It was two months ago that I first saw the Data Geek Challenge at SCN and I even got a badge for accepting it.

DataGeekBadge.jpg

Then time flew really fast before I got to work. Last month I got into serious business and started searching for some datasets. The real challenge was finalizing a dataset. The datasets available ranged from serious issues like heart disease and global warming to funny ones like the color of M&Ms in a packet 😆 . So finally what did I settle for? Something in between.

The following analysis is on the dataset I created from the nutrition information available from famous fast-food chains(as published by the restaurant chains). The top five brands to be particular. Only the menu listings for food are considered here. I have left out the beverage list (too confusing with different measurements and serving sizes). Believe me when I say that the hardest part was transferring all the nutrition information from the tables in pdf to excel. The rest was just child’s play in SAP Lumira.

About the data:

Nutritional information

5 fast food restaurants – Mc Donalds, Subway, Wendy’s, Burger King, Taco Bell

715 menu items

16 attributes –   16 attributes – ServingSize(g), Calories, Calories from Fat, Total Fat (g), Saturated Fat (g), Trans Fat (g), Cholesterol (mg), Sodium (mg),  Carbohydrates (g), Dietary Fiber (g), Sugars (g), Protein (g), Vitamin A, Vitamin C, Calcium, Iron

About the Analyst:

He is a Data Geek aspirant and not your nutritionist 😛 .

To start with, I wanted to find the restaurant that offers a wide range of choices. How do the restaurants rank in terms of menu size?

Pretty easy, I just used a simple column chart with the restaurant names in X-axis and Menu(count distinct) in the Y-axis.

Subway tops the list with 171.

Subway_171.jpg

Next I wanted to see who serves me the highest amount of calories.

For this I used a donut chart with all menu items and calories represented by the pie sectors and I used the total calories for the pie depth.

Menu_Calorie.jpg

Colorful, but definitely not very useful. So, I narrowed it to the restaurant names instead of the menu items. But this time I used the ‘pie chart with variable slice depth’.

I expected it to be Subway, since it had the biggest list of menu items, but surprisingly I see Burger King steals the spot.

Restaurant_Calorie.jpg

What about fat you say. Let’s see about that. I use a 3D column chart to see the total fat in all menu listings and the calories that came from all that fat. Wendy’s did not have the information about ‘Calories from Fat’ so I filtered it out.

Total Fat.jpg

As a nutritionist…oops data analyst, I am worried about the heart too. Let’s check out the cholesterol levels of the food that we eat at these places.

Let’s see the top ten bad-boys in this category,

Cholestrol.jpg

Of course there are a lot of good things in there called proteins and vitamins. Let’s get our facts straight on these using an area chart. We can do this only for three brands since Wendy’s and Burger King do not have any information on vitamins served.

Protein.jpg

Mc Donald’s seems to fare well than Subway even though it has a lesser count of menu items.

And lastly, my favorite. What goes into to the menu names that make it appealing to us?

I split the menu names across all restaurants into individual words and fed it to Lumira as a separate file and what better chart to analyze this information than the ‘tag cloud. The tag cloud is one of my favorites.

Tag_Cloud1.jpg

All the analyses has left me hungry and wanting a Grilled Sandwich with Cheese and Chicken and Egg.

And if you don’t like that filter it out and you have other options too,

Tag_Cloud2.jpg

Bon Appetit,

Benedict

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32 Comments

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  1. Suseelan Hari

    Hi Benedict,

    Good Day!

    Fantastic Work!

    Nice analysis! I appreciate.

    Keep sharing new things. Have a nice day! 😆

    Mouth full of water! 😆 😆 😆

    Regards,

    Hari Suseelan

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      1. Benedict Venmani Felix Post author

        Thank You very much Suseelan and Kumar:)

        May be I should put a link to all these fast food restaurants here so that people can order some food once they have read the blog 😆

        Regards,

        Benedict

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  2. Irshaad Bijan Adatia

    Benedict,

    There’s a lot of worthwhile information here, it actually made me a little hungry. I think today for lunch I’m going to go for some Subway! *haha*

    Where did you find this great information? We’d love to add it to our list… Data Sources

    This is definitely something that is worth sharing with the rest of the world through Social Media too!

    Check out our post from our twitter account @SAPLumiraExpert

    We’re def. looking forward to having more posts and visualizations from you Benedict!

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    1. Benedict Venmani Felix Post author

      Hi Bijan,

      thank you for the nice comments 🙂 .

      I consolidated the data from the nutritional information available as pdf from all the above mentioned restaurant sites. I will be happy to share the dataset with you if you can give me a mail ID. I already sent the .svid file to datageek@sap.com

      Benedict

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  3. Anthony Gandouin

    Hello Benedict,

    Great Presentation of your work! I found it quite interesting that Chicken has the largest impact on our decisions in the menu name.

    Keep up the good work, looking forward to more like these!

    – Anthony

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  4. vasanth rajagopal

    HI Vasanth,

    You are going places buddy!  Nice thought and Execution..! Presentation as simple as it gets for anyone and they can make easy connect..! Congratulations ! and keep up your spirits!

    ~ Vasanth Rajagopal

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