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Python BI Project

The following project consists in finding an office space for a Digital Marketing Agency

Main code asks the user for an address or location where they want to search or evaluate if its optimal for their office.

There are some limitations: They want to be sorrounded with Small and Medium Business They want to have a coffee shop nearby They want to be in San Diego California

For this project I'm using the following libraries:

  • Pandas
  • Pymongo
  • TQDM
  • Folium
  • Numpy
  • Warnings
  • Regex
  • Pickle
  • OpenCage (for geocode)

In order to achieve the main result, I'm folowing 6 steps:

Step 1

Define client type: as I mentioned in the README ,they want to be sorrounded with Small and Medium Business, they want to have a coffee shop nearby and they want to be in San Diego California

Step 2

Correctly query the data I want from Mongo.

Step 3

Transforming data according to client needs.

Step 4

Create a new collection with the final DataFrame in MongoCompass so we can add a 2dsphere index.

Step 5

Make geoqueries of the new collection with client input and display them in a heatmap reflecting the concentration of offices in the selected area.

Step 6

Get more information about restaurants in the area and display them with the heatmap mentioned above and marking where the restaurants of coffee shops are.