What Is NumPy In Python?

Table of Contents (TOC):

• What Is NumPy?
• Key Features Of NumPy
• How To Learn NumPy?
  • Basics of NumPy
  • Mastering NumPy and Pandas
• Conclusion
• Bonus Points

If you are new to learning Python, questions like ‘What is NumPy in Python?’, ‘What does it do?’ and ‘How do you use it?’ must be on your mind. This article will help you understand these concepts and make learning Python easier for you.

What Is NumPy In Python?

NumPy, also known as Numerical Python, is a Python library specifically designed for numerical computation. It is essential for working with large datasets and multi-dimensional objects with various mathematical functions. So if your work requires heavy computation, learning Python NumPy is very important.

Key Features Of NumPy

1. Powerful N-dimensional Array Object

NumPy Arrays are lists in which numerical data can be structured and optimized. In comparison to regular Python Arrays, NumPy Arrays support N-dimensional Array objects, making the entire process more efficient.

2. Broadcasting

NumPy in Python also simplifies operations by allowing computations between different arrays. It aligns various arrays based on their dimensions automatically, avoiding creating new data.

3. Comprehensive Mathematical Functions

When you import NumPy in Python, you get access to a vast library of mathematical functions. This includes trigonometric functions, exponential functions, basic arithmetic operations, and more.

4. Linear Algebra Capabilities

It also contains routines for linear algebra operations like matrix multiplication, decompositions, calculating determinants, and more.

5. Random Number Generation

If your work requires you to generate random numbers for probability distributions, Python NumPy can help you with it. It includes a module dedicated to generating random numbers that can be crucial for simulations, statistical modelling, machine learning tasks, and more.

6. Fourier Transform Routines

For those working in Engineering fields, the NumPy library in Python can help you perform FFTs for signal processing and image analysis.

7. Tools for Integration with Other Languages

If you are interested in learning about Python libraries, NumPy can be a great starting point. A fundamental understanding of Numpy will make learning scientific libraries like SciPy and Pandas easier.

8. Ease of Use and Expressiveness

Seeing as NumPy is specifically designed for Numerical Python functions, it is easier to use when working with numerical code in comparison to Python.

Also Read: Exploratory Data Analysis with Pandas, NumPy, Matplotlib & Seaborn

How To Learn NumPy?

Learning Python and NumPy does not have to be complicated. UniAthena’s Basics of Python free short course will help you get started with Python programming and learn the fundamentals in just 4-6 hours.

This course is a great starting point for anyone new to this programming language. You will get the chance to learn about the various variables, data structures, strings, and functions of Python. This will create a strong foundation on which you can build your knowledge.

1. Basics of NumPy

You can learn about the NumPy library in Python with our Basics of NumPy free short course. You will just need to sign in or log in to access the course. It is a perfectly beginner-friendly course that will teach you the fundamentals of NumPy.

Here are some of the topics you will learn from this course:

• NumPy 1-D Arrays
• Multidimensional Arrays
• Mathematical Operations
• Computation Times in NumPy vs Python Lists

You will also have 4 lab sessions that will give you hands-on experience in using NumPy in Python programming. This free course also offers you a free certification from CIQ, UK.

2. Mastering NumPy and Pandas

If you want to go beyond the basic understanding of NumPy, you can also explore our Mastering Data Pre-Processing Using Numpy & Pandas free short course. It will give you essential knowledge of data pre-processing and also introduce you to working with other libraries such as Pandas.

This course covers the following topics:

• Data Pre-Processing Using NumPy
• Exploring NumPy Arrays & Mathematical Operations
• Understanding Pandas and Indexing & Slicing
• Operations on Data Frames & Pivot Tables

Conclusion

NumPy is a computing library for Python programming. Sometimes, just learning the Python programming language might not be enough; if you work with numericals, NumPy might make your work much more efficient. 

Learn NumPy for free with UniAthena!

Bonus Points:

• NumPy is great for numerical computation, while Pandas is great for data analysis.
• For larger data where you are working with 500K+ rows, Pandas might be the right library for you.
• If you are learning Python and NumPy, you will also benefit from learning Pandas.