Python for Business Analytics – Chapter 18: Multidimensional arrays

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Multidimensional arrays, also known as arrays of arrays, are an important data structure in programming and they play a critical role in business analytics. A multidimensional array is a collection of arrays, where each array can contain one or more elements. In Python, multidimensional arrays are called nested lists.

In business analytics, multidimensional arrays are used to store and process complex data, such as data that has multiple levels of detail or data that requires multiple dimensions to represent. For example, you can use a multidimensional array to store sales data for multiple products, where each product has its own sales data.

One of the benefits of using multidimensional arrays in business analytics is that they provide a convenient way to store and access complex data. For example, if you need to analyze sales data for multiple products and multiple regions, you can store that data in a multidimensional array and then access the data for each product and region individually. This makes it easy to perform operations on the data and analyze it in meaningful ways.

Multidimensional arrays are also useful in business analytics because they allow you to perform operations on the data in a way that is easy to understand and interpret. For example, you can use multidimensional arrays to perform calculations on sales data, such as calculating the total sales for each product in each region, the average sales for each product in each region, and the number of products that have sold above a certain threshold in each region. These calculations can be performed quickly and easily with multidimensional arrays, making it possible to gain valuable insights into your data.

In a nutshell, I would like to say that, multidimensional arrays are an essential tool for business analytics in Python. They allow you to store and manipulate complex data in a structured and efficient manner, making it possible to perform a wide range of operations on that data. Whether you’re analyzing sales data, customer information, or product inventory, multidimensional arrays are a powerful tool that will help you get the most out of your data and make informed decisions.

Python for Business Analytics – Chapter 18: Multidimensional arrays

Loader Loading...
EAD Logo Taking too long?

Reload Reload document
| Open Open in new tab

Download PDF [139.03 KB]

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

95% Discount on “Projects & Recipes, tutorials, ebooks”

Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!