Table of Contents

1. Installation

2. Project Motivation

3. Project Motivation

4. File Description

5. Results

6. Licensing, Authors, and Acknowledgements

7. Blog Post

Installation

I would recommend to download annoconda on your machiney.

Project Motivation

This is the Coursera Caption project. The goal of this project is to find the ideal location to build a new cinema in the USA. We found this by asking a few questions listed below.

1.Footfall of the location ?

2. Customer purchase behaviour ?

Tools Used and Data

Foursquare API

Jupyter Notebook on local machine /IBM Watson Account

Data

The Wikipedia page (https://en.wikipedia.org/wiki/List_of_United_States_cities_by_population) was scraped using the BeautifulSoup library to build a pandas dataframe listing the cities, states, coordinates, area and population density. The dataframe was cleaned and processed appropriately.

The Wikipedia page (https://en.wikipedia.org/wiki/List_of_United_States_counties_by_per_capita_income) was scraped using the BeautifulSoup library to build a pandas dataframe listing the cities, states and percapita income. The dataframe was cleaned and processed appropriately.

The Foursquare API is then used to get the venues in each city of United States Based on the categories of each venue as decided by the CEO, we have assigned weights to each of them and got the city that has the maximum weight.

File Description

IntroductionBusiness Problem.pdf: Intros About Business Problem.

CAP.pdf, CAP.PPT: Depth Business Plan and metholody involved in PDF and PPT format respectively

The battle of Neighbourhoods - Final Report.ipynb : The actual source code of data

The battle of Neighbourhoods - Final Report.ipynb : Report and conclusion from the above data.

Result

Based on the given constraints, the green circle is ideal place to build the cinema for mass footfalls and revenue

Licensing

Big thanks to Coursera for this capstone project. I would also like to thank wikipedia for the data.

Blog Post