribers were more than the customers.
For the presentation, I focus on the duration, the user's age, the user's type, and the user's gender.
In the first Visualization is the distribution of duration, the duration starts from 0 and reaches 80,000, and most frequent trips duration is between 0 and 1000 and then begins to decrease to up to 5000.
In the second Visualization is the distribution of gender of the members and is divided into three categories: male, female, and others. It shows that the highest percentage is male, which is 74.60%, followed by female, which is 23.32%, and the lowest is others, which is 2.09%.
The third Visualization is the distribution of users' age, ranging from 0 to 100, it was found that most of the users' age are between 0 and 50 and the rest are between 50 and 100.
The last Visualization is the distribution of the type of the user is shown in relation to his gender and the number of his frequency, and it turns out that the most frequent in subscriber is in males, then followed by females than in subscriber.