https://github.com/nafisalawalidris/data-science-methodology-
https://github.com/nafisalawalidris/data-science-methodology-
Last synced: 7 months ago
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- Host: GitHub
- URL: https://github.com/nafisalawalidris/data-science-methodology-
- Owner: nafisalawalidris
- Created: 2023-03-18T00:41:28.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-19T00:17:11.000Z (over 2 years ago)
- Last Synced: 2025-01-23T07:12:15.492Z (9 months ago)
- Language: Jupyter Notebook
- Size: 451 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Data Science Methodology
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### Insights ###
- The dataset contains 57,691 recipes, each with 384 ingredients. The data includes a categorical variable cuisine which identifies the type of cuisine for each recipe.
- The value_counts() method can be used to count the number of recipes for each cuisine. Based on the cuisine_counts output, it can be observed that the dataset includes a wide range of cuisines, with Italian being the most common, followed by Mexican and Southern US.
- The histogram of the number of ingredients used in the recipes shows that the majority of recipes use between 5 and 20 ingredients. There are a few recipes with over 50 ingredients, which may be outliers.
- The heatmap of the most commonly used ingredients in each cuisine shows that certain ingredients are more prevalent in some cuisines than others. For example, soy sauce and sesame oil are commonly used in East Asian cuisines, while oregano and cumin are commonly used in Latin American cuisines.