# @aartii.py on Instagram

- **Type:** Video
- **Original URL:** https://www.instagram.com/p/DXegPogj0sz
- **Gondola URL:** https://gondola.cc/posts/64657434-aartiipy-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/14a4af3bce.jpg
- **Posted:** 2026-04-23T13:58:31.000+00:00
- **Account Owner:** Aarti Sinha (@aartii.py) — https://gondola.cc/aartii.py

## Caption

I added 1 million numbers. Python list: 0.21 seconds. NumPy array: 0.001 seconds. Same result. 200× faster.  NumPy replaces Python lists when you’re working with numerical data.  Instead of this: [x * 2 for x in my_list] ← loop needed  You write this: arr * 2 ← no loop, instant  That’s called vectorisation — NumPy operates on the entire array at once.  This is why Pandas, scikit-learn, and TensorFlow are all built on NumPy underneath. When you’re working with millions of rows, this speed difference decides whether your model trains in 1 second or 3 minutes.  Day 12 · Libraries series starts now. Did you know NumPy was this much faster?
#NumPy
#Python
#DataScience
#LearnPython
#MachineLearning
PythonLibraries
aartii_py
DataScienceIndia

## Stats

- **Views:** 521
- **Likes:** 0
- **Shares:** 0
- **Comments:** 14

## Tags

numpy, machinelearning, python, learnpython, datascience

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