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Top 10 numpy course for data analytics Best top numpy course
2 students

Top 10 numpy course for data analytics Best top numpy course

Best top course on python numpy top 10 python numpy course Python numpy for data analytics Python numpy for data science
Created byDr Karveer B Manwade
Last updated 10/2022
English

What you'll learn

  • Python numpy: The numerical array to store data
  • Attributes of numpy and their usage
  • Creation of array by using different routines
  • Usage of numpy
  • Use of numpy with matplotlib

Course content

5 sections • 25 lectures • 4h 17m total length

  • Introduction3:13
  • How to install numpy1:26
  • NumPy - Ndarray Object10:43

    Explore the NumPy ndarray object, its dtype-based elements, and how to create multi-dimensional arrays with shape and memory order (row-major or column-major).

  • NumPy - Data Types13:42
  • NumPy - Array Attributes10:27

Requirements

  • Python programming

Description

The data analytics needs specialized data structure for storing numerical data. The numpy library provides the required data stucture. NumPy is a Python package. It stands for 'Numerical Python'. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. In this course python numpy library is explained in details. In this tutorial you will learn,

  • What is numpy?

  • How to create and use numpy array?

  • Accessing elements of array.

  • Operations on numpy array.

  • Functions of numpy array.

Anybody knowing basic knowledge of python programming can take up this course. In this course each and every concept is explained in detail. Also following resources are provided to students,

  1. Notes

  2. Examples

The contents of this course are,

1. What is numpy

2. How to install numpy

3. NumPy - Ndarray Object

4. NumPy - Data Types

5. NumPy - Array Attributes

6. NumPy - Array Creation Routines

7. NumPy - Array From Existing Data

8. NumPy - Array From Numerical Ranges

9. NumPy - Indexing & Slicing

10. NumPy - Advanced Indexing

11. NumPy - Broadcasting

12. NumPy - Iterating Over Array

13. NumPy - Array Manipulation

14. NumPy - Binary Operators

15. NumPy - String Functions

16. NumPy - Mathematical Functions

17. NumPy - Arithmetic Operations

18. NumPy - Statistical Functions

19. NumPy - Sort, Search & Counting Functions

20. NumPy - Byte Swapping

21. NumPy - Copies & Views

22. NumPy - Matrix Library

23. NumPy - Linear Algebra

24. NumPy - Matplotlib

25. NumPy - Histogram Using Matplotlib

26. I/O with NumPy

Who this course is for:

  • Under graduate, post graduate students, working professional, aspiring data analyst/scientist

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