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Exploring New York Neighborhoods for the best Italian Restaurants (The Battle of Neighborhoods)

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Exploring New York Neighborhoods for the best Italian Restaurants (The Battle of Neighborhoods)

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This is a data analytic report exploring the New York Neighborhoods for Italian restaurants. It is the Battle of neighborhoods where some neighborhoods win while others lose. The analysis was done using many libraries and packages in python like Foursquare and Pandas. The report forms part of the IBM Capstone Project for "Applied Data Science" Specialization.

This is a data analytic report exploring the New York Neighborhoods for Italian restaurants. It is the Battle of neighborhoods where some neighborhoods win while others lose. The analysis was done using many libraries and packages in python like Foursquare and Pandas. The report forms part of the IBM Capstone Project for "Applied Data Science" Specialization.

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Exploring New York Neighborhoods for the best Italian Restaurants (The Battle of Neighborhoods)

  1. 1. 1 Exploring New York Neighborhoods for the best Italian Restaurants Using Data Analytics (The Battle of Neighborhoods) CHIBUIKE OSIGWE
  2. 2. i Exploring New York Neighborhoods for the best Italian Restaurants Using Data Analytics (The Battle of Neighborhoods) CHIBUIKE OSIGWE
  3. 3. ii Preface As a part of the IBM Data Science professional program Capstone Project, we worked on the real datasets to get an experience of what a data scientist goes through in real life. Main objectives of this project were to define a business problem, look for data in the web and use Foursquare location data to compare different neighborhoods of New York to figure out which neighborhood is suitable for starting a new restaurant business. In this project, we will go through all the process in a step by step manner from problem designing, data preparation to final analysis and finally will provide a conclusion that can be leveraged by the business stakeholders to make their decisions.
  4. 4. iii Content Preface....................................................................................................................... ii Content..................................................................................................................... iii Introduction................................................................................................................1 1.1 Background.......................................................................................................1 1.2 Problem.............................................................................................................2 1.3 Target Audience................................................................................................3 Data Acquisition and Methodology...........................................................................4 2.1 Data Source.......................................................................................................4 2.2 Methodology.....................................................................................................4 Exploratory Data Analysis.........................................................................................5 3.1 Number of Neighborhoods ...............................................................................5 3.2 Italian Restaurants Per Borough.......................................................................5 3.3 Italian Restaurants Per Neighborhood..............................................................9 Conclusion and Recommendation ...........................................................................12 4.1 Recommendation and Discussion...................................................................12 4.2 Conclusion ......................................................................................................13
  5. 5. 1 Introduction 1.1 Background New York City (NYC), often called the City of New York or simply New York (NY), is the most populous city in the United States. With an estimated 2018 population of 8,398,748 distributed over about 302.6 square miles (784 km2 ), New York is also the most densely populated major city in the United States.[10] Located at the southern tip of the U.S. state of New York, the city is the center of the New York metropolitan area, the largest metropolitan area in the world by urban landmass.[11] With almost 20 million people in its metropolitan statistical area and approximately 23 million in its combined statistical area, it is one of the world's most populous megacities. New York City has been described as the cultural, financial, and media capital of the world, significantly influencing commerce,[12] entertainment, research, technology, education, politics, tourism, art, fashion, and sports. Home to the headquarters of the United Nations,[13] New York is an important center for international diplomacy.[14][15] Situated on one of the world's largest natural harbors, New York City is composed of five boroughs, each of which is a county of the State of New York.[16] The five boroughs–Brooklyn, Queens, Manhattan, the Bronx, and Staten Island–were consolidated into a single city in 1898.[17] The city and its metropolitan area constitute the premier gateway for legal immigration to the United States. As many as 800 languages are spoken in New York,[18] making it the most linguistically diverse city in the world. New York is home to more than 3.2 million residents born outside the United States,[19] the largest foreign-born population of any city in the world as of 2016.[20][21] As of 2019, the New York
  6. 6. 2 metropolitan area is estimated to produce a gross metropolitan product (GMP) of $2.0 trillion. If greater New York City were a sovereign state, it would have the 12th highest GDP in the world.[22] New York is home to the highest number of billionaires of any city in the world. Figure 1: A Typical Italian Restaurant 1.2 Problem This final project explores the best locations for Italian restaurants throughout the city of New York. Food Business News stated that worldwide pasta sales were up for the second year in a row with the United Sates holding the largest market (Donley, 2018). New York is a major metropolitan area with more than 8.4 million (Quick Facts, 2018) people living within city limits. Most of the Italian immigration
  7. 7. 3 into the United States occurred during the late 19th and early 20th century with over two million immigrants between 1900 and 1910. Italian families first settled in Little Italy’s neighborhood around Mulberry Street as has continued to thrive ever since. Italy account for the largest black immigrants in the United State, with almost 100,000 Manhattan inhabitants reporting Italian ancestry, the need to find and enjoy Italian cuisine is on the rise. This report explores which neighborhoods and boroughs of New York City have the most as well as the best Italian restaurants. Additionally, I will attempt to answer the questions “Where should I open a Italian Restaurant?” and “Where should I stay If I want great Italian food?” 1.3 Target Audience Who will be more interested in this project? What type of clients or a group of people will benefit? 1. Business personnel who wants to invest or open a Italian restaurant in New York. This analysis will be a comprehensive guide to start or expand restaurants targeting the Italian crowd. 2. Freelancers who loves to have their own restaurant as a side business. This analysis will give an idea, how beneficial it is to open a restaurant and what are the pros and cons of this business. 3. Italian crowd who wants to find neighborhoods with lots of option for Italian restaurants. 4. Business Analyst or Data Scientists, who wish to analyze the neighborhoods of New York using Exploratory Data Analysis and other statistical & machine learning techniques to obtain all the necessary data, perform some operations on it and, finally be able to tell a story out of it.
  8. 8. 4 Data Acquisition and Methodology 2.1 Data Source In order to answer the above questions, data on New York City neighborhoods, boroughs to include boundaries, latitude, longitude, restaurants, and restaurant ratings and tips are required.  New York City data containing the neighborhoods and boroughs, latitudes, and longitudes will be obtained from the data source: https://cocl.us/new_york_dataset  New York City data containing neighborhood boundaries will be obtained from the data source: https://data.cityofnewyork.us/City- Government/Borough-Boundaries/tqmj-j8zm  All data related to locations and quality of Italian restaurants will be obtained via the FourSquare API utilized via the Request library in Python. 2.2 Methodology Data will be collected from https://cocl.us/new_york_dataset and cleaned and processed into a data frame. Foursquare be used to locate all venues and then filtered by Italian restaurants. Ratings, tips, and likes by users will be counted and added to the data frame. Data will be sorted based on rankings. Finally, the data be will be visually assessed using graphing from various Python libraries.
  9. 9. 5 Exploratory Data Analysis 3.1 Number of Neighborhoods Foursquare API is very useful online application used my many developers & other applications like Uber etc. In this project I have used it to retrieve information about the places present in the neighborhoods of New York. The API returns a JSON file and we need to turn that into a data-frame. Here I have chosen 100 popular spots for each neighborhood within a radius of 1km. From figure 1 below, it can be seen that the Manhattan have the lowest number of neighborhood while Queens Borough have the highest number. Brooklyn and Staten Island seem to have seem to be in pair. This shows a little bit of competitive attribute between the two boroughs. Using the Folium package, the coordinates of the various neighborhoods bbelonging to the five boroughs were ascertained after requested. This can be found in Figure two. 3.2 Italian Restaurants Per Borough Total number of 233 restaurants were returned from the analysis, each belonging to a particular borough and neighborhood.
  10. 10. 6 Figure 2: Neigbourhood per borough Figure 3 A Snapshot of the Boroughs and Neighborhood around New York
  11. 11. 7 Figure 4: Italian Restuarants Per Borough From Figure 3 above, it can be deduced that Manhattan have the highest number of Italian restaurants despite having the least number of neighborhood. They have up to 100 Italian restaurants in the borough. The Queen borough have the least number with a total of 20. Additionally, Brooklyn and Staten Island are almost on pair showing a high competition attribute between the two.
  12. 12. 8 Figure 5: A picture of the Neighborhoods and Boroughs showing the total number of Italian restaurants Figure 6: Italian Restaurants Per Neighborhood
  13. 13. 9 This shows that Manhattan borough accounts fo the highest number of Borough despite having the smallest number of Neighbourhoods. Figure 4 shows a returned value showing the total of Italian restaurants. 3.3 Italian Restaurants Per Neighborhood From Figure 5, it can be deduced that the neighborhood of Belmont have the highest number of Italian restaurant with over 16 numbers. This is followed by Greenwich Village, then West Village to Lenox Hill which have the lowest. The range of numbers of the Italian restaurant is highly skewed, showing that they are all dispersed throughout the neighbourhoods. From figure 6, it is evidently shown that Belmont Neighborhood belongs to Bronx borough. This means that Bronx borough have the highest of restaurant of a particular neighborhood
  14. 14. 10 Figure 7: figure showing Belmont Neighborhood .
  15. 15. 11 Figure 8: Map Showing the restaurant density of the Neighbourhood and Borough The map shows a high clustered visualization around Manhattan and Lenox Hill, judging from their locations.
  16. 16. 12 Conclusion and Recommendation 4.1 Recommendation and Discussion Queens and The Bronx have the least amount of Italian restaurants per borough. However, of note, Belmont of The Bronx is the neighborhood in all of NYC with the most Italian Restaurants. Despite Manhattan having the least number of neighborhoods in all five boroughs, it has the most Italian restaurants. Based on this information, I would state that Manhattan and Queens are the best locations for Italian cuisine in NYC. To have the best shot of success, I would open an Italian restaurant in Queens. Queens has multiple neighborhoods and has the least number of Italian restaurants making competition easier than in other boroughs. According to this analysis, Queens’s borough will provide the least competition for the new upcoming Italian restaurant, as there is very little Italian restaurants spread or no Italian restaurants in few neighborhoods. Also looking at the population distribution seems like it is densely populated with Italian crowd, which helps the new restaurant by providing high customer visit possibility. Therefore, definitely this region could potentially be a perfect place for starting quality Italian restaurants. Some of the drawbacks of this analysis are — the clustering is completely based only on data obtained from Foursquare API and the data about the Italian population distribution in each neighborhood is also based on the 2016 census which is not up- to date. Thus, there is a huge gap of around 3 years in the population distribution data. Even Though there are many areas where it can be improved, yet this analysis has certainly provided us with some good insights, preliminary information on possibilities & a head start into this business problem by setting the step stones properly.
  17. 17. 13 4.2 Conclusion Finally, to conclude this project, wwe have got a chance to solve a business problem like how a real like data scientists would do. We have used many python libraries to fetch the data, to manipulate the contents & to analyze and visualize those datasets. We have made use of Foursquare API to explore the venues in neighborhoods of New York, then get good amount of data from online. We also applied Visualization technique for insights and used Folium to visualize it on a map. Some of the drawbacks or areas of improvement shows us that this analysis can be further improved with the help of more data and easy coding syntax. Similarly we can use this project to analysis any scenario such as opening a different cuisine restaurant or opening of a new gym and etc. I hope that this project helps as an initial guidance to take more complex real-life challenges using data-science. Find the code for this analysis on github . Find me on LinkedIn!

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