A. Introduction

1) Description of the problem and a discussion of the background.

Toronto, the most populous city in Canada, with a population of 2,731,571 as of 2016. Current to 2016, the Toronto census metropolitan area (CMA), of which the majority is within the Greater Toronto Area (GTA), held a population of 5,928,040, making it Canada's most populous CMA.The Toronto metropolitan area was the second-fastest-growing metropolitan area in North America, adding 125,298 persons.

The Toronto region’s Food and Beverage sector employs more than 64,000 workers with annual wages totaling $3.2B. Sector businesses located within the city of Toronto account for more than 50 per cent of this workforce.

The amount of tea that Canadians drink has doubled in the past few decades. As of 2015, Canadians drink 85 litres per person per year, up from 79.4 litres in 2008, and only 36 litres in 1991! Tea surpassed both soft drinks and bottled water, and is only slightly less than the amount of coffee that Canadians drink. However it’s also interesting to note that the average amount of coffee drank by Canadians decreased from the previous year, while tea rose by several litres.

There are same neighborhood some places have a high demand while there are others hardly getting any profit. So if I wanna open a tea store, where would be a nice place to open my first store? The objective of the following analysis is to check where would be popular in a determined neighborhood, and which neighborhood has a better acceptance for that kind. This capstone would be interesting for those who wanna open a tea store and have no idea where to open.

2) Who would be interesting at the capstone?

This capstone would be interesting for those who wanna open a tea store and have no idea where to open.

• Investor
• Entrepreneur
• Tea supplier
• Asian restaurants

3) Data that you can get from this capstone

• Top venues of Toronto in different sectors
• Market demand (cluster)
• Best place to open a tea store
• Where do you have more competitor
• etc.

4) Description of the data and how it will be used to solve the problem.

Considering the problem mentioned, the following data will be used to solve the problem:

• From Wikipedia, I have found a complete list of postal codes of Toronto, followed by theirs borough and neighborhood name: https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M
• I used the Foursquare API to explore the top venues of a given neighborhood.
• CSV file "Geospatial_Coordinates.csv" given by IBM