Updated: 24 apr 2026
Imports¶
The required Python libraries are imported below
Source
import pandas as pd
import requestsAbout¶
This notebook retrieves metadata about all bikeshare stations within a single network from public API endpoints. The base URL of the API of the single bikeshare network was obtained from the previous notebook
User Inputs¶
base_url = "https://toronto.publicbikesystem.net/customer/gbfs/v3.0"The following derived variables are created to define the two station API endpoints from the above
url_info = f"{base_url}/station_information"
url_status = f"{base_url}/station_status"Extract¶
First we retrieve the station information from the station_information/ endpoint
r_info = requests.get(url_info).json()
df_info = pd.DataFrame.from_records(r_info["data"]["stations"]).convert_dtypes(
dtype_backend="pyarrow"
)
df_infoLoading...
Next, we’ll get the station status from the station_status/ endpoint
r = requests.get(url_status).json()
df_status = pd.DataFrame.from_records(r["data"]["stations"]).convert_dtypes(
dtype_backend="pyarrow"
)
df_statusLoading...
Transform¶
Next, we’ll merge these two outputs using the station_id column
df = df_info.merge(df_status, on="station_id", how="left")
dfLoading...