NumPy is a library for performing computations on multi-dimensional arrays. It stands for Numerical Python.
It was released in 2006. It has multiple routines to execute various operations on arrays.
Apart from its scientific use, it is also used as an efficient multi-dimensional container for generic data.
Now, let’s get started with our roadmap.
Prerequisites: It is advised to have some basic knowledge of python before learning NumPy.
Step1:
Set its environment on your PC. Learn about ndarray objects.
Step2:
Learn data types, array attribution, array creation routines, array from existing data, and array from numerical ranges.
Step3:
Move on to some more interesting concepts. Learn about indexing, slicing, advanced indexing, and broadcasting.
Step4:
We are halfway done with it now. Understand the concept of iterating over an array, array manipulation, binary operators, and arithmetic operators.
Step5:
Learn string functions, mathematical functions, statistical functions, sort, search, and counting functions. Understand the concept of byte-swapping, copies, and views.
Step6:
Learn about matrix library and Matplotlib. Understand the concept of linear algebra and I / O with NumPy.
Step7:
We are done with NumPy. Keep performing some operations with it on regular basis to get better at it.
