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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
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

Choosing between openpyxl and pandas

When it comes to exporting data to Excel, both openpyxl and pandas are excellent choices. openpyxl is a dedicated library for working with Excel files as it provides extensive functionality for creating, modifying, and saving Excel workbooks. On the other hand, pandas offers a high-level data manipulation interface with convenient methods for exporting data to Excel, which is ideal when a simple data dump is all you need.

If you require fine-grained control over the Excel file’s structure, such as adding formatting, formulas, or charts, openpyxl is a suitable option. It allows you to work directly with the underlying Excel objects, providing more flexibility. On the other hand, if you primarily focus on data manipulation and want a simpler way to export DataFrames to Excel without worrying about Excel-specific features, pandas is a convenient choice. It abstracts away some of the lower-level details and provides a more straightforward...

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