Jupyter notebook:
- Creation and filling of the SQL database
- View tables
- Creating Pandas dataframes for basic SQL tables
- Show the names of sweets which weight is 300
- Show the names of sweets which cost is 100
- Find a list of sweets that start with "M"
- Names of sweets that have a cost of 150 and a weight of 300
- Names of sweets which cost is from 200 to 300
- Sort names of sweets by ID in descending order
- Find the name of the sweet with the highest price
- Which cities have storehouses?
- Find manufacturers in more than one city
- Find the names of all chocolates
- Find the number of sweets for each type. In the response, display the name of the type and the quantity
- Find types of sweets that have more than 2 quantity
- Which cities have storehouses with sweets "Milty"?
- How many sweets are in each storehouse?
- Find storehouses with more than 8 sweets
- Selection
This code was prepared for this article: https://medium.com/@axegggl/sql-vs-pandas-all-the-most-popular-queries-2b9e0cfa9f97
Python 3.10.5 numpy 1.23.0 pandas 1.4.2