Seamlessly integrate the Python and R programming languages with spreadsheet-based data analysis to maximize productivity

• 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

– 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.

• 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.

– The comprehensive approach to the topics covered makes it suitable for both beginners and intermediate learners.

– A basic understanding of Excel, Python, and R is all you need to get started.

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