Lab | SQL Queries 9

In this lab, you will be using the Sakila database of movie rentals. You have been using this database for a couple labs already, but if you need to get the data again, refer to the official installation link.

The database is structured as follows:

Instructions

In this lab we will find the customers who were active in consecutive months of May and June. Follow the steps to complete the analysis.

• Create a table rentals_may to store the data from rental table with information for the month of May.

• Insert values in the table rentals_may using the table rental, filtering values only for the month of May.

• Create a table rentals_june to store the data from rental table with information for the month of June.

• Insert values in the table rentals_june using the table rental, filtering values only for the month of June.

• Check the number of rentals for each customer for May.

• Check the number of rentals for each customer for June.

• Create a Python connection with SQL database and retrieve the results of the last two queries (also mentioned below) as dataframes:

  • Check the number of rentals for each customer for May

  • Check the number of rentals for each customer for June

    Hint: You can store the results from the two queries in two separate dataframes.

• Write a function that checks if customer borrowed more or less films in the month of June as compared to May.

  Hint: For this part, you can create a join between the two dataframes created before, using the merge function available for pandas dataframes. Here is a link to the documentation for the merge function.