Sanderson / Kun Extending Excel with Python and R

Unlock the potential of analytics languages for advanced data manipulation and visualization
1. Auflage 2024
ISBN: 978-1-80461-554-6
Verlag: De Gruyter
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 344 Seiten

- 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.

Autoren/Hrsg.

Sanderson, Steven

Kun, David

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung

Inhaltsverzeichnis

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

Über Autor(innen)

Sanderson Steven :

Steven Sanderson, MPH, is an applications manager for the patient accounts department at Stony Brook Medicine. He received his bachelor's degree in economics and his master's in public health from Stony Brook University. He has worked in healthcare in some capacity for just shy of 20 years. He is the author and maintainer of the healthyverse set of R packages. He likes to read material related to social and labor economics and has recently turned his efforts back to his guitar with the hope that his kids will follow suit as a hobby they can enjoy together.Kun David :

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 and 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.