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, I'm gonna walk through a couple excel examples of how we can manipulate a daytime data
0:08 and then show how we would do that and pandas. So I've opened up my sample sales details file, and there's a column See, that has the purchase date.
0:16 So what if during our analysis, we wanted to get the month associated with that purchase state,
0:21 we would enter a formula that looks something like this and copy that down to eat row. We could do a similar thing for the day.
0:29 We want to do that for the year, relatively straightforward. And just for the sake of talking about data types,
0:37 what would happen if we tried to do the same formula? But maybe did I'll call him be, too, which is not a year we get evaluator.
0:46 So this starts to talk about how you when you're working with Excel,
0:50 you intuitively know you can't call year on a calm that doesn't have a daytime value
0:54 So we'll use that concept when we start to work on our hands data frame and then the final thing I want to do an example of is what if
1:05 you wanted to understand what quarter you were in now, I had to look this up on the Internet.
1:09 But if I wanted to know that this first March 5th was in quarter one, here's a formula I would have to use.
1:17 I have to use round up and then put in the date and then divided by three been around 20 and the reason I show that form was it highlights how some
1:32 of the things that you can do in excel with a formula are a little complicated and you typically have to do some Google searching.
1:39 But in pandas, there are some easier options, which we will explore in a second.

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