Python Pandas: Taking advantage of shift() method in Pandas to process rows and columns

Are you really interested in learning how to can process your pandas dataframe rows and columns using shift() method? If yes, you are in the right place...

In this tutorial, you will learn the following:

- (00:00) Content Start
- (00:06) Content Intro
- (4:00) Using shift() function to shift rows upward and downward
- (10:30) Using shift() function to shift columns towards left and right
- Update values in the new created rows and columns with shift() function
- (13:40) Using shift() method with timeseries dataset to update datetime based index
- (19:00) Creating rolling update using shift method()
- (21:50) Combine shift with transpose and groupby to generate rolling value based on rows
- (27:06) Content Reacp

GitHub URL:

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Tags:
#webdevelopment, #frontend #react, #chakraui, #layout, #fullstackdevelopment #pandas #dataanalysis #python #bigdata #machinelearning #artificialintelligence #ai #ml #dataanalysis

[seiken]

Thank you so much for the tutorial, it helped me a lot.

[AILab]

Video TimeLine:


- (00:00) Content Start
- (00:06) Content Intro
- (4:00) Using shift() function to shift rows upward and downward
- (10:30) Using shift() function to shift columns towards left and right
- Update values in the new created rows and columns with shift() function
- (13:40) Using shift() method with timeseries dataset to update datetime based index
- (19:00) Creating rolling update using shift method()
- (21:50) Combine shift with transpose and groupby to generate rolling value based on rows
- (27:06) Content Reacp

[vampire-cgxi]

I have vertical data in csv file, i need to make it horizontal. I tried using transpose but it is getting concatenated in the first row. As a result headers are repeated. How should I process this in order to have unique headers and corresponding values.