Association Pattern Analysis

 Some of the very earliest work we did in the big enterprise used forms of this analysis.   A classic pattern analysis.    Good basic intro with code.  Is applicable in many areas. 

Association Analysis Explained

How grocery stores are becoming more effective at marketing through data science

By Amanda West  in Towards Data Science

Association analysis is a hot topic in data science right now. By discovering relationships between items within large quantities or networks of data, we can glean insights in many areas. These include uncovering unconscious consumer buying patterns at a particular store or through an app (known as market basket transactions), finding interesting patterns in text mining, or potentially discovering patterns in healthcare, transportation, or survey-based data. These relationships may be represented by what we call association rules, which are typically written in the form {A} → {B}, where the two items A and B exhibit some sort of relationship.

This article is intended for the data science-curious who are passingly familiar with data science, but might not have a deep knowledge of the industry. In this article, you will learn:

Vocabulary / Definitions

Overview of the Apriori Algorithm

Common Association Rules

Implementation in R

Statistical Pitfalls ... " 

Market Basket Analysis

Some of the very earliest analysis (1970s) we supported in the enterprise were variants on market basket analysis.    So I was pleased to find this relatively simple example posted in DSC, by Ayumi Owada,  here using Apriori in Python.   Every marketing person should know of this capability, answering the question: What do people buy with this?

Maximizing Sales with Market Basket Analysis    Posted by Ayumi Owada  

Sales data analyses can provide a wealth of insights for any business but rarely is it made available to the public. In 2018, however, a retail chain provided Black Friday sales data on Kaggle as part of a Kaggle competition. Although the store and product lines are anonymized, the dataset presents a great learning opportunity to find business insights! In this post, we’ll cover how to prepare data, perform basic analysis, and glean additional insights via a technique called Market Basket Analysis.

Let’s see what the data looks like. We use Pivot Billions to analyze and manipulate large amounts of data via an intuitive and familiar spreadsheet style. After importing, we see that the data contains over 500K rows at the bottom, along with example data for each column.  ... "