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Luckily, in this tutorial I'll show you how to work with a massive dataset of Amazon Best Seller products that contains over 2 million rows and takes up 11 GB
A huge shoutout to Bright Data for providing it and helping bring this video to life!
you can get a free sample of this dataset here:
https://get.brightdata.com/pythonsimplified
Plus, I'll demonstrate that small improvements to your code have a huge impact on processing speed – no matter how strong and powerful your computer is!!
To do this, we compare the performance of two different systems:
️ my custom-made new generation PC
my poor old laptop (yes, the one held down with tape and barely operational)
You'll see that well-written code can even make my old laptop work like a supercomputer! #python #datasets #brightdata #data #ecommerce #datascience #pandas #pythonprogramming
️ RELATED TUTORIALS ️
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Anaconda Guide for Beginners (Install Jupyter Notebook):
https://youtu.be/MUZtVEDKXsk
Panda guide for beginners:
https://youtu.be/zN2Hua6oII0
For beginner loop:
https://youtu.be/dHANJ4l6fwA
TIME STAMPS
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00:00 – introduction
01:05 – introduction to working with professional data platforms
03:38 – complexity of loading very large data sets
06:43 – focus on relevant data
09:09 – loading data in small chunks
10:25 – access and change data fragment values
12:19 – save changed data to a new csv file
2:49 PM – Thanks for watching!
Connect with me
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Github:
https://github.com/mariyasha
Disagreement:
https://discord.com/invite/wgTTmsWmXA
LinkedIn:
https://ca.linkedin.com/in/mariyasha888
Twitter:
https://twitter.com/mariyasha888
Blog:
https://www.pythonsimplified.org
Credits
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Beautiful titles, transitions, sound effects and music:
mixkit.co
Beautiful icons:
flaticon.com
Beautiful graphics:
freepik.com
Please take the opportunity to connect and share this video with your friends and family if you find it helpful.