Can a Starbucks a Day Keep the Doctor Away?Chris LouieBlockedUnblockFollowFollowingFeb 8Starbucks was there for me when no-one else wasWhen I was a student I had a 45 minute commute every morning to my university, and was always in a rush to get to class on time.
And in order to be a functioning student, I made sure that every morning I’d make a mobile order to my local Starbucks for either a Venti Caramel Macchiato (with 2 pumps of vanilla syrup and less caramel drizzle) or just a triple shot Espresso over ice.
As a result, I’ve ordered some item from Starbucks every day for almost 4 years and have grown to be a supporter of the brand and team members I’ve met throughout the years.
And yes, I realized that if I had woken up earlier and purchased a coffee maker or a Nespresso machine, I would have probably saved a lot more money in the long run.
But this article isn’t about how hindsight can show you how much money you’d save if you weren’t dependent on Starbucks for your caffeine fix — this article is about the nutrition facts of Starbucks beverages and how you can make pivotal choices for your diet without giving up on your oh-so-beloved Starbucks.
With that, for those of us who depend on Starbucks for our everyday fix, this article was made just for you.
Whether you’re a consumer or skeptic of retail caffeinated beverages, I hope you’ll enjoy this exploratory data analysis.
To just preface and add some historical context from the Starbucks ‘About Us’ — Starbucks began in 1971 in Seattle’s historic Pike Place Market, with two things in mind: to ‘share great coffee with our friends and make the world a little better.
’ From the beginning, Starbucks set out to be a different kind of company.
One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection.
Map of Starbucks locations : Wikimedia CommonsAnd now in 2018, Starbucks has over 28,000 stores worldwide, with a Fiscal 2019 Guidance of opening approximately 2,100 net new Starbucks stores globally, I would not bet against Starbucks becoming one of the world’s most recognizable brands by 2030.
One of the things that interests me about Starbucks is their menu.
Outside of their holiday season promotions, I’ve noticed that products can get shelved, and aren’t displayed on some in-store menus.
I don’t know if it’s some wide range AB testing that Starbucks has for their stores, or a glitch in the matrix, but I find it being one of the alluring things about Starbucks.
TLDR; If you’ve never come across a Starbucks drink/brand/logo in your lifetime, you will soon — very soon.
Starbucks Nutrition DataGetting started with this exploration, I was looking at the Starbucks Nutrition dataset uploaded on Kaggle.
But quickly after looking at the data, I found it to be very limited.
After a bit of searching around, I found this PDF table from Starbucks with a long list of their beverages and their Nutrition Facts, given the size of the beverage and variation of milk option.
Reading tables from PDFs is tricky, but with the help of tabula-py and their documentation, anybody can read a table from a PDF and export it to their file format of choice(CSV, JSON, XLS, etc.
Taking a quick peek into the data, the first thing I found was that this Starbucks table covers many variations for almost every single beverage.
Those variations come with their Size, Milk option, and any add-ons a customer wants(extra shot of espresso, extra syrup pumps, etc.
) Finally after some cleaning, I drafted up some visualizations.
You’ll be able to interact with the visualizations I created using plotly, and you can find the notebooks to all the work in my GitHub repository.
In the repository there is a rough draft with mostly comments and TODOs I set for myself, but the main Starbucks-EDA notebook is much cleaner.
A look into the PDFStarbucks beverages by categoryThe PDF categorizes all the beverages in a row with all NaN values besides the title of the category (i.
Frappuccino, Espresso, Latte, etc.
) With that, I created new data frames by category:And to make this project more interesting, to decide which Starbucks products to include in the data frame, I sent out a one question survey to my peers and asked them to send it to their peers.
That question was :“What is(are) your favorite drink(s) as Starbucks?”After 2 days of surveying, I received 89 responses and used those responses to construct the data frames.
Bar plot of responses to the surveyQuick Guide to the VisualizationsTo view the interactive plots, all you have to do is click on the box in the middle that says ‘Show Embed’ if you want to view the interactive plot.
If the interactive plots are not working, be sure to be using a compatible browser such as Google Chrome, or the Medium app for mobile device viewers.
For convenience, below are a few gifs of what you can expect from the different interactive plots.
What to expect from an Interactive Bar PlotWhat to expect from an Interactive 3D Scatter PlotIn the following interactive plots, you will find labels at the bottom of the embedded plot describing what type they are and a brief summary of the visualization in their respective category.
Caffeinated Beverages measuring Caffeine and Calories by SizeFrappuccinosFrappuccino Interactive Bar PlotAbove is a bar plot of all the Frappuccino offerings, which was the only data frame that I wanted to include all the variations because it’s such an iconic product.
Below is an interactive 3D scatter where the X axis is the sugar in milligrams, the Y axis are the product names (I don’t believe all of the names fit on the embedded Y axis), and the Z axis is the milk option.
If you notice the coordinate markers are scaled by their color, and that color is scaled by each product’s calorie count by their specific variation.
Frappuccino Interactive 3D Scatter PlotEspressosEspresso Beverages Interactive Bar PlotAbove is a bar plot of the espresso products that were pooled from the survey, and below is a 3D scatter plot of those products with the X axis being the caffeine values, the Y axis being the product names, the Z axis being the milk option, and the color scale is the amount of dietary fiber in grams.
Espresso Beverages Interactive 3D Scatter PlotTea LattesTea Latte Interactive Bar PlotAbove is a bar plot of the tea latte products that were pooled from the survey, and below is a 3D scatter plot of those products with the X axis being the calorie count, the Y axis being the product names, the Z axis being the milk option, and the color scale is the amount of total fat in grams.
Tea Latte Interactive 3D Scatter PlotSome quick InsightsThe 5 most popular beverages were:Caramel Macchiato (14 votes)Chai Tea Latte (11 votes)Mocha Frappuccino (10 votes)Pike Place Roast (8 votes)Cold Brewed Coffee (8 votes)An order of a Venti Iced White Chocolate Mocha has the most Calories at 630 calories in one drink.
An order of a Brewed Coffee — True North Blend Blonde Roast has the most Caffeine at 475 mg of Caffeine in one drink.
A Java Chip Frappuccino® Blended Beverage with Whipped Cream and NonFat milk has the most Sugar at 89 grams of sugar in one drink.
ConclusionOver the course of the last two decades there has been a raging debate about caffeine and whether or not it is good or bad for you.
The argument against caffeine is that it can effect or rapidly increase risk of human body function, anxiety, and heart disease.
And the argument against this claim is that every human is different and depending on an individual’s pre-existing conditions, you may find caffeine to benefit or detriment your health.
Overall, caffeine is not produced inside of the human body.
So by consuming caffeine, you’re forcing your body to change the way it internally works.
Of course, I myself am a proponent of caffeine, but I’ll let you, the reader, make the best judgment for yourself.
Bringing it back to our big question:Can a Starbucks a Day Keep the Doctor Away?My answer:Low calorie espresso drinks might, but Frappuccinos and some venti sized drinks won’t.
Thank you and I hope you enjoyed reading!.