29,99 €
– 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.
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Seitenzahl: 394
Veröffentlichungsjahr: 2024
Extending Excel with Python and R
Unlock the potential of analytics languages for advanced data manipulation and visualization
Steven Sanderson
David Kun
Copyright © 2024 Packt Publishing
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First published: April 2024
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Published by
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ISBN 978-1-80461-069-5
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To my wife, I love you. Thank you for putting the children to bed every night so I could work on this book. I would not have been able to work on it without that time. To my children, Daddy loves you. And to my mom, thank you for thinking any idea I had was a good one.
– Steven Sanderson
To my family, for illuminating every step of this journey with your love and unwavering support.
– David Kun
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.
I want to thank Packt for this opportunity and David, my co-author, for working on this with me. I also want to thank my family as this took a good deal of time to put together.
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.
I extend my heartfelt gratitude to my partner, Ania, and my children for the encouragement throughout the journey of writing this, my inaugural book.
Jesús Martín de la Sierra Silva is a dedicated R developer with an engineering background who has been involved in large IT projects transforming raw data into insightful actionable decisions. He provides decision-making capabilities based on a statistical approach, by exploring connections and patterns in data and producing valuable visualizations. Jesús also specializes in creating user-friendly applications that seamlessly integrate complex computations such as process mining, forecasting, network analysis, or machine learning predictive models. For years, he has promoted the transition from spreadsheet software to R to bring a powerful perspective on modern data analysis.
David Napoli holds a master’s degree in aerospace engineering and All but Dissertation in Health Services Research/Biostatistics. David has 25 years of experience working with data, with extensive experience in quantitative development, including the development, maintenance, and governance of data repositories, risk adjustment methodologies, IBNR determination, and analytic platform innovation. David also has 25 years of experience in advanced data visualization, statistical modeling and evaluation, and survival analysis. David has applied his analytics proficiency in multiple roles, including director of strategic analytics and distinguished faculty instructor of data visualization, data analytics, and advanced analytics curriculums.
Mehmet Sinan İyisoy is a biostatistician with years of experience in medical statistics. He holds BSc and MSc degrees in mathematics and statistics. Starting out as a mathematician, his career transitioned through phases of programmer, system administrator, and biostatistician. Sinan has consistently shown a strong dedication to data and programming. He is an enthusiastic user of a wide array of technologies, predominantly consisting of open source components. He has accumulated experience across various institutions and diverse roles for which his profound expertise was central. With a passion for statistics, Sinan now continues to contribute to scientific literature and public knowledge while working at Necmettin Erbakan University.
Shane Alex Jose has a master’s in statistics. His passion for coding stemmed from tutoring graduate-level Python courses – yet he claims he’s more confident in R. Oddly, he relishes debugging and considers it very cathartic! Currently, Shane is working as an analyst programmer in EvoEnergy’s data analytics team – enhancing models and building/testing internal R packages/shiny dashboards used across the company. Having worked across multiple sectors, Shane is fascinated by the variety of data used across various industries and the impact data can have (especially if incorrectly governed). He aims to become confident across multiple specializations to help identify gaps and develop unique solutions/insights that could potentially address these gaps.
This introductory part lays the foundation for working with Excel files in both R and Python. The chapters cover essential tasks such as reading and writing Excel spreadsheets using popular libraries such as R and Python, enabling you to automate tasks and further enhance your Excel workflows using tools such as RDCOMClient, blastula, schedule, and smtplib for scheduling runs and sending emails.readxl, openxlsx, xlsx, pandas, and openpyxl. Additionally, you’ll learn how to execute VBA code.
This part has the following chapters:
Chapter 1, Reading Excel SpreadsheetsChapter 2, Writing Excel SpreadsheetsChapter 3, Executing VBA Code from R and PythonChapter 4, Automating Further – Task Scheduling and Email