NumPy - Numerial Python | Belayet Hossain

Numpy:

NumPy?is?the?fundamental?package?for?scientific?computing?in?Python.?It?is?a?Python?library?that?provides?a?multidimensional?array?object,?various?derived?objects?(such?as?masked?arrays?and?matrices), and?an?assortment?of?routines?for?fast?operations?on?arrays,?including?mathematical,?logical,?shape?manipulation,?sorting,?selecting,?I/O,?discrete?Fourier?transforms,?basic?linear?algebra,?basic?statistical?operations,?random?simulation?and?much?more.

At?the?core?of?the?NumPy?package, is?the?ndarray?object.?This?encapsulates?'n' dimensional?arrays?of?homogeneous?data?types

Topics:

1.?Creating?Numpy?Arrays

2.?Array?Attributes

3.?Changing?Datatype

4.?Array?Operations

5.?Array?Functions

6.?Indexing & Slicing

7.?Iterating

8.?Reshaping

9.?Stacking

10?Splitting

Python Before & after NumPy:

prior to the creation of Numpy, working with numerical data in Python was a challenge. working with large datasets or complex calculations was often slow and cumbersome.

After the creation of Numpy, Python became a more powerful language for numerical computing and data analysis. Numpy introduced a powerful set of tools for handling large arrays and matrices of numeric data. These tools were optimized for numerical computing, making it much faster and more efficient to work with large datasets and perform complex calculations.

NumPy Mathematical Functions- https://numpy.org/doc/stable/referenc...

NumPy Universal Functions- https://numpy.org/doc/stable/referenc...

#Batch02 #datanerd