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Name:

Description:

If you like to eat cereal, do yourself a favor and avoid this dataset at all costs. After seeing these data it will never be the same for me to eat Fruity Pebbles again.

Variables:

Fields in the dataset:

  • Name: Name of cereal

  • mfr: Manufacturer of cereal

    • A = American Home Food Products;

    • G = General Mills

    • K = Kelloggs

    • N = Nabisco

    • P = Post

    • Q = Quaker Oats

    • R = Ralston Purina

  • type:

    • cold

    • hot

  • calories: calories per serving

  • protein: grams of protein

  • fat: grams of fat

  • sodium: milligrams of sodium

  • fiber: grams of dietary fiber

  • carbo: grams of complex carbohydrates

  • sugars: grams of sugars

  • potass: milligrams of potassium

  • vitamins: vitamins and minerals - 0, 25, or 100, indicating the typical percentage of FDA recommended

  • shelf: display shelf (1, 2, or 3, counting from the floor)

  • weight: weight in ounces of one serving

  • cups: number of cups in one serving

  • rating: a rating of the cereals (Possibly from Consumer Reports?)

Link To Google Sheets:

Rows:

Columns:

License Type:

References/Notes/Attributions:

 

Acknowledgments

These datasets have been gathered and cleaned up by Petra Isenberg, Pierre Dragicevic and Yvonne Jansen. The original source can be found here

This dataset has been converted to CSV

R Dataset Upload:

Use the following R code to directly access this dataset in R.

d <- read.csv("https://www.key2stats.com/80_Cereals_1615_63.csv")

R Coding Interface:


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