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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
2. Chapter 1: Reading Excel Spreadsheets FREE CHAPTER 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

Open source solutions for exposing R as API endpoints

We are going to start off by first showing how to expose R as an API endpoint via the plumber package. The plumber package and its associated documentation can be found at the following URL: https://www.rplumber.io/index.html.

The first thing we will do is build out a very simple single-argument API to obtain the histogram of a standard normal distribution. Let’s take a look at the code; we will then discuss what is happening inside of it:

#* Plot out data from a random normal distribution
#* @param .mean The mean of the standard normal distribution
#* @get /plot
#* @serializer png
function(.mean) {
  mu <- as.numeric(.mean)
  hist(rnorm(n = 1000, mean = mu, sd = 1))
}

The lines starting with #* are comments. In the plumber API, these comments are special and are used for documentation. They describe what the API endpoint does and provide information about the parameters. The first comment introduces...

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