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Extending Excel with Python and R

You're reading from  Extending Excel with Python and R

Product type Book
Published in Apr 2024
Publisher Packt
ISBN-13 9781804610695
Pages 344 pages
Edition 1st Edition
Languages
Authors (2):
Steven Sanderson Steven Sanderson
Profile icon Steven Sanderson
David Kun David Kun
Profile icon David Kun
View More author details

Table of Contents (20) Chapters

Preface 1. Part 1:The Basics – Reading and Writing Excel Files from R and Python
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

Automating Excel tasks

One of the major benefits of executing VBA code from Python is the automation of Excel tasks.

This section will discuss practical examples of automating common Excel operations using VBA from Python. By seamlessly integrating Python and VBA, you can streamline your data analysis workflows and significantly enhance your productivity.

Let’s explore some of the tasks you can automate using this powerful combination.

Data manipulation

With Python and VBA integration, you can automate data manipulation tasks in Excel. This includes tasks such as sorting data, filtering records, merging datasets, and performing complex transformations. For example, you can use Python to retrieve data from external sources, process it using Python libraries such as pandas or NumPy, and then update the Excel worksheet with the transformed data using VBA. This integration allows you to automate repetitive data manipulation tasks and ensure data consistency across sources...

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