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Udemy - Writing production-ready ETL pipelines in Python Pandas 2022-4

Udemy - Writing production-ready ETL pipelines in Python Pandas 2022-4
Total Titles: 151
 
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02_007 Quick and Dirty_ Argument Date
02_007 Quick and Dirty_ Argument Date
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21.12.15
02_008 accessing_the_xetra_data.ipynb
02_008 accessing_the_xetra_data.ipynb
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21.12.15
02_008 Quick and Dirty_ Save to S3
02_008 Quick and Dirty_ Save to S3
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21.12.15
02_009 Quick and Dirty_ Code Improvements
02_009 Quick and Dirty_ Code Improvements
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21.12.15
02_010 quick and dirty transformations.ipynb
02_010 quick and dirty transformations.ipynb
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21.12.15
02_011 Quick and dirty solution - argument date.ipynb
02_011 Quick and dirty solution - argument date.ipynb
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21.12.15
02_012 quick and dirty solution - save to s3.ipynb
02_012 quick and dirty solution - save to s3.ipynb
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21.12.15
02_013 quick and dirty - improvements.ipynb
02_0013 quick and dirty - improvements.ipynb
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21.12.15
03_001 Why a code design is needed_
03_001 Why a code design is needed_
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21.12.15
03_002 Functional vs. Object Oriented Programming
03_002 Functional vs. Object Oriented Programming
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21.12.15
03_003 Why Software Testing_
03_003 Why Software Testing_
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21.12.15
03_004 Quick and Dirty to Functions_ Architecture Design
03_004 Quick and Dirty to Functions_ Architecture Design
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21.12.15
03_005 Quick and Dirty to Functions_ Restructure Part 1
03_005 Quick and Dirty to Functions_ Restructure Part 1
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21.12.15
03_006 Quick and Dirty to Functions_ Restructure Part 2
03_006 Quick and Dirty to Functions_ Restructure Part 2
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21.12.15
03_007 Restructure get_objects Intro
03_007 Restructure get_objects Intro
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21.12.15
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