Read Giant Datasets Fast - 3 Tips For Better Data Science Skills
We've learned how to work with data. But how about massive amounts of data? as in - files with millions of rows, tens of gigabytes in size, and ages of staring at your computer waiting for everything to load?
Luckily, in this tutorial, I will show you how to work with a gigantic dataset of Amazon Best Seller Products that has over 2 million rows, and takes up 11GB in size 😱😱😱
A huge shoutout to Bright Data for supplying it and helping this video come to life!
⭐ you can get a free sample of this dataset here:
https://get.brightdata.com/pythonsimp...
Additionally, I will demonstrate that slight improvements to your code make a huge impact on the processing speed - regardless of how strong and powerful your computer is!!
For this, we will compare the performance across 2 different systems:
🖥️ my custom build new-gen PC
💻 my poor old laptop (yes, the one that is held by scotch tape and is barely operational 😅)
You will see that well-written code can even make my old laptop run like a supercomputer! 💪💪💪 #python #datasets #brightdata #data #ecommerce #datascience #pandas #pythonprogramming
📽️ RELATED TUTORIALS 📽️
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• Anaconda Beginners Guide for Linux an...
⭐ Pandas Guide For Beginners:
• Basic Guide to Pandas! Tricks, Shortc...
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• Python For Loops - Programming for Be...
⏰ TIME STAMPS ⏰
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00:00 - intro
01:05 - intro to working with professional data platforms
03:38 - complexity of loading very large datasets
06:43 - focus on relevant data ⭐
09:09 - load data in small chunks ⭐
10:25 - access and change data chunks values
12:19 - save modified data into a new csv file ⭐
14:49 - Thanks for watching! 😀
🤝 Connect with me 🤝
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🔗 Github:
https://github.com/mariyasha
🔗 Discord:
/ discord
🔗 LinkedIn:
/ mariyasha888
🔗 Twitter:
/ mariyasha888
🔗 Blog:
https://www.pythonsimplified.org
💳 Credits 💳
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⭐ Beautiful titles, transitions, sound FX, and music:
mixkit.co
⭐ Beautiful icons:
flaticon.com
⭐ Beautiful graphics:
freepik.com
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