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- ---
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- license: mit
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+ ---
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+ license: mit
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+ ---
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+
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+ # Bixi's OpenData Modelisation
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+ Here is a huggingface dataset refined with [AntoineGiraud/dbt_bixi_opendata](https://github.com/AntoineGiraud/dbt_bixi_opendata) dbt-core project<br>
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+ that loads & transform [bixi OpenData](https://bixi.com/fr/donnees-ouvertes/) thanks to [DuckDB](https://duckdb.org/) πŸ¦†πŸš€
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+
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+ ## Viz' exploration ideas
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+ I used Power BI to explore the transformed data offloaded to .parquet (~ 4.7 times lighter than .csv)
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+ After the pandemic, Montrealers realy went back to bixi πŸ₯³
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/66e9b7eb6d83fd1e4fa3b41a/bbDJyhw34kyLOhOIcO43V.png)
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+
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+ ## Data sources
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+
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+ ### Bixi Rentals OpenData ([link](https://bixi.com/fr/donnees-ouvertes/))
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+
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+ - 🚲 **Rentals V1** : from 2014 to 2021
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+ > for station info, join to station
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+ yearly file with station_code
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+ - β›½ **Stations V1** : from 2014 to 2021
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+ > 1 station code per year
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+ - 🚲 **Rentals V2** : from 2022 to 2024+
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+ > start/end station info on each rentals\
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+ *-> 2.7 times heavier `.csv`* 1.4Gb -> 0.5Gb\
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+ *-> 2.3 times heavier `.parquet` 250Mb -> 106Mb*
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+
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+ ### GIS referential
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+
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+ - 🧭 **Municipal sectors** : from the OD 2013 survey (cf. [donnees quebec](https://www.donneesquebec.ca/recherche/dataset/artm-secteurs-municipaux-od13/resource/95ab084b-727e-4322-9433-0fed7baa690d))
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+
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+ ## Schema/DB steps :
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+
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+ - **raw** : raw tables loaded as is from .csv
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+ - **stg** : intermediate tables
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+ - **dtm** : tables ready for analytics & reporting use
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/66e9b7eb6d83fd1e4fa3b41a/WC9X27HN15k4br9iARpE7.png)
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+ ### Loading
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+ DuckDB realy shines by it's speed & local OLAP capabilities 😎
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+ Here is 🚲 v1 rentals (2014 - 2021) load & offload to .parquet
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+ - `.csv` is **4.5** times heavier than `.parquet`
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+ - `.json` is **2.7** times heavier than `.csv`
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/66e9b7eb6d83fd1e4fa3b41a/CPcQ1-GiV77kJESLeQQL7.png)