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Extending Excel with Python and R

Extending Excel with Python and R

By : Steven Sanderson, Kun
5 (5)
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Extending Excel with Python and R

Extending Excel with Python and R

5 (5)
By: Steven Sanderson, Kun

Overview of this book

– Extending Excel with Python and R is a game changer resource written by experts Steven Sanderson, the author of the healthyverse suite of R packages, and David Kun, co-founder of Functional Analytics. – This comprehensive guide transforms the way you work with spreadsheet-based data by integrating Python and R with Excel to automate tasks, execute statistical analysis, and create powerful visualizations. – Working through the chapters, you’ll find out how to perform exploratory data analysis, time series analysis, and even integrate APIs for maximum efficiency. – Both beginners and experts will get everything you need to unlock Excel's full potential and take your data analysis skills to the next level. – By the end of this book, you’ll be able to import data from Excel, manipulate it in R or Python, and perform the data analysis tasks in your preferred framework while pushing the results back to Excel for sharing with others as needed.
Table of Contents (20 chapters)
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1
Part 1:The Basics – Reading and Writing Excel Files from R and Python
6
Part 2: Making It Pretty – Formatting, Graphs, and More
10
Part 3: EDA, Statistical Analysis, and Time Series Analysis
14
Part 4: The Other Way Around – Calling R and Python from Excel
16
Part 5: Data Analysis and Visualization with R and Python for Excel Data – A Case Study

Calling R and Python from Excel via an API

An API, or Application Programming Interface, serves as a bridge between different software applications, allowing them to communicate and share data in a standardized way. It’s like a waiter at a restaurant who takes your order and conveys it to the kitchen, bringing back the meal once it’s ready.

In the digital world, an API specifies how software components should interact. It defines the methods and data formats that applications can use to request and exchange information. APIs can be used for various purposes, such as accessing web services, databases, or even hardware devices.

One fundamental use of APIs is enabling third-party developers to integrate their applications with existing services or platforms. In the context of your coding interests in R and Python, APIs can be utilized for data retrieval and for exposing your models to other software, including Excel.

The beauty of APIs lies in their versatility...

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