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In this article, I am going to talk about Numpy, Python’s one of the most important libraries.

### What is Numpy

**It can be imported in a simple way as follows :**

```
import numpy as np
# np label can be used to access the numpy library.
```

### Why Use Numpy

So why do we use Numpy when we have the list data structure in Python?Â **Here are the reasons : **

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**Numpy is faster than list :Â**

Numpy stores its data in a continuous location in memory, unlike Python list data structures. Therefore Numpy can access its data much more easily and efficiently.

**Â NumPy uses much less memory to store data :Â**

Numpy arrays take up less memory space than Python list data structures.Â

**Â Convenient to useÂ Â**

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**Lots of Built-in FunctionsÂ**

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If you are interested in machine learning or data science, Numpy is a Python library you will use frequently.

So how do you learn Numpy? As with everything else in life, the best way to learn something is to learn **by doing it**. Below I have listed the best courses and books for you to learn Numpy. These courses and books will enable you to learn Numpy as efficiently as possible.

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### Numpy Courses

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Codeacademy is one of the best platforms among e-learning platforms. The course I recommend here is **Codeacademy – Learn Statistics with Numpy**.

**Course Description**

**Why Learn NumPy?**

### Â

**Take-Away Skills:**

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Datacamp is an e-learning platform that offers high-quality courses in the field of data science. The course I recommend here is the **Datacamp Introduction to Python course**. This course starts by teaching the programming language Python and then continues with Numpy.

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**Course DescriptionÂ**

### Udemy - Python Numpy for Absolute Beginners

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**In this course, you are going to learn :Â**

- Learn How To Use Python Interactively And By Using a Script
- Use Python for Data Science and Machine Learning
- Create Your First Numpy array and Acquaint Yourself With Python Numpy
- Learn to work with powerful tools in the NumPy array, and get started with data exploration.

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**Course DescriptionÂ**

### Best Numpy Books

**Official DescriptionÂ **

- IPython and Jupyter:Â provide computational environments for data scientists using Python
- NumPy:Â includes theÂ ndarrayÂ for efficient storage and manipulation of dense data arrays in Python
- Pandas:Â features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
- Matplotlib:Â includes capabilities for a flexible range of data visualizations in Python
- Scikit-Learn:Â for efficient and clean Python implementations of the most important and established machine learning algorithms

**Official DescriptionÂ**

- Use the IPython shell and Jupyter notebook for exploratory computing
- Learn basic and advanced features in NumPy (Numerical Python)
- Get started with data analysis tools in the pandas library
- Use flexible tools to load, clean, transform, merge, and reshape data
- Create informative visualizations with matplotlib
- Apply the pandas groupby facility to slice, dice, and summarize datasets
- Analyze and manipulate regular and irregular time series data
- Learn how to solve real-world data analysis problems with thorough, detailed examples.

**Official DescriptionÂ**

- Work with vectors and matrices using NumPy
- Plot and visualize data with Matplotlib
- Perform data analysis tasks with Pandas and SciPy
- Review statistical modeling and machine learning with statsmodels and scikit-learn
- Optimize Python code using Numba and Cython