Why I've decided to write this

In my last article I've talked about returning values with Python. But returning them is simple, what can make it harder is what I'm going to talk about today: where the value is treated.

Python object in IRIS

Following the example of the last aricle, we have the method:

csp-log-tutorial

Prerequisites

Make sure you have git installed.

I created a git folder inside the IRIS mgr directory. I right clicked the git folder and chose Git Bash Here from the context menu.

git clone https://github.com/oliverwilms/csp-log-tutorial.git

Clone my csp-log-tutorial GitHub repo if you like to try it out for yourself.

InterSystems IRIS has quite a few different kinds properties. Let’s put them in order so that they make better sense.

First of all, I would divide them into categories:

• Atomic or simple properties (all those %String, %Integer, %Data and other system or user datatypes)
• References to stored objects
• Built-in objects
• Streams (both binary and character)
• Collections (which are divided into arrays and lists)
• Relationships (one-many and parent-children)

Some of these kinds of properties are quite straightforward. For example, atomic properties:

Property Name As %Name;
Property DoB As %Date
Property Age As %Integer

Introduction

Data analytics is a crucial aspect of business decision-making in today's fast-paced world. Organizations rely heavily on data analysis to make informed decisions and stay ahead of the competition. In this article, we will explore how data analytics can be performed using Pandas and Intersystems Embedded Python. We will discuss the basics of Pandas, the benefits of using Intersystems Embedded Python, and how they can be used together to perform efficient data analytics.