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Extending Excel with Python and R

You're reading from   Extending Excel with Python and R Unlock the potential of analytics languages for advanced data manipulation and visualization

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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781804610695
Length 344 pages
Edition 1st Edition
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Authors (2):
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Steven Sanderson Steven Sanderson
Author Profile Icon Steven Sanderson
Steven Sanderson
David Kun David Kun
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David Kun
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Table of Contents (20) Chapters Close

Preface 1. Part 1:The Basics – Reading and Writing Excel Files from R and Python FREE CHAPTER
2. Chapter 1: Reading Excel Spreadsheets 3. Chapter 2: Writing Excel Spreadsheets 4. Chapter 3: Executing VBA Code from R and Python 5. Chapter 4: Automating Further – Task Scheduling and Email 6. Part 2: Making It Pretty – Formatting, Graphs, and More
7. Chapter 5: Formatting Your Excel Sheet 8. Chapter 6: Inserting ggplot2/matplotlib Graphs 9. Chapter 7: Pivot Tables and Summary Tables 10. Part 3: EDA, Statistical Analysis, and Time Series Analysis
11. Chapter 8: Exploratory Data Analysis with R and Python 12. Chapter 9: Statistical Analysis: Linear and Logistic Regression 13. Chapter 10: Time Series Analysis: Statistics, Plots, and Forecasting 14. Part 4: The Other Way Around – Calling R and Python from Excel
15. Chapter 11: Calling R/Python Locally from Excel Directly or via an API 16. Part 5: Data Analysis and Visualization with R and Python for Excel Data – A Case Study
17. Chapter 12: Data Analysis and Visualization with R and Python in Excel – A Case Study 18. Index 19. Other Books You May Enjoy

Calling R/Python Locally from Excel Directly or via an API

In this chapter, we are going to discuss calling R and Python from within Excel. You may ask yourself why you would want to do that when there are many functions inside of Excel that one can use or, if so desired, can write with the VBA portion of the application. One reason why you might want to call R or Python from Excel is to leverage the power and flexibility of these programming languages for data analysis and visualization. Excel is a widely used spreadsheet application that can handle large datasets and perform basic calculations and functions. However, Excel has some limitations when it comes to more advanced or customized tasks, such as statistical modeling, machine learning, web scraping, natural language processing, and so on. By calling R or Python from Excel, you can access the rich libraries and packages that these languages offer and use them to manipulate, transform, and visualize your data in more sophisticated...

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