Peer- graded assignment capstone project the battle of neighborhoods( week 1)
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August 19, Applied Data Science Capstone Peer-graded Assignment: Capstone Project - The Battle of Neighborhoods Now that you have been equipped with the skills and the tools to use location data to explore a geographical location, over the course of two weeks, you will have the opportunity to be as creative as you want and come up with an idea to leverage the Foursquare location data to explore or compare neighborhoods or cities of your choice or to come up with a problem that you can use the Foursquare location data to solve. Remember that data science problems always target an audience and are meant to help a group of stakeholders solve a problem, so make sure that you explicitly describe your audience and why they would care about your problem. We will be finding areas of New York City that are 'untapped' in potential meaning they can be further developed at the most economically efficient rates. Remember that you will need to use the Foursquare location data to solve the problem or execute your idea.
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New York City, the most populous city in the United States, one of the greatest metropolises over the world, is a dream place for gourmet to seek delicious cuisine. Its food culture includes an array of international cuisines influenced by the city's immigrant history. Central and Eastern European immigrants, especially Jewish immigrants from those regions, brought bagels, cheesecake, hot dogs, knishes, and delicatessens or delis to the city. Italian immigrants brought New York-style pizza and Italian cuisine into the city, while Jewish immigrants and Irish immigrants brought pastrami and corned beef, respectively.
This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about location data and different location data providers, such as Foursquare. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data. Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings.
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