Extending Excel with Python and R
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Extending Excel with Python and R

Unlock the potential of analytics languages for advanced data manipulation and visualization

About the Book

– Extending Excel with Python and R is a game changer resource written by experts Steven Sanderson, the author of the healthyverse suite of R packages, and David Kun, co-founder of Functional Analytics.

– This comprehensive guide transforms the way you work with spreadsheet-based data by integrating Python and R with Excel to automate tasks, execute statistical analysis, and create powerful visualizations. 

– Working through the chapters, you’ll find out how to perform exploratory data analysis, time series analysis, and even integrate APIs for maximum efficiency. 

– Both beginners and experts will get everything you need to unlock Excel's full potential and take your data analysis skills to the next level.

– By the end of this book, you’ll be able to import data from Excel, manipulate it in R or Python, and perform the data analysis tasks in your preferred framework while pushing the results back to Excel for sharing with others as needed.

About the Author

Packt Publishing Ltd
Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

Table of Contents

  1. Reading Excel Spreadsheets
  2. Writing Excel Spreadsheets
  3. Executing VBA Code from R and Python
  4. Automating Further (Email Notifications and More)
  5. Formatting Your Excel sheet
  6. Inserting ggplot2/matplotlib Graphs
  7. Pivot Tables (tidyquant in R and with win32com and pypiwin32 in Python)/Summary Table {gt}
  8. Exploratory Data Analysis with R and Python
  9. Statistical Analysis: Linear and Logistic Regression
  10. Time Series Analysis: Statistics, Plots, and Forecasting
  11. Calling R/Python Locally from Excel Directly or via an API
  12. Data Analysis and Visualization with R and Python for Excel Data – A Case Study

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