/ih_datamadpt0923_project_m1

Ironhack Madrid - Data Analytics Part Time - Sep 2023 - Project Module 1

Primary LanguageJupyter NotebookMIT LicenseMIT

ih_datamadpt0923_project_m1

Ironhack Madrid - Data Analytics Part Time - Sep 2023 - Project Module 1

Data:

There are 2 main datasources:

  • CSV Files. The datasets contains information from the BiciMAD stations including their location (i.e.: latitude / longitude). You may find the .csv files in the data folder.

  • API REST. We will use the API REST from the Portal de datos abiertos del Ayuntamiento de Madrid, where you can find the Catálogo de datos with more than 70 datasets. The API endpoint is https://datos.madrid.es/egob.

IMPORTANT: These are the body corresponding to every dataset:

  • Alana: /catalogo/209426-0-templos-catolicas.json

  • Alberto: /catalogo/209434-0-templos-otros.json

  • Ana: /catalogo/202162-0-instalaciones-accesibles-municip.json

  • Andrew: /catalogo/202180-0-instalaciones-accesibles-no-muni.json

  • Carlos: /catalogo/202311-0-colegios-publicos.json

  • Elena: /catalogo/203166-0-universidades-educacion.json

  • Guille: /catalogo/200215-0-instalaciones-deportivas.json

  • John: /catalogo/200304-0-centros-culturales.json

  • Natalia: /catalogo/201000-0-embajadas-consulados.json

  • Rodrigo: /catalogo/300356-0-monumentos-ciudad-madrid.json

  • Sil: /catalogo/208844-0-monumentos-edificios.json

  • Silvia: /catalogo/300614-0-centros-educativos.json

  • Tere: /catalogo/200761-0-parques-jardines.json

  • Tomás: /catalogo/212808-0-espacio-deporte.json

Main Challenge:

You must create a Python App (Data Pipeline) that allow their potential users to find the nearest BiciMAD station to a set of places of interest using the methods included in the module geo_calculations.py. The output table should look similar to:

Place of interest Type of place (*) Place address BiciMAD station Station location
Auditorio Carmen Laforet (Ciudad Lineal) Centros Culturales Calle Jazmin, 46 Legazpi Calle Bolívar, 3
Centro Comunitario Casino de la Reina Centros municipales de enseñanzas artísticas Calle Casino, 3 Chamartin Calle Rodríguez Jaén, 40
... ... ... ... ...

(*) This correspond to the type of place assigned to you.

Your project must meet the following requirements:

  • It must be contained in a GitHub repository which includes a README file that explains the aim and content of your code. You may follow the structure suggested here.

  • It must create, at least, a .csv file including the requested table (i.e. Main Challenge). Alternatively, you may create an image, pdf, plot or any other output format that you may find convenient. You may also send your output by e-mail, upload it to a cloud repository, etc.

  • It must provide, at least, two options for the final user to select when executing using argparse: (1) To get the table for every 'Place of interest' included in the dataset (or a set of them), (2) To get the table for a specific 'Place of interest' imputed by the user.

Additionally:

  • You must prepare a 4 minutes presentation (ppt, canva, etc.) to explain your project (Instructors will provide further details about the content of the presentation).

  • The last slide of your presentation must include your candidate for the 'Ironhack Data Code Beauty Pageant'.

Bonus 1:

You may include in your table the availability of bikes in each station.

Bonus 2:

You may improve the usability of your app by using FuzzyWuzzy.

Bonus 3:

Feel free to enrich your output data with any data you may find relevant (e.g.: wiki info for every place of interest) or connect to the BiciMAD API and update bikes availability realtime or find a better way to calculate distances...there's no limit!!!

Project Main Stack