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Extending Excel with Python and R

Extending Excel with Python and R

By : Steven Sanderson, Kun
5 (5)
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Extending Excel with Python and R

Extending Excel with Python and R

5 (5)
By: Steven Sanderson, Kun

Overview of this 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.
Table of Contents (20 chapters)
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1
Part 1:The Basics – Reading and Writing Excel Files from R and Python
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6
Part 2: Making It Pretty – Formatting, Graphs, and More
10
Part 3: EDA, Statistical Analysis, and Time Series Analysis
14
Part 4: The Other Way Around – Calling R and Python from Excel
16
Part 5: Data Analysis and Visualization with R and Python for Excel Data – A Case Study

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

This introductory part lays the foundation for working with Excel files in both R and Python. The chapters cover essential tasks such as reading and writing Excel spreadsheets using popular libraries such as R and Python, enabling you to automate tasks and further enhance your Excel workflows using tools such as RDCOMClient, blastula, schedule, and smtplib for scheduling runs and sending emails.readxl, openxlsx, xlsx, pandas, and openpyxl. Additionally, you’ll learn how to execute VBA code.

This part has the following chapters:

  • Chapter 1, Reading Excel Spreadsheets
  • Chapter 2, Writing Excel Spreadsheets
  • Chapter 3, Executing VBA Code from R and Python
  • Chapter 4, Automating Further – Task Scheduling and Email

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