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North American Bike Share User Behaviour Data
Data Science and Analytics
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About
A one-year collection of user data from the Cyclistic bike-share service, designed to enable exploration of how different customer types use the service. This public data is from Motivate International Inc. and serves as the basis for the capstone project in the Google Data Analytics course on Coursera. As Cyclistic is a fictional company for the case study, this real-world dataset is used as a suitable substitute. Due to data-privacy measures, it does not include personally identifiable information, which prevents linking ride purchases to specific credit card numbers.
Columns
- ride_id: A unique identifier for each ride.
- rideable_type: The type of bicycle used (e.g., classic_bike, electric_bike).
- started_at: The date and time the ride started.
- ended_at: The date and time the ride ended.
- start_station_name: The name of the station where the ride began.
- start_station_id: A unique identifier for the starting station.
- end_station_name: The name of the station where the ride ended.
- end_station_id: A unique identifier for the ending station.
- start_lat: The latitude coordinate of the starting station.
- start_lng: The longitude coordinate of the starting station.
- end_lat: The latitude coordinate of the ending station.
- end_lng: The longitude coordinate of the ending station.
- member_casual: The type of user, classified as either 'member' or 'casual'.
- Year: The year the ride took place.
- Month: The month the ride took place.
- ride_length: The duration of the ride.
- Year-Month: A combined field representing the year and month of the ride.
Distribution
The data is provided as a single CSV file,
df_1_year.csv, with a size of 753.2 MB. It contains 3.24 million valid records across 18 columns. Note that some fields related to station information contain missing values; for instance, start_station_name and end_station_name have 16% and 17% missing data, respectively.Usage
This data is ideal for analysing customer behaviour and usage patterns in the mobility sector. It can be used for data analysis and visualisation projects to understand ride patterns, peak usage times, popular routes, and differences in behaviour between member and casual riders. It is particularly well-suited for educational settings like data analytics courses or for business analysts practising with a real-world scenario.
Coverage
The data spans a one-year period from 1 August 2021 to 1 August 2022. Geographically, it covers the bike-share service's operations in North America. The user base is segmented into two types: 'member' riders, who account for 59% of the rides, and 'casual' riders, who account for the remaining 41%.
License
CC0: Public Domain
Who Can Use It
- Data Analytics Students: Perfect for completing case studies and capstone projects, such as the Google Data Analytics Certificate.
- Business Analysts: Useful for analysing customer segmentation and usage patterns to inform marketing and business strategies.
- Urban Planners: To study urban mobility trends and support infrastructure planning.
- Data Scientists: For building predictive models related to bike demand or user behaviour.
Dataset Name Suggestions
- Cyclistic Bike Share Annual Rider Analysis
- North American Bike Share User Behaviour Data
- One-Year Cyclistic Ride Data for Customer Segmentation
- Urban Mobility: Cyclistic Bike Share Patterns
- Member vs Casual Rider Bike Usage Logs
Attributes
Original Data Source: North American Bike Share User Behaviour Data
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