Shapes
(Long, Short, Wide, Narrow and Big) - The concept of ‘shapes of data’ refers to different structures and organizations that datasets can take. Understanding the shape of data is fundamental in data analysis, as it influences how information is stored, processed, and analyzed. Different shapes have implications for data manipulation, visualization, and modeling.
References
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https://en.wikipedia.org/wiki/Curse_of_dimensionality🔗en.wikipedia.org -
https://en.wikipedia.org/wiki/Wide_and_narrow_data🔗en.wikipedia.org
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What does it mean for data to be in long form vs wide form, and when would you use each? In Pandas, how do you convert from one form to another?🔗Stacked Turtles -
The human genome is complex. We address this complexity to transform drug development. Learn about our technology, team, applications and COVID-19 developments.🔗biotx.ai
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This tutorial explains the difference between long and wide data formats, including several examples.🔗Statology -
When performing data analysis, the structure of the data determines what kind of analysis you can do with it and how it is consumed – by machine🔗The Data School Down Under