# Numpy:The ultimate course on python numpy for data analytics

Numpy for data analytics, python numpy

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 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

• Introduction to numpy –> 5 lectures • 40min.
• NumPy Array Creation –> 3 lectures • 44min.
• Accessing numpy array –> 4 lectures • 1hr 5min.
• Operations on numpy array –> 7 lectures • 1hr.
• Advanced operations on numpy array –> 6 lectures • 50min. Requirements

• Python programming.

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

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

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