Learn
This lesson introduced some methods for combining multiple DataFrames:
- Creating a DataFrame made by matching the common columns of two DataFrames is called a
merge
- We can specify which columns should be matches by using the keyword arguments
left_on
andright_on
- We can combine DataFrames whose rows don’t all match using
left
,right
, andouter
merges and thehow
keyword argument - We can stack or concatenate DataFrames with the same columns using
pd.concat
Instructions
1.
Cool T-Shirts Inc. just created a website for ordering their products. They want you to analyze two datasets for them:
visits
contains information on all visits to their landing pagecheckouts
contains all users who began to checkout on their website
Use print
to inspect each DataFrame.
2.
We want to know the amount of time from a user’s initial visit to the website to when they start to check out.
Use merge
to combine visits
and checkouts
and save it to the variable v_to_c
.
3.
In order to calculate the time between visiting and checking out, define a column of v_to_c
called time
that calculates the difference between checkout_time
and visit_time
for every row.
4.
Use .mean()
to calculate the average time to checkout and print that value to the terminal.
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