# Arulius Savio

## Numpy.Divide() – How to Use Numpy Divide in Python?

The division is one of the rudimentary arithmetic operations which is used to find out which multiple of a given number is another. It ain’t something that can be done with our fingers as we were taught to carry out addition & subtraction. So, it becomes all the more tedious when it comes to analyzing […]

## Numpy.subtract(): How to Use Subtract Numbers with NumPy in Python?

One of the rudimentary arithmetic operations is to subtract a given entity from another. Though this might be a no-brainer that doesn’t involve the computing capabilities of a programming language such as Python, one might just underestimate this operation when it comes to handling lumpsum data. This article sets out to explore the different variances

## Multiplying in Python – A Simple Guide

The foundations of data analysis lie in robust arithmetic. All the complicated algorithms that one can develop can be narrowed down into basic arithmetic such as addition, subtraction, multiplication or division; even calculus is a simple means of carrying out these basic operations. That being said, we shall set out to explore carrying out one

## Comparing Date & Time in Python [Easy Step By Step]

When one has to analyze data, it leaves no exception. The tool that is to be deployed for the analysis must be compatible with handling the various types of data that can be thrown at it. The data can be in the form of text, fractions, dates, integers, time & so. Python is one of

## How to Export to Excel using Pandas?

Python can take you as far as analyzing the truckloads of data fed into it, but when it comes to presenting the data to a large audience, it ain’t its cup of tea. There are other dedicated tools which might serve the purpose better. One such tool is MS Excel! This article sets out to

## How to Replace Multiple Values using Pandas?

When one can analyse data using Python, does it give any flexibility to play around with the input data fed for the analysis? This is what this article set out to explore. We shall construct data & demonstrate replacing multiple values within it by leveraging the capabilities of the Pandas library. Setting up the Pandas