Learn Python NumPy Library with Simple Example

NumPy stands for Numerical Python; it emerged in the early 2000s as an open-source project initiated by Travis Olliphant. NumPy was designed to provide a powerful array object and a suite of functions for performing mathematical operations on these arrays. Its creation marked a significant leap forward in Python’s capabilities for scientific computing.

Here, we learn Numpy from the very beginning to advanced. So let’s start with a very first step. To work more efficiently with NumPy, we need to install Jupyter Notebook. VSCode is also fine, but Jupyter Notebook is even better.

Install Jupyter Notebook

To install Jupyter, you can use the following command in your terminal or command prompt:

pip install jupyter

Once installed, launch Jupyter by typing jupyter notebook in your terminal. This will open a new tab in your web browser, allowing you to create and run notebooks with Python code.

Now, let’s start learning NumPy. Here is a link to all the basic to advanced topics, organized into a 7-day plan to help you effortlessly master the NumPy library:

Day-1 (Introduction)

👉 Introduction to NumPy in Python with Simple Example

Day-2 (Special NumPy Arrays)

👉 Special NumPy Array with Example

Day-3 (NumPy Array with Random Value)

👉 Create a NumPy Array with Random Values

Day-4 (Data Types)

👉 Data Types in NumPy with Simple Example

Day-5 (Shape & Reshape)

👉 Shape and Reshape in NumPy Array