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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
Concepts
Authors (2):
Steven Sanderson Steven Sanderson
Profile icon Steven Sanderson
LinkedIn
Steven Sanderson, MPH, is an applications manager for the patient accounts department at Stony Brook Medicine. He received his bachelor's degree in economics and his master's in public health from Stony Brook University. He has worked in healthcare in some capacity for just shy of 20 years. He is the author and maintainer of the healthyverse set of R packages. He likes to read material related to social and labor economics and has recently turned his efforts back to his guitar with the hope that his kids will follow suit as a hobby they can enjoy together.
See other products by Steven Sanderson
David Kun David Kun
Profile icon David Kun
LinkedIn
David Kun is a mathematician and actuary who has always worked in the gray zone between quantitative teams and ICT, aiming to build a bridge. He is a co-founder and director of Functional Analytics and the creator of the ownR Infinity platform. As a data scientist, he also uses ownR for his daily work. His projects include time series analysis for demand forecasting, computer vision for design automation, and visualization.
See other products by 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

Summary

Embedding visualizations in Excel reports offers a practical way to enhance data presentation, customization, and automation. Whether you’re working with sales data, financial reports, or any other dataset, this approach empowers you to create insightful reports that convey your data-driven insights effectively.

In this chapter, you learned about data visualization techniques in general, the ways to extend your Excel workflows and reports with those techniques, and how to implement them in R and Python.

We have covered the most popular and powerful R packages and Python libraries in detail. You learned about the typical plots used to carry out your analysis and how to communicate your findings, along with use cases and examples where those data visualizations can be used.

The next time you prepare an Excel report, you will be in a position to dazzle your audience with the most beautiful and insightful visualizations they have ever seen!

In the next chapter...

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Authors (2)

Left arrow icon
Profile icon Steven Sanderson
LinkedIn
Steven Sanderson, MPH, is an applications manager for the patient accounts department at Stony Brook Medicine. He received his bachelor's degree in economics and his master's in public health from Stony Brook University. He has worked in healthcare in some capacity for just shy of 20 years. He is the author and maintainer of the healthyverse set of R packages. He likes to read material related to social and labor economics and has recently turned his efforts back to his guitar with the hope that his kids will follow suit as a hobby they can enjoy together.
Read more
See other products by Steven Sanderson
Profile icon David Kun
LinkedIn
David Kun is a mathematician and actuary who has always worked in the gray zone between quantitative teams and ICT, aiming to build a bridge. He is a co-founder and director of Functional Analytics and the creator of the ownR Infinity platform. As a data scientist, he also uses ownR for his daily work. His projects include time series analysis for demand forecasting, computer vision for design automation, and visualization.
See other products by David Kun
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