Which Starbucks Coffee Store Amenities Are the Most Popular?

Jhonasttan Regalado
Posted on Nov 12, 2016

Problem

As I’m walking from Grand Central Station to the NYC Data Science Academy for my first day of class, I’m thinking of which Starbucks Coffee store serves breakfast sandwiches. It is a journey in trial and error and wasted time as I walk into stores along my path until I find the right one.  Providing a solution to this problem was the basis for project three of the NYC Data Science boot camp. The scope of the project (solve a business problem using web scraping technology and present your insight) was a great opportunity to use Scrapy (a web scraping framework) for data capture, R Studio for data analysis and CARTO to prototype a web based product. My solution allows end users to view the Starbucks Coffee Store amenities and their locations in one place. Go ahead, give it a try here.

Technology Scope

  • Scrapy for web scraping stores info including their amenities via the Starbucks Coffee Store Locator website
  • R Studio for EDA (Exploratory Data Analysis)
  • CARTO for rapid web-based product development
  • MCA (Multiple Correspondence Analysis) for analyzing commonalities between the amenities

You can view the CARTO based end user product here.

cartogui

Process

The store locations are distributed across multiple URLs, spanning New York City. The web browser image below highlights the geospatial (longitude / latitude) coordinates within the URL.

starbucksstorelocatorsite

 

Most of the processing work is performed within Scrapy, the magic sauce that allows you to scrape web sites, munge and process the data for analysis and feed to CARTO for map visualization. The following steps were performed within Scrapy:

  • Regex (regular expressions) for creating amenities features - used as filter criteria in CARTO map layers
  • HTML to wrap store locations as hyperlinks - CARTO renders fields in HTML format out of the box

pythonspyder

The Spyder framework integrates web scraping and Python programming for a flexible and adaptable solution to capture and process web-based content.  R Studio provides a smooth interface and great libraries for EDA to gain insight from the data. The CARTO dataset upload and mapping process is intuitive and allows you to visualize your data on base maps within minutes.

Analysis

EDA in R Studio identified the most common and least common amenities within stores.

amenitiesbarplot2

Five most common amenities:

  • LB: LaBoulange
  • WA: Oven-warmed Food
  • LU: Lunch
  • DR: Digital Rewards
  • XO: Mobile Order and Pay

Five least common amenities:

  • DT: Drive-Through
  • EM: Starbucks Evenings
  • WT: tbd - Walk-T
  • FZ: Fizzio Handcrafted Sodas
  • hrs24: Open 24 hours per day

MCA(Multiple Correspondence Analysis) was performed to analyze the systematic patterns of variations with the amenities. The process requires the features to be of categorical data type (factors in an R dataframe).

amenitiesmca

Based on eigenvector values, the clusters identify amenities with the most commonalities. In the diagram above, the cluster on the bottom right represents the most common amenities across 200 store locations. The cluster to the left has a lower distribution across store locations. Amenity FZ (Fizzio Handcrafted Sodas) stands out as having high direction from the zero intercept. It is the only amenity found in one store location within NYC and perhaps worthy of highlighting to Starbucks Coffee consumers.

Conclusion

Combining Open Source and vendor applications (Scrapy, R Studio, CARTO) allowed me to deliver an interactive product that uses a website as the data source within a two week time line. The web app prototype enables end users to visually explore, analyze and find Starbucks Coffee stores with the most / least common amenities. But most importantly, you can view a store's amenities with a minimum amount of clicks.

cartomap

Follow up

  • Highlight the Most / Least common amenities when the user hovers over a store location in CARTO
  • Create a Map Layer for Shiny application Citibike Analysis, allowing users to locate Starbucks Coffee stores based on amenities and proximity

Acknowledgement

  • Concept / Development / Design: Chris Valle, Joshua Litven, Fred Cheung, Conred Wang, Chris Makris, Zheyu (Sammy) Zhang
  • CARTO End User Testing: Carlos Peguero, Jeffrey Regalado, Yasmin Regalado, Cris Macario, Alexander Ryzhkov

Source code is available at GitHub.

About Author

Jhonasttan Regalado

Jhonasttan Regalado

Jhonasttan Regalado is an established leader and technologist with domain expertise in Global Markets Trading and a Masters of Science in Management of Technology from the NYU Tandon School of Engineering, Polytechnic Institute. With practical knowledge and a...
View all posts by Jhonasttan Regalado >

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spravocnikovami February 28, 2017
Данный портал spravocnikpolekarstvam.ru по сути своей по праву считается абсолютно бесплатным фармакологическим либо фармацевтическим справочником онлайн. Для удобства и простоты пользования порталом в верхнем правом углу, над меню под названием "Общая часть", имеется модуль поиска: сюда следует вбить имя лекарственного препарата и в итогах поиска будут показаны соответствия, найденные во всех без исключения разделах вебсайта. Медицинских справочников лекарств на сегодняшний день большее множество, но не взирая на такое множество информационных систем, их не становится никоим образом меньше. Действительно, разобраться в потоке все новых и новых фармацевтических средств оказываются все сложнее и труднее. И фармакологическая гонка все намного больше напоминает гонку вооружений или борьбу за завоевание вселенной. Теперь и обыкновенному клиенту необходимо соображать в тонкостях и аспектах выпуска лекарственных средств, или хотя бы суметь сориентироваться. Русский рынок фармацевтических средств претерпел значительные изменения в ходе последних 5-10 лет. Серьёзно убавились объемы выпуска лекарственных препаратов на соответствующих производствах на территории Российской Федерации; субстанции лекарственных средств на сегодняшний день синтезирует только 21 предприятие, которые выпускают антибиотики и витамины, и только 9 - синтетические вещества. нифедипин рецепт на латинском

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