mathnet-numerics | Math.NET Numerics - Math | Math library
kandi X-RAY | mathnet-numerics Summary
kandi X-RAY | mathnet-numerics Summary
Math.NET Numerics is an opensource numerical library for .NET, Silverlight and Mono. Math.NET Numerics is the numerical foundation of the Math.NET initiative, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Covered topics include special functions, linear algebra, probability models, random numbers, statistics, interpolation, integration, regression, curve fitting, integral transforms (FFT) and more. In addition to the core .NET package (which is written entirely in C#), Numerics specifically supports F# with idiomatic extension modules and maintains mathematical data structures like BigRational that originated in the F# PowerPack. If a performance boost is needed, the managed-code provider backing its linear algebra routines and decompositions can be exchanged with wrappers for optimized native implementations such as Intel MKL.
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QUESTION
Background
Let's think, there is a list of values which presents activity of a person for several hours. That person did not have any movement in those hours. Therefore, all the values are 0.
What did raise the question?
Searching on Google, I found the following formula of skewness. The same formula is available in some other sites also. In the denominator part, Standard Deviation (SD) is included. For a list of similar non-zero values (e.g., [1, 1, 1]) and also for 0 values (i.e., [0, 0, 0]), the SD will be 0. Therefore, I am supposed to get NaN
(something divided by 0) for skewness. Surprisingly, I get 0 while calling pandas.DataFrame.skew()
.
My Question
Why does pandas.DataFrame.skew()
return 0 when the SD of a list of values is 0?
Minimum Reproducible Example
...ANSWER
Answered 2022-Jan-14 at 09:19You can find the implementation here: https://github.com/pandas-dev/pandas/blob/main/pandas/core/nanops.py
As you can see there is a:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install mathnet-numerics
MathNet.Numerics
MathNet.Numerics.FSharp - optional extensions for a better F# experience. BigRational.
MathNet.Numerics.Providers.MKL - Binding to Native Intel MKL provider.
MathNet.Numerics.MKL.Win - Native Intel MKL provider (Windows).
MathNet.Numerics.MKL.Win-x86 - Native Intel MKL provider (Windows/32-bit only).
MathNet.Numerics.MKL.Win-x64 - Native Intel MKL provider (Windows/64-bit only).
MathNet.Numerics.Data.Text - Text-based matrix formats like CSV and MatrixMarket.
MathNet.Numerics.Data.Matlab - MATLAB Level-5 matrix file format.
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