Best resources to learn Numpy and Pandas in python

In this tutorial, we will discuss the different resources where we can learn about NumPy and Pandas libraries of Python in a more efficient way.

NumPy

NumPy, a Python library used for scientific computing and numerical computation, is one everyone should learn. Large, multidimensional arrays and matrices are supported by NumPy, along with a wide range of sophisticated mathematical operations that can be performed on these arrays. It takes less memory to store the data than Python, which is used in various domains of computer programming.

The top free online resources to learn NumPy are listed in this article,

1. NumPy Official Document
   
   The thorough document provided by NumPy explains this library's purpose and operation. The official guide will assist you in starting from scratch to learn NumPy. NumPy fundamentals, NumPy for programmers, nuts and bolts for developers, and other subjects are covered.
   
2. Complete NumPy course with applications
   
   This course is a simple Udemy course for students who want a quick overview of the NumPy library. You can join this course if you're interested in learning about AI (Artificial intelligence) or data science; you only need the basics of Python programming language.
   
3. Linear Regression with NumPy and Python
   
   This course is ideal for you if you're searching for a hands-on experience where you can use NumPy side by side. This Coursera-guided project will teach you linear regression using NumPy and Python. To gain a deeper grasp of the foundations and explore the machinery of various learning algorithms.
   
4. NumPy Tutorial
   
   This GitHub lesson is the greatest choice for people who are just starting with NumPy and Data Science and don't want to spend any money on learning. By completing this tutorial, you will understand NumPy's ideas and discover how Python programming can be used for any data science tasks. Justin Johnson, a skilled data scientist with a strong background in Python programming and NumPy, is the lesson author of the lesson. He will offer you more assistance to aid you with the course questions. After completing this session, you can continue to more advanced NumPy and Data Science courses.
   
5. Python NumPy: Machine Learning & Data Science Course
   
   In this Udemy course, we will learn how to use the NumPy library efficiently, learn the fundamentals of Python, arrays in NumPy, and NumPy features.  The fact that NumPy arrays are speed-optimized is their most crucial feature. Basics of the NumPy library, a little more on installing Anaconda, and instructions for using the Jupyter notebook.

Pandas

Pandas, one of the most well-known Python packages, offers data structures that are quick, adaptable, and expressive. The library contains several user-friendly features, such as simple handling of missing data, sophisticated indexing, and data alignment, to mention a few.

The top free online resources to learn Pandas are listed in this tutorial,

1. Pandas with Python
   This Udemy course, which teaches you how to group and join data as well as process very complex data and more, is recommended for those who have at least a basic understanding of the Python programming language and want to delve further into the panda's library and learn some of its advanced features.
   
   Data frame and series are the two most fundamental operations in Pandas, along with when to apply them in your project. Then discover date ranges, data inspection, and data frame slicing.
   
   Additionally, you will learn about importing data from various file types, working with text data, concatenation & descriptive statistics, merging data frames, and data visualisation.
   
2. Writing Efficient Code with Pandas
   Understanding Python and the Pandas library will be aided by taking this course, which will also introduce the useful built-in Pandas functions. By the end of the course, one will be able to quickly loop through large datasets, apply methods, and work with data from various groups. In addition, students can use these techniques on various real-world datasets, including poker hands and tip data.
   
3. Data Analysis with Pandas and Python
   We will rapidly analyse data in this Udemy course with Python's robust Pandas module. Use Python's well-known Pandas module to perform a wide range of data operations, such as grouping, pivoting, joining, and more!
   
   Learn about Pandas objects' hundreds of methods and properties.
   
   Know how to manipulate 1D, 2D, and 3D data sets very well. Fix typical problems with incomplete or damaged data sets.
   
4. Introduction to Data Science in Python
   In this Coursera course, we will learn the fundamentals of the Python programming environment, including core python programming techniques, and the NumPy library will be covered in this course. The popular Python Pandas data science library will be used to teach students how to manipulate and clean data, explain the abstraction of Series and data frames as the key data structures for data analysis, and provide tutorials on how to use tools like group-by, merge efficiently use tools like group-by, merge, and pivot tables.
   
5. Data Analysis with Pandas
   An additional great interactive course to study data analysis using Pandas online is the one by CodeCademy. This course teaches you how to use Python's sophisticated Pandas library for data analysis and additional Python modules like Scipy (for statistical research) and Matplotlib to ingest, clean, and have enormous amounts of data.
   Along with interactive exercises, quizzes, and assessments, this course also covers creating Pandas DataFrames, calculating aggregates, and merging to create Pandas DataFrames, calculate aggregates, and merge several tables.