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Personal Data Exploratory Project in Python. Data extracted from AllRecipes.

Home Page: https://www.kaggle.com/datasets/dimitryzub/allrecipes-all-us-recipes-by-state

Jupyter Notebook 99.65% Python 0.35%
data data-visualization dataexploration dataextraction matplotlib pandas python seaborn webscraping

allrecipes-us-recipes-by-state-analysis's Introduction

AllRecipes - USA Recipes Analysis By Every State

Project Goals

  1. What is the most common ingidients across all recipes? Top 3-5-10 ingidients.
  2. What is the most ingidient(s) by State?
  3. Which state has more avarage number of reivews?
  4. What most loved (analyzed by nubmber of reviews/rating) dish each state have? Like Arizona - beef.
  5. What is an avarage Prep/Cook time per State?
  6. What is an avarage Servings per State?
  7. Which state has the biggest avarage of Calories/Fat/Carbs/Protein/etc?
  8. What is the most popular recipes category?
  9. What is the avarage reviews/rating count per category?
  10. What is the most popular recipe provider (Recipe by "...")

Key Takeaways

  1. Arizona has higher avarage reviews: 418.
  2. Desserts category is the most popular.
  3. Avarage recipe Rating: 4, Reviews: 132.
  4. Category with the higher number of reviews is 'Bread': 7722 reviews.
  5. Most reviewed dish
  6. Avarage cook time (preparation and cooking itself) is around 183.4 miuntes.
    • Italian, Pork and Everyday cooking categories has the longest total cook time.
  7. Top categories with avarage highest servings: Cookies (36), Sauces and condiments (26), Everyday cooking (24).
  8. Wayoming has the longest avarage cook time: 159 min.
  9. Illinoins has the highest calories.
  10. Highest nutritions per category:
    • Calories: Everyday Cooking (2057g)
    • Fat: Meat and Poultry (170g)
    • Carbs: Mini Foods (177g)
    • Protein: Seafood (118g)

Data Sources

Publicly available from the AllRecipes - U.S. Recipes by State. Not an API, parsed by myself using own script.

Every recipes from all states has been collected.

Analysis Methods

  • Exploratory analysis.

Tech Stack

What more could be done

  1. Extract individual ingridient.
  2. Properly sort stacked bar chart.

Explore Yourself

Open in Gitpod

Kaggle dataset: https://www.kaggle.com/datasets/dimitryzub/allrecipes-all-us-recipes-by-state

allrecipes-us-recipes-by-state-analysis's People

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