NumPy - Numerical Python
NumPy (stands for Numerical Python ) is a fast and versatile library for the Python programming language, adding support for large, N-dimensional arrays and matrices, along with a large collection of comprehensive mathematical functions to operate on these multidimensional arrays . NumPy was created in 2005 by Travis Oliphant. It is one of the fundamental package for scientific computing in Python. NumPy arrays are stored at one continuous place in memory unlike Python lists (which can grow dynamically ), so processes can access and manipulate them very fast and efficiently.
How To Install NumPy
- Python installed on your system
The easiest way to install NumPy is by using Pip Installs Packages (Pip). If you don't have Pip installed on your system, you need to set up the package manager that corresponds to the version of Python you have.
With Pip set up, you can use its command line for installing NumPy .
Importing the NumPy module
If you have large amounts of calls to NumPy functions , it can become tedious to write numpy.x() over and over again. Instead, it is common to import under the briefer name np.
Create a NumPy array
Creating a 1-D NumPy array with continuous 9 values.
Check the type of NumPy array
Create a 2-D NumPy array
Creating a 2-D NumPy array with 2 rows and 4 columns.
Create a 3-D NumPy array
Creating a 3-D NumPy array with 2 rows, 3 columns and 4 depth.
NumPy Array Shape
The shape property of a NumPy array returns a tuple with the size of each array dimension.
1-D NumPy Array shape
Here npArr is a 1-D NumPy array so the shape of the array is (9,), this means that the array has continuous 9 values only.
2-D NumPy Array shape
Here npArr is a 2-D NumPy array so the shape of the array is (2, 4), this means that the array has 2 rows and 4 columns dimensions.
3-D NumPy Array shape
Here npArr is a 3-D NumPy array so the shape of the array is (2, 3, 4), this means that the array has 2 rows, 3 columns and 4 depth dimensions.