NumPy is a python library used for working with arrays. I hope to teach you the fundamentals of NumPy: Creating an Array, Accessing Elements, Array Slicing, Array Iterating, Array Joins, Split Array, Sorting Arrays, Random Numbers, ...

NumPy is a python library used for working with arrays. It also has functions for working in the domain of linear algebra, Fourier transform, and matrices. In this article, I hope to teach you the fundamentals of NumPy.

If you want to learn about Python first, you can check out my beginners guide.

It would help if you had Python installed and PIP. If you have already done this, you can start working with NumPy. Before you can use NumPy, we have to install with the following command line:

`C:\Users\Your Name>pip install numpy`

Then open up a python script or file and import the library:

`import numpy`

Now, NumPy is imported and ready for you to use. NumPy usually is imported as np instead of NumPy:

`import numpy as np`

We can check if NumPy works by adding two simple lines of code:

`arr = np.array([1, 2, 3, 4, 5])print(arr)#output: [1 2 3 4 5]`

NumPy was developed to work with arrays, so let’s create one with NumPy. An important thing to know is that NumPy uses the ‘ndarray’ object to create an array. You can create one as follows:

`import numpy as np #import the libraryarr = np.array([1, 2, 3, 4, 5]) #initializing an ndarrayprint(arr) #print the arrayprint(type(arr)) #output: <class 'numpy.ndarray'>`

In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.

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