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_onandright_on - We can combine DataFrames whose rows don’t all match using
left,right, andoutermerges and thehowkeyword 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:
visitscontains information on all visits to their landing pagecheckoutscontains 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.
Sign up to start coding
By signing up for Codecademy, you agree to Codecademy's Terms of Service & Privacy Policy.