Move from Excel to Python with Pandas Transcripts
Chapter: Case study walk through: Sales commissions
Lecture: Combining customer sales reps
0:00 in the previous exercise, we looked at customer information and figured out the effective sales
0:05 commission rate per customer. But what we need to figure out now is how do
0:09 we pull in the sails rap associated with each customer?
0:13 So I'm going to create a new notebook,
0:15 and I'm keeping my original notebook open because I may want to copy and pay some
0:20 of the data between so I can leverage the work I did in the past.
0:23 So in this example, I started my new notebook and filled in the information at
0:27 the top. Now I'm going to give my imports and the other piece on one
0:31 of leverages the data that I already have to read in the file so and copy
0:37 and paste that over. It's still going to read in our customer master.
0:40 I'm still gonna leave that report file in place so that I can use it in
0:44 the future, and then we'll remember when we read in this file.
0:48 We already figured out how to read in the file using the ZIP code correctly.
0:52 I'm gonna call this a different data frame,
0:54 though they call it the of Customers.
0:56 And the other thing I'm gonna do.
0:58 It's actually specify the sheet name,
1:02 and the reason it worked before is because customers is the first sheep name.
1:07 Now we've read in her file,
1:09 and the other sheet is the sales reps.
1:13 So let's go ahead and read that in a swell.
1:21 This is just the sale sheet.
1:29 Now we read in the sales rep.
1:30 So we have the sales rep information and our customers,
1:34 and we want to join these two data frames.
1:36 Together. You'll notice a challenge.
1:38 The sales reps are identified by region,
1:41 but our customers on Lee have a state,
1:43 so we don't have a good way to tie those two together.
1:48 So let's walk through how we would do that.