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You're reading from  Extending Excel with Python and R

Product typeBook
Published inApr 2024
PublisherPackt
ISBN-139781804610695
Edition1st Edition
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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.
Read more about Steven Sanderson

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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Making a table with the Base R xtabs function

Before we move onto the core of the topic, let us understand a few of the important components.

Here is a list of some key components of a pivot table:

  • Rows and columns: Pivot tables typically involve two primary components – rows and columns. The data rows contain individual records or observations, while the columns contain the attributes or variables that define those records.
  • Values: Pivot tables allow users to aggregate and summarize data by calculating values based on specific metrics, such as sum, average, count, or percentage.
  • Filters and slicers: Filters and slicers enable users to focus on specific subsets of data within the pivot table, enhancing the granularity of analysis. These tools are especially useful when dealing with large datasets.
  • Row and column labels: Pivot tables allow users to drag and drop attributes into row and column labels, defining the layout and structure of the table dynamically...
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Extending Excel with Python and R
Published in: Apr 2024Publisher: PacktISBN-13: 9781804610695

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