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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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Toc

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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

accuracy of model 203

adjusted R-squared 208

Advanced Python Scheduler (APScheduler) 68, 69

features and benefits 68

aesthetic 122

Apache Kafka 69

Application Programming Interface (API) 268

calling, from Excel VBA 276-279

R/Python, calling from Excel via 268

Augmented Dickey-Fuller (ADF) test 239-241

components 240, 241

auto ARIMA modeling

with healthyR.ts 226-232

autocorrelation function (ACF) plot 223, 238

creating, in R 224-226

autoregressive (AR) 238

autoregressive integrated moving average (ARIMA) models 218

Azure Functions 279

con 279

pro 279

use cases 279

B

background color of cells

modifying 94

bar charts

cons 114

constructing, with matplotlib 136, 137

constructing, with plotnine 123

ggplot2, using...

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