scholarmetrics.euclidean

scholarmetrics.euclidean(arr: _Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], ignore_nan: bool = True) → float[source]

Calculate Euclidean index for an author.

An Euclidean index of a vector is the square root of the sum of the squared elements.

Parameters:

  • arr (array-like) – Array of citations.

  • ignore_nan (bool (optional, default=True)) – If True, remove nan values and return 0 if all values are nan.

Returns:

eui – Euclidean index of the author for the given citations.

Return type:

float

Examples

>>> from scholarmetrics import euclidean
>>> citations = [6, 10, 5, 46, 0, 2]
>>> euclidean(citations)
47.75981574503821

Notes

The Euclidean index was originally proposed by Motty Perry and Philip J. Reny [eu].

References

[eu]

Perry, M. and P. J. Reny (2016): “How to Count Citations If You Must”, The American Economic Review, 106(9), pp. 2722-2241. DOI: 10.1257/aer.20140850