Recipes Selection with Pandas - manipulation of large food dataset

Overview

This project uses a large public dataset and Pandas to select a small subset of the data based on specific criteria.

Objective: For a new cooking website, 30 unique modern dessert recipes are needed. A selection is to be made from a public dataset from food.com.

image: screenshot from Kaggle.com - selected dataset

The relevant data available on kaggle.com contains two datasets:

1. Recipe dataset (522,517 recipes from 312 different catagories)
2. Reviews dataset (1,401,982 reviews from 271,907 users)

Data Import

Both files in csv format are imported into Pandas.

Data Manipulation

In order to find the right selection from more than half a million options, the data manipulations of both sets include:

-value counts
-df.loc
-data type and field conversions
-left join
-saving to cvs and more

Final Selection

A final dataset containing 30 dessert recipes is reached and the file saved as a csv file for future use.