Quick Introduction to Numpy Library

Overview:

Numpy is a popular library in Python, which is used in Machine Learning and Statistical analysis. This article provides some of the commonly used operations in Numpy. Numpy array operations are efficient and fast compared to normal array operations.


Jupyter Notebook:

The code is run using Jupyter Notebook and the relevant snapshots are provided.

Note: Numpy could be imported as below:

import numpy as np

Array Operations:

Basic Operations:

Array could be created using np.array(). Shape property provides a tuple of number of rows and columns. We can apply various mathematics functions like mean, median etc on the array.



Comparison in Array:

We can apply various techniques to compare one row against other, which would be required when we perform computational analysis.



Array Data Retrieval:

We can retrieve data from an array, in terms of rows, columns. We can also, retrieve specific rows or columns or exclude specific rows or columns.


Max Min Operations:

We can find out various maximum and minimum values from the array. We can find out index of maximum value in the array and also retrieve maximum across an row or column.




Comments

Popular posts from this blog

Spring Integration - Bulk processing Example

Pivotal Cloud Foundry (PCF) Integration with Elastic Cloud Storage (ECS)

AWS - Basic Security Considerations