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You're reading from  Extending Excel with Python and R

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Published inApr 2024
PublisherPackt
ISBN-139781804610695
Edition1st Edition
Concepts
Data Analysis
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Authors (2):
Steven Sanderson
Steven Sanderson
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Steven Sanderson

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.
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David Kun
David Kun
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David Kun

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.
Read more about David Kun

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Choosing between openpyxl and pandas

When it comes to exporting data to Excel, both openpyxl and pandas are excellent choices. openpyxl is a dedicated library for working with Excel files as it provides extensive functionality for creating, modifying, and saving Excel workbooks. On the other hand, pandas offers a high-level data manipulation interface with convenient methods for exporting data to Excel, which is ideal when a simple data dump is all you need.

If you require fine-grained control over the Excel file’s structure, such as adding formatting, formulas, or charts, openpyxl is a suitable option. It allows you to work directly with the underlying Excel objects, providing more flexibility. On the other hand, if you primarily focus on data manipulation and want a simpler way to export DataFrames to Excel without worrying about Excel-specific features, pandas is a convenient choice. It abstracts away some of the lower-level details and provides a more straightforward...

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Extending Excel with Python and R
Published in: Apr 2024Publisher: PacktISBN-13: 9781804610695
© 2024 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
Steven Sanderson

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.
Read more about Steven Sanderson

author image
David Kun

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.
Read more about David Kun

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