In addition to using pd.merge()
, each DataFrame has its own .merge()
method. For instance, if you wanted to merge orders
with customers
, you could use:
new_df = orders.merge(customers)
This produces the same DataFrame as if we had called pd.merge(orders, customers)
.
We generally use this when we are joining more than two DataFrames together because we can “chain” the commands. The following command would merge orders
to customers
, and then the resulting DataFrame to products
:
big_df = orders.merge(customers)\ .merge(products)
Instructions
We have some more data from Cool T-Shirts Inc. The number of men’s and women’s t-shirts sold per month is in a file called men_women_sales.csv
. Load this data into a DataFrame called men_women
.
Merge all three DataFrames (sales
, targets
, and men_women
) into one big DataFrame called all_data
.
Display all_data
using print
.
Cool T-Shirts Inc. thinks that they have more revenue in months where they sell more women’s t-shirts.
Select the rows of all_data
where:
revenue
is greater thantarget
AND
women
is greater thanmen
Save your answer to the variable results
.