Learn
Working with Multiple DataFrames
Mismatched Merges
In our previous examples, there were always matching values when we were performing our merges. What happens when that isn’t true?
Let’s imagine that our products
table is out of date and is missing the newest product: Product 5. What happens when someone orders it?
Instructions
1.
We’ve just released a new product with product_id
equal to 5
. People are ordering this product, but we haven’t updated the products
table.
In script.py, you’ll find two DataFrames: products
and orders
. Inspect these DataFrames using print
.
Notice that the third order in orders
is for the mysterious new product, but that there is no product_id
5 in products
.
2.
Merge orders
and products
and save it to the variable merged_df
.
Inspect merged_df
using:
print(merged_df)
What happened to order_id
3?