Move from Excel to Python with Pandas Transcripts
Chapter: Course conclusion and review
Lecture: Data wrangling

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0:00 in the next chapter, we went into more detail on pandas specifically around data wrangling
0:05 And one of the important concepts is to make sure that you have the correct
0:09 data types for your pandas. Data frame handles Data types are very similar to sell
0:14 formatting in Excel, you can use the Info Command to see all of your data types, and for the most part,
0:19 pandas will determine a data type correctly when reading in files. But sometimes it doesn't. So.
0:25 It's important to do a quick check and understand your data types and make sure that
0:30 it supports the A types of analysis that you want to use in future analysis or
0:35 transformation steps. We also discuss that there are some additional advanced options,
0:40 such as the category, Boolean and string that we didn't go into detail in this course, but you will encounter as you continue on your pandas journey.
0:48 Once the data is in the proper type, you can start to filter it for doing additional analysis or data scrubbing or cleaning.
0:56 And the concept that we talked about was the Excel Auto Filter, which is very familiar to all Excel users and is a good analogy for bullying,
1:05 indexing, bullying indexing allows us to create a list of true false values that represent
1:11 different rows in our data frame and then apply them to that data frame in a
1:16 very flexible style so that we can filter our data down to a smaller subset that
1:21 we care about for future analysis or cleaning or data wrangling efforts.

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