#DuoDare 4 – Nutrition

#DuoDare 4 – Nutrition

Welcome to #DuoDare.  The Data Duo is back at it with a little friendly competition.  Each month, one of us will pick a data source and dare the other to viz it better.  We will pass our visualizations to each other for some feedback and present them to the community (you) to be the judge.  Please fill out the Google Form to vote for your favorite duo viz.  Our bragging rights are on the line so we need you more than ever!

Don’t forget, your monthly vote gets you an entry (up to 12) in our drawing at the end of the year for some free swag!

Full rules and vote tracker

The Data

We just passed Thanksgiving and I ate a lot of food as expected. Thinking about food almost all November made me think of a dataset that would be particularly nice to visualize around holiday time. So, I decided to search for data about nutrition in our food items. I came across USDA’s nutrient database and thought it was a nice comprehensive dataset of variety of food items along with its caloric content and nutrient values.

I also wanted something non-geo spatial so Adam doesn’t kick my butt again this month! Now it’s a different story if he actually wins this month also because then it’s the close of #DuoDare! I probably should pack my bags and go home. 😂

Adam’s Reaction to the Data

Last month, I chose a data set ripe for some geospatial analysis.  It went a bit viral with over 305 thousand views (wow, that was unexpected)!  Even with all those views, I barely eked out a win in month 3.  I knew this month Pooja would come back with a #DuoDare to push me into an uncomfortable place.  Boy, was I was right!

She sent over an Excel file with two tabs, Calories and Nutritional Information.  When I first saw the data, I was like “how in the hell am I supposed to visualize that?”

There was really nothing that could be done to compare or analyze this data set since all of the serving sizes were different measures (i.e., ounces, cups, Tbsps, slices, loafs, cakes, pies, etc.).  Some foods had multiple measures.  There were 961 foods in the calorie table and only 180 in the nutritional table so I focused just on the calories.  This left me with weight, carbs, protein and calories for measures, which wasn’t very interesting to me.

I decided to go full-on #Poojatastic and focus on only one food at a time.  This viz is mostly design work using some images from Photoshop, text boxes, and padding in Tableau.

I created all new measures based on the number of servings selected and daily caloric intakes by gender.  I thought adding a bunch of dynamic calculations would add enough interest and make the story about what is interesting to the reader.

The Away Team: Adam’s viz

Pooja’s feedback: I love the design. Simple, to the point and lets the user play with all the different parameters. What an awesome idea to use male and female figures to show bars as depicting % daily caloric intake. I really like the little softer touches like adding a suffix of ‘servings’, ‘cals’ in the parameters.

I love how the cards are dynamic too. You can enter the calories and it dynamically updates the percent value. Placement of the cards by male and female figures is intuitively designed. Also like the idea of ‘losing your weight’ factor to add to the story! Well done, Adam!

The Home Team: Pooja’s viz

Adam’s feedback: Ok, when Pooja showed me this I was like “damn, you’re gonna kick my butt this month”.  She did a great job of designing an informative viz.  I am big fan of the 100% bar charts to measure progress toward a goal.  I use these at work all the time!  Poo probably does too, so it is cool to see cool things we do at work make it back into our personal work.

As always, Pooja does a great job leading a reader through a story with simple elements and lines.  I especially like the info icon wrapped into the subtitle with the use of borders

This was a really challenging data set, but I think she did great with it.  One thing that could be improved is the filter experience.  Poo combined the fields so you wouldn’t have to make multiple filter selections, but the serving size dimension was ordered first in front of the food.  As a result, the foods are not alphabetical and you have to use the search box to look for foods or scroll down.  Picky I know, but I have to give her some constructive feedback!

Great job Poo!

It’s up to you now, vote for your favorite viz below.

Voting is closed for this month, but check out the #DuoDare page for the next one.

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