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numfocus / YouTubeVideoTimestamps

Adding timestamps to NumFOCUS and PyData YouTube videos!
https://www.youtube.com/c/PyDataTV
MIT License
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So You Wanna Be a Pandas Expert? (Tutorial) - James Powell | PyData Global 2021 #70

Open torres-federico-e opened 2 years ago

torres-federico-e commented 2 years ago

So You Wanna Be a Pandas Expert? (Tutorial) - James Powell | PyData Global 2021

Claim on Pandas Expertise video, by James Powell

Will be uploading Timestamps on few moments

Timestamps (Not finished):

1:50 - Why Pandas? Introduction - Pandas vs. Python Builtins 17:14 - Pandas - Why so much complexity? 18:41 - Numpy - Introduction 26:44 - Numpy Conclusions 27:15 - Xarray - Introduction 31:44 - Xarray - Conclusions 31:59 - Pandas - Series & Arrays 32:50 - Pandas - Index introduction 33:56 - Pandas - Conclusions and Problems 34:47 - Series - Accessor ambiguity & Methods 36:19 Why this Pandas ambiguity? 39:10 Possible Errors & Indexes Types 40:25 Index is a Mechanism - Demo 41:46 Index translates: Human to Physical Memory 45:11 Demo: Index Mechanics on Arithmetics 47:07 Indexes are Operative metadata 50:04 Back to Numpy - Rule comparisson

Alt-Shivam commented 2 years ago

Hey @torres-federico-e Can you help me out to understand this repo I mean there are lots of issues open but still, no PRs to resolve them I am just kind of confused. Thanks.

torres-federico-e commented 2 years ago

Of course. The PyData YouTube Channel has opened for collaboration all the Time Stamping efforts for indexing videos of their conferences

You basically claim a video from their YouTube channel that you want to watch, make the timestamps, and create an issue on this repo and collaborate.

They will add them to YouTube, make a PR, and credit for your help to the community afterwards.

Check the instructions here if you want to join!

Alt-Shivam commented 2 years ago

Got it. Thanks a lot for the help @torres-federico-e

s-m-amin-ghasemi commented 2 years ago

1:50 - Why Pandas? Introduction - Pandas vs. Python Builtins 2:26 - Loop+Sets Vs Pandas 3:45 - List and Dictionary Introduction 4:26 - Pandas Intersection of two Collections 6:13 - List Intersection of two Collections 6:48 - Dict Intersection of two Collections 7:41 - Counter Intersection of two Collections 8:28 - Pandas "+" Operation 10:22 - Pandas groupby 11:29 - Redefining variable in python will result as append pandas Dataframe 12:50 - Pandas "+" Operation and reset_index() key 13:07 - Pandas transform, apply, agg key 17:14 - Pandas - Why so much complexity? 18:41 - Numpy - Introduction 26:44 - Numpy Conclusions 27:15 - Xarray - Introduction 31:44 - Xarray - Conclusions 31:59 - Pandas - Series & Arrays 32:50 - Pandas - Index introduction 33:56 - Pandas - Conclusions and Problems 34:47 - Series - Accessor ambiguity & Methods 36:19 Why this Pandas ambiguity? 39:10 Possible Errors & Indexes Types 40:25 Index is a Mechanism - Demo 41:46 Index translates: Human to Physical Memory 45:11 Demo: Index Mechanics on Arithmetics 47:07 Indexes are Operative metadata 50:04 Back to Numpy - Rule comparisson