Move from Excel to Python with Pandas Transcripts
Chapter: Data wrangling with Pandas
Lecture: Walk through of data types in Excel

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0:00 Before we do some work in pandas,
0:01 I'm gonna walk through a couple excel examples of how we can manipulate a daytime data
0:07 and then show how we would do that and pandas.
0:10 So I've opened up my sample sales details file,
0:12 and there's a column See, that has the purchase date.
0:15 So what if during our analysis,
0:17 we wanted to get the month associated with that purchase state,
0:20 we would enter a formula that looks something like this and copy that down to eat
0:25 row. We could do a similar thing for the day.
0:28 We want to do that for the year,
0:31 relatively straightforward. And just for the sake of talking about data types,
0:36 what would happen if we tried to do the same formula?
0:39 But maybe did I'll call him be,
0:41 too, which is not a year we get evaluator.
0:45 So this starts to talk about how you when you're working with Excel,
0:49 you intuitively know you can't call year on a calm that doesn't have a daytime value
0:53 So we'll use that concept when we start to work on our hands data frame
1:00 and then the final thing I want to do an example of is what if
1:04 you wanted to understand what quarter you were in now,
1:06 I had to look this up on the Internet.
1:08 But if I wanted to know that this first March 5th was in quarter one,
1:14 here's a formula I would have to use.
1:16 I have to use round up and then put in the date and then divided by
1:22 three been around 20 and the reason I show that form was it highlights how some
1:31 of the things that you can do in excel with a formula are a little complicated
1:35 and you typically have to do some Google searching.
1:38 But in pandas, there are some easier options,
1:41 which we will explore in a second.