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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

Making a table with the gt package

The gt package in R allows users to create beautiful and customizable tables in R. One of the main pros of the gt package is its ease of use. The package is designed to be user-friendly, with a simple syntax that makes it easy to create tables quickly. Additionally, the package offers a wide range of customization options, allowing users to create tables that are tailored to their specific needs.

Another pro of the gt package is its ability to handle large datasets. The package is optimized for performance, which means that it can handle large datasets without slowing down. This is particularly useful for users who need to create tables from large datasets, as it allows them to do so quickly and efficiently.

The gt package also offers a wide range of styling options, allowing users to create tables that are visually appealing and easy to read. Users can customize the fonts, colors, and formatting of their tables, making it easy to create tables...

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