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Ironhack Madrid - Data Analytics Part Time - May 2022 - Project Module 1

Python 68.57% Jupyter Notebook 31.43%

ih_datamadpt0522_project_m1's Introduction

ih_datamadpt0522_project_m1

Ironhack Madrid - Data Analytics Part Time - May 2022 - Project Module 1

Data:

There are 2 main datasources:

  • MySQL Online Database. The database contains information from the BiciMAD stations including their location (i.e.: latitude / longitude). In order to access the database you may need the following credentials:
Server:        SERVER_IP
Database:      BiciMAD

IMPORTANT => Username and password will be provided in class.

IMPORTANT => Specific datasets will be assigned to each student in order to perform the challenges.


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
... ... ... ... ...

(*) There is a list of datasets each one with different places. A specific dataset will be assigned to each student.

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!!!


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