Lecture 26: Introduction to Numpy (Part 2) (Hindi)

🔢 Dive into NumPy's Advanced Functions and Array Operations! 🔍

Welcome to another exciting exploration of NumPy - the powerhouse of numerical computing in Python! 🚀

In this video, we're delving deep into advanced NumPy functions and array operations that will take your data manipulation skills to the next level:

1. Exploring the Extremes:

Unleash the power of argmax() and argmin() functions to find the indices of the maximum and minimum values in arrays.
Use argsort() to get the indices that would sort the array.
2. Multi-dimensional Marvels:

Step into the world of multi-dimensional arrays and discover their shape and size.
Master argmax() and argmin() with specified axes for multi-dimensional arrays.
Get creative with argsort() for various dimensions.
3. Joining Arrays:

Learn how to stack arrays vertically and horizontally using vstack() and hstack().
Get precise with column_stack() for combining arrays column-wise.
4. Finding Common Ground:

Explore intersect1d() for identifying common elements between arrays.
Harness setdiff1d() to find the elements unique to each array.
5. Mathematical Marvels:

Perform array-wise addition, multiplication, and summation with ease.
Take control of arithmetic operations with scalar values for NumPy arrays.
6. Math Functions Galore:

Calculate mean, median, standard deviation, and more with NumPy's mathematical functions.
Discover how to locate values meeting specific criteria with where().
Count non-zero elements and find their positions with count_nonzero() and nonzero().
And don't forget the mysterious s=t() (probably meant to be sort())!
Are you ready to elevate your data analysis, scientific computing, and machine learning projects? NumPy is your trusty companion. Join us on this NumPy adventure, and unlock the full potential of your Python programming skills! 🌟🔢