Week 102 - Snowpark & Python

Snowpark Pandas! Finally, our love-hate relationship with Pandas becomes one completely full of love as we use familiar, well-known syntax on the distributed Snowflake system.

This week's challenge tasks you with using Snowpark Pandas to answer 5 rapid-fire questions!

Below is your start-up SQL code:

create or replace stage frosty_stage url = 's3://frostyfridaychallenges/challenge_102/';

Then open up a notebook and place the following in the first cell:

import modin.pandas as pdimport snowflake.snowpark.modin.pluginfrom snowflake.snowpark.context import get_active_sessionsession = get_active_session()clothes_shop_df = pd.read_csv('@frosty_stage/clothes_shop_purchases.csv')

After that, you're ready to answer the following 4 questions!

1. At what hour of the day are the majority of our sales?
2. Which server sold the most?
3. What is the total price like if we deduct 20% for tax on the first five items?
4. What would the biggest till number be if we merged tills 4 and 5?

1:

2:

3:

4: