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https://github.com/surajv311/data_analysis-food_recipes_ds
Data preprocessing, cleaning, <Analysis> & plotting 📊 of Food Recipies Dataset (from Kaggle). 🐍 Libraries used: Pandas, Matplotlib, Seaborn, Plotly.📈
https://github.com/surajv311/data_analysis-food_recipes_ds
data-analysis kaggle-dataset matplotlib numpy pandas plotly seaborn
Last synced: about 3 hours ago
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Data preprocessing, cleaning, <Analysis> & plotting 📊 of Food Recipies Dataset (from Kaggle). 🐍 Libraries used: Pandas, Matplotlib, Seaborn, Plotly.📈
- Host: GitHub
- URL: https://github.com/surajv311/data_analysis-food_recipes_ds
- Owner: Surajv311
- Created: 2021-09-18T18:49:46.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-10-19T02:52:31.000Z (about 3 years ago)
- Last Synced: 2023-08-18T11:54:16.237Z (over 1 year ago)
- Topics: data-analysis, kaggle-dataset, matplotlib, numpy, pandas, plotly, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 6.82 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Data Analysis of Food Recipes.
- Data Set Link (Kaggle): [Link](https://www.kaggle.com/kanishk307/6000-indian-food-recipes-dataset)
- Notebook Link: [Link](https://github.com/Surajv311/Data_Analysis-Food_Recipes_DS/blob/main/Data_Analysis--Food-Recipies.ipynb)
- 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:
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