You will need to access our MySQL database for this challenge. The database credentials will be sent to you by e-mail.

After accessing our database, create queries using the schema looqbox_challenge to answer the following questions:

1. What are the 10 most expensive products in the company?
2. What sections do the 'BEBIDAS' and 'PADARIA' departments have?
3. What was the total sale of products (in $) of each Business Area in the first quarter of 2019?

As a new member of the crew, your mission now is to create a dynamic function in Python, on the most flexible of ways, to produce queries and retrieve a dataframe based on three parameters:

• product_code: integer

• store_code: integer

• date: list of ISO-like strings

• Date e.g.

  • ['2019-01-01', '2019-01-31']

It should look like this my_data = retrieve_data(product_code, store_code, date)

Make your team proud!

Extra instructions:

• Retrieve all columns from table data_product_sales;
• Imagine people from other teams will also utilize this function!

Query 1:

SELECT
      STORE_CODE,
      STORE_NAME,
      START_DATE,
      END_DATE,
      BUSINESS_NAME,
      BUSINESS_CODE
FROM data_store_cad

Query 2:

SELECT
        STORE_CODE,
        DATE,
        SALES_VALUE,
        SALES_QTY
FROM data_store_sales
WHERE DATE BETWEEN '2019-01-01' AND '2019-12-31'

In addition, he gave you this set of instructions:

• Use the queries as they are (do not modify them or create a new one);

• Please filter the period between this given range:

  • ['2019-10-01','2019-12-31']

Create at least one chart using the table IMDB_movies. The code must be in Python, and you are free to use any libraries, data in the table and graphic format. Explain why you chose the visualization (or visualizations) you are submitting.

• MySQL database
• Python

• Send an e-mail to the person that you are in contact within Looqbox!
• Your answer must be sent in PDF format with the code snippets used in each question, as well as the result obtained (values, tables, graphs)

• MySQL documentation
• Data Visualization Catalogue