How healthy is the meal: an analysis of recipe data

Today I find epicurious data on my plate and decided to look into the interconnection between ratings, nutrients, ingredients, meals, seasons, holidays and cooking techniques.

Overview of recipe data

The dataset from Epicurious website contains the rating, nutritional component (calories, fat and protein) as well as tags of recipes, which looks like this:

These tags are also used in navigation menus.

Each recipe have multiple tags conveying a plurality of information:

  • state name: i.e. Alabama
  • meal type: i.e.brunch
  • holiday: i.e.4th of Jul
  • season: i.e.summer
  • dietary concerns: i.e.vegetarian
  • technique: i.e.braise
  • ingredient: i.e.beef

Rating vs nutrients

On the 5-point rating scale we classify 4–5 rating as good, 3 as ok, less than 3 as bad.

We can see the better rated recipes have more calories, proteins, sodium and in general more fat.

Next we can look at content of calories, fat, protein, sodium among meals tagged with different seasons, holidays, techniques etc.

Nutrients vs meals

number of recipes by meal type

We observe brunch recipes tend to be low in fat, while breakfast is relatively high in protein and sodium.

Nutrients vs seasonal meals

number of recipes by season

Not much variation between meals of different season in terms of protein and sodium.

Nutrients vs holiday meals

number of recipes by holiday

Nutrients vs cooking techniques


This is #day54 of my #100dayprojects on data science and visual storytelling. Full code on my github. Thanks for reading. Suggestions of new topics and feedbacks are always welcomed.