Move from Excel to Python with Pandas Transcripts
Chapter: Course conclusion and review
Lecture: Practical example
0:00 in the final section of this course,
0:02 we went through a real life example to bring many of the concepts together.
0:06 We worked with multiple different file types and brought them together to build a very nice
0:12 summary report that answered an important business question.
0:16 Along the way, we highlighted some of the benefits to this approach versus Excel.
0:20 So when you are done with this analysis,
0:23 you have a Jupiter notebook. It has documented steps that you can use for future
0:27 analysis. It's easy to rerun and model the analysis.
0:31 So in our examples, as we changed our commissions rates,
0:35 all we had to do was change a small amount of code and rerun and evaluate
0:39 the output. The examples we walked through were relatively small Excel files,
0:44 but there's no reason the code that we developed couldn't run on much larger data sets
0:50 that would be very impractical to run in an Excel file.
0:54 Finally, we've just touched the tip of the iceberg for all the capabilities that you
0:59 have in the python ecosystem. We could take this analysis that we've done and build
1:05 on it and build more complex visualizations machine learning algorithms,
1:10 orm or complex analysis to answer critical business problems.