.. _urban_planning:

==============
Urban planning
==============

Seattle Parking
===============

Driving in Seattle is quickly becoming very similar to driving in cities like San Francisco, 
Silicon Valley or Los Angeles: more and more companies choose to settle or open their offices 
in Seattle so they can tap into the tech community that Seattle has to offer. With that, 
parking in Seattle is getting harder by day.

`Paid Parking Occupancy dataset <https://data.seattle.gov/browse?q=2020%20Paid%20Parking%20Occupancy%20(Year-to-date)&sortBy=relevance>`_ provided by the City of Seattle Department of Transportation 
provides a view into around 300 million parking transactions annually from around 12 
thousands parking spots on roughly 1,500 block faces. The dataset does not include any 
transaction for Sundays as there is no paid parking. Most of the parking spots have a 
2-hour limit.

**Notebooks:**

- **ETL:** `1_blazing_seattleParking.ipynb <https://github.com/BlazingDB/Welcome_to_BlazingSQL_Notebooks/blob/master/webinars/seattle_parking/1_blazing_seattleParking.ipynb>`_
- **Regression model and graph:** `2_seattleParking_ml_graph.ipynb <https://github.com/BlazingDB/Welcome_to_BlazingSQL_Notebooks/blob/master/webinars/seattle_parking/2_seattleParking_ml_graph.ipynb>`_

**Recordings:**

- **ETL:** 
    - *English:* `GPU-Accelerated Data Science: Find a Parking Spot with SQL <https://www.youtube.com/watch?v=qmX0H3bkR48&t=2092s>`_
    - *Spanish:* `Ciencia de Datos Acelerada con GPUs: Buscar Estacionamiento con SQL <https://www.youtube.com/watch?v=X3WxOieweD8>`_
- **Regression model and graph:** 
    - *English:* `GPU-Accelerated Data Science: Machine learning and graph analytics with RAPIDS <https://www.youtube.com/watch?v=VY2I3FIqiyc>`_
    - *Spanish:* `Ciencia de Datos Acelerada con GPUs: Machine learning y análisis de grafos con RAPIDS <https://www.youtube.com/watch?v=N19aHSmA4jk>`_

**Blogs**

- Where should I park?: `https://towardsdatascience.com/where-should-i-park-29e8da95265a <https://towardsdatascience.com/where-should-i-park-29e8da95265a>`_
- Where should I walk?: `https://towardsdatascience.com/where-should-i-walk-e66b26735de5 <https://towardsdatascience.com/where-should-i-walk-e66b26735de5>`_
- Where really are the parking spots?: `https://towardsdatascience.com/where-really-are-the-parking-spots-ed6a1129035e <https://towardsdatascience.com/where-really-are-the-parking-spots-ed6a1129035e>`_


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