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Data preprocessing, cleaning, <Analysis> & plotting πŸ“Š of Food Recipies Dataset (from Kaggle). 🐍 Libraries used: Pandas, Matplotlib, Seaborn, Plotly.πŸ“ˆ

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Data Analysis of Food Recipes.

  • Data Set Link (Kaggle): Link
  • Notebook Link: Link
  • Libraries used: Pandas, Matplotlib, Seaborn, Plotly.
  • Data was processed & cleaned; Different Cuisines, Diets & Course of the meal were compared with their total cooking time, total preparation time & servings to gather insights from the data.

Some of the insights from the data is:

  • South Indian recipes have more servings & are popular.
  • Salads consume less time to prepare.
  • High Protein Vegetarian course consumes high amount of time (on an average) to prepare.
  • etc.

Images of the graphs/plots:

diet-servings graph

pairplot

pie chart

scatter plot

Correlation image


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Data preprocessing, cleaning, <Analysis> & plotting πŸ“Š of Food Recipies Dataset (from Kaggle). 🐍 Libraries used: Pandas, Matplotlib, Seaborn, Plotly.πŸ“ˆ

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