More useful summary tools

Python for Spreadsheet Users

Chris Cardillo

Data Scientist

.mean()

fruit_sales.groupby('store', as_index=False).mean()

Fruit Store Sales on Average.png

Steps to an answer

Fruit store transactions
Total sales by fruit for each store
Sorted sales by fruit for each store
Top row for each store

1: Fruit store transactions

many fruit sales.png

2: Total sales by fruit for each store

totals = fruit_sales.groupby(['store', 'product_name'], as_index=False).sum()

grouped and summarized.png

3: Sorted sales by fruit for each store

totals = (totals.sort_values('revenue', ascending=False)
.reset_index(drop=True))

totals sorted.png

4: Top row for each store

top_store_sellers = totals.groupby('store').head(1).reset_index(drop=True)

Top gross groceries.png

Steps to an answer

# Raw data
fruit_sales

# Summary - by fruit by store
totals = fruit_sales.groupby(['store', 'product_name'], as_index=False).sum()

# Sort the Summary
totals = (totals.sort_values('revenue', ascending=False)
.reset_index(drop=True))

# First row for each store
top_store_sellers = totals.groupby('store').head(1).reset_index(drop=True)

Top gross groceries.png

Steps to an answer

1: Raw Transaction Data

many fruit sales.png

2: By Fruit/Store Summary

grouped and summarized.png

Steps to an answer

2: By Fruit/Store Summary

grouped and summarized.png

3: By Fruit/Store Sorted

totals sorted.png

Steps to an answer

3: By Fruit/Store Sorted

totals sorted.png

4: First Row Per Store

Top gross groceries.png

Your turn!

Python for Spreadsheet Users