Extending Excel with Python and R
Unlock the potential of analytics languages for advanced data manipulation and visualization
Published on 23. September 2024
344 pages
978-1-80461-554-6 (ISBN)
Description
No detailed description available for "Extending Excel with Python and R".
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Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
12,16 MB
ISBN-13
978-1-80461-554-6 (9781804615546)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Other editions
Additional editions
Steven Sanderson | David Kun
Extending Excel with Python and R
Unlock the potential of analytics languages for advanced data manipulation and visualization
Book
04/2024
Packt Publishing
€52.30
Shipment within 3-4 weeks
Persons
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.
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.
Content
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
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
