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Extending Excel with Python and R: Unlock the potential of analytics languages for advanced data manipulation and visualization
Purchase options and add-ons
Seamlessly integrate the Python and R programming languages with spreadsheet-based data analysis to maximize productivity
Key Features- Perform advanced data analysis and visualization techniques with R and Python on Excel data
- Use exploratory data analysis and pivot table analysis for deeper insights into your data
- Integrate R and Python code directly into Excel using VBA or API endpoints
- Purchase of the print or Kindle book includes a free PDF eBook
For businesses, data analysis and visualization are crucial for informed decision-making; however, Excel's limitations can make these tasks time-consuming and challenging. 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, the company behind the ownR platform engineering solution for R, Python, and other data science languages.
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. Whether you're a beginner or an expert, this book has 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.
What you will learn- Read and write Excel files with R and Python libraries
- Automate Excel tasks with R and Python scripts
- Use R and Python to execute Excel VBA macros
- Format Excel sheets using R and Python packages
- Create graphs with ggplot2 and Matplotlib in Excel
- Analyze Excel data with statistical methods and time series analysis
- Explore various methods to call R and Python functions from Excel
If you're a data analyst or data scientist, or a quants, actuaries, or data practitioner looking to enhance your Excel skills and expand your data analysis capabilities with R and Python, this book is for you. It provides a comprehensive introduction to the topics covered, making it suitable for both beginners and intermediate learners. A basic understanding of Excel, Python, and R is all you need to get started.
Table of Contents- Reading Excel Spreadsheets
- Writing Excel Spreadsheets
- Executing VBA Code from R and Python
- Automating Further (Email Notifications and More)
- Formatting Your Excel sheet
- Inserting ggplot2/matplotlib Graphs
- Pivot Tables (tidyquant in R and with win32com and pypiwin32 in Python)/Summary Table {gt}
- Exploratory Data Analysis with R and Python
- Statistical Analysis: Linear and Logistic Regression
- Time Series Analysis: Statistics, Plots, and Forecasting
- Calling R/Python Locally from Excel Directly or via an API
- Data Analysis and Visualization with R and Python for Excel Data - A Case Study
- ISBN-101804610690
- ISBN-13978-1804610695
- PublisherPackt Publishing
- Publication dateApril 30, 2024
- LanguageEnglish
- Dimensions9.25 x 7.52 x 0.72 inches
- Print length344 pages
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Editorial Reviews
About the Author
Steven Sanderson has been working in healthcare for almost 20 years with a focus in the last 12 years on analytics. Steve has spent those years working on dashboards, automations, and visualizations for clinical, finance and IT operations. Steven is also the author of the healthyverse suite of R packages which are in active development. Steven received his MPH from Stony Brook University School of Medicine Graduate Program in Public Health.
David Kun is the co-founder of Functional Analytics, the company behind the ownR platform engineering solution for R, Python and other data science languages. He is a qualified Actuary with two MSc's concentrated on Mathematics. He has been using R since his MSc thesis in 2006 and Python since 2018
Product details
- Publisher : Packt Publishing (April 30, 2024)
- Language : English
- Paperback : 344 pages
- ISBN-10 : 1804610690
- ISBN-13 : 978-1804610695
- Item Weight : 1.32 pounds
- Dimensions : 9.25 x 7.52 x 0.72 inches
- Best Sellers Rank: #189,510 in Books (See Top 100 in Books)
- #74 in Data Modeling & Design (Books)
- #99 in Data Processing
- #5,468 in Unknown
About the authors
Steven Sanderson is a Manager of Applications with a deep passion for data and it's compliments: cleaning, analysis, visualization and communication. He is known primarily for his work in R.
After is MPH, Steven continued his work in the healthcare industry as a clinical decision support analyst working his way up to Manager of Applications at Stony Brook Medicine for Patient Financial Services. He currently is focused on expanding functions in his healthyverse suite of packages while also slimming them down and expanding their robustness. He also now enjoys helping mentor junior employees to set them up for success.
David Kun is a mathematician and actuary who has always worked in the gray zone between
quantitative teams and ICT, aiming to build a bridge. He is a co-founder and director of Functional
Analytics, the creator of the ownR infinity platform. As a data scientist, he also uses ownR for
his daily work. His projects include time series analysis for demand forecasting, computer vision for
design automation, and visualization.
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