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  1. Hourly Bikeshare + Weather 2024

    • kaggle.com
    Updated Apr 16, 2025
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    Sebastian Quirarte (2025). Hourly Bikeshare + Weather 2024 [Dataset]. https://www.kaggle.com/datasets/sebastianquirarte/mibici-bikeshare-weather-data-2024
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 16, 2025
    Dataset provided by
    Kaggle
    Authors
    Sebastian Quirarte
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Overview

    MiBici (translated as MyBike in english) is a public bike service used in my home city of Guadalajara (GDL), Jalisco, Mexico. This service is used in Guadalajara's Metropolitan Area, which has a population of 5,268,642 (as of 2020) distributed in eight main municipalities and a total area of 2,543.13 squared km (981.91 squared mi).

    This service has established stations where users can take and return a public bike, all they need is to sign up through MiBici's platform and pay a charge for 1, 3, 7 days, or annual use. After signing up, users get a transport card that can be used at any station in Guadalajara's Metropolitan Area.

    MiBici makes their data public and has published it every month since December 2014.

    A GitHub repository is also available with the R scripts used to merge, transform, and clean data from 4,496,890 bike trips registered in 2024 and hourly weather data obtained through the Open-meteo API, as well as the combined bikeshare + weather data and standalone hourly weather data available as csv files.

    Data

    Data was obtained directly from MiBici's public data website. In this site, data is published in CSV files corresponding to individuals month from December 2014 to Febuary 2025. Data from 2024 was downloaded, cleaned, and transformed into a hourly format, as well as merged with hourly weather data.

    bikeshare_weather_GDL_2024.csv variables:

    variabledescriptionunits
    datedate in yyyy-mm-dd format (i.e. '2024-01-01')date
    monthmonth of year (1 = jan, 2 = feb, ... , 12 = dec)month
    dayday of monthday
    hourhour of the day in 24 h format starting at 0hour
    trip_countcount of hourly bike tripscount
    is_weekendis the day a weekend? i.e. saturday/sunday (1 = yes, 0 = no)binary
    is_holidayis the day a federal holiday in Mexico? (1 = yes, 0 = no)binary
    apparent_temperatureperceived temperature combining wind chill factor, relative humidity and solar radiation°C
    wind_speedwind speed at 10 meters above groundkm/h
    is_day1 if the current time has daylight, 0 at nightbinary
    temperatureair temperature at 2 meters above ground°C
    relative_humidityrelative humidity at 2 meters above ground%
    precipitationtotal precipitation (rain, showers, snow) sum of the preceding hourmm
    weather_codeweather condition as a numeric code. Follow WMO weather interpretation codes (see below)WMO code
    seasonseason of the year (winter, spring, summer, fall)category

    WMO Weather interpretation codes (WW)

    codedescription
    0clear sky
    1mainly clear
    2partly cloudy
    3overcast
    45fog
    61rain: slight
    63rain: moderate
    80rain showers: slight
    81rain showers: moderate
    95thunderstorm
    96thunderstorm with slight hail

    Additional Data

    I have also cleaned, transformed, and combined all bikeshare data from Dec 2014 to Mar 2024 and published the final dataset (2.51 GB) in Kaggle.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Sebastian Quirarte (2025). Hourly Bikeshare + Weather 2024 [Dataset]. https://www.kaggle.com/datasets/sebastianquirarte/mibici-bikeshare-weather-data-2024
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Hourly Bikeshare + Weather 2024

MiBici 2024 hourly bikeshare data combined with hourly weather data.

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Apr 16, 2025
Dataset provided by
Kaggle
Authors
Sebastian Quirarte
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

Overview

MiBici (translated as MyBike in english) is a public bike service used in my home city of Guadalajara (GDL), Jalisco, Mexico. This service is used in Guadalajara's Metropolitan Area, which has a population of 5,268,642 (as of 2020) distributed in eight main municipalities and a total area of 2,543.13 squared km (981.91 squared mi).

This service has established stations where users can take and return a public bike, all they need is to sign up through MiBici's platform and pay a charge for 1, 3, 7 days, or annual use. After signing up, users get a transport card that can be used at any station in Guadalajara's Metropolitan Area.

MiBici makes their data public and has published it every month since December 2014.

A GitHub repository is also available with the R scripts used to merge, transform, and clean data from 4,496,890 bike trips registered in 2024 and hourly weather data obtained through the Open-meteo API, as well as the combined bikeshare + weather data and standalone hourly weather data available as csv files.

Data

Data was obtained directly from MiBici's public data website. In this site, data is published in CSV files corresponding to individuals month from December 2014 to Febuary 2025. Data from 2024 was downloaded, cleaned, and transformed into a hourly format, as well as merged with hourly weather data.

bikeshare_weather_GDL_2024.csv variables:

variabledescriptionunits
datedate in yyyy-mm-dd format (i.e. '2024-01-01')date
monthmonth of year (1 = jan, 2 = feb, ... , 12 = dec)month
dayday of monthday
hourhour of the day in 24 h format starting at 0hour
trip_countcount of hourly bike tripscount
is_weekendis the day a weekend? i.e. saturday/sunday (1 = yes, 0 = no)binary
is_holidayis the day a federal holiday in Mexico? (1 = yes, 0 = no)binary
apparent_temperatureperceived temperature combining wind chill factor, relative humidity and solar radiation°C
wind_speedwind speed at 10 meters above groundkm/h
is_day1 if the current time has daylight, 0 at nightbinary
temperatureair temperature at 2 meters above ground°C
relative_humidityrelative humidity at 2 meters above ground%
precipitationtotal precipitation (rain, showers, snow) sum of the preceding hourmm
weather_codeweather condition as a numeric code. Follow WMO weather interpretation codes (see below)WMO code
seasonseason of the year (winter, spring, summer, fall)category

WMO Weather interpretation codes (WW)

codedescription
0clear sky
1mainly clear
2partly cloudy
3overcast
45fog
61rain: slight
63rain: moderate
80rain showers: slight
81rain showers: moderate
95thunderstorm
96thunderstorm with slight hail

Additional Data

I have also cleaned, transformed, and combined all bikeshare data from Dec 2014 to Mar 2024 and published the final dataset (2.51 GB) in Kaggle.

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