scipy.stats.percentileofscore(a, score, kind='rank')

The percentile rank of a score relative to a list of scores.

A percentileofscore of, for example, 80% means that 80% of the scores in a are below the given score. In the case of gaps or ties, the exact definition depends on the optional keyword, kind.

Parameters :

a: array like :

Array of scores to which score is compared.

score: int or float :

Score that is compared to the elements in a.

kind: {‘rank’, ‘weak’, ‘strict’, ‘mean’}, optional :

This optional parameter specifies the interpretation of the resulting score:

  • “rank”: Average percentage ranking of score. In case of

    multiple matches, average the percentage rankings of all matching scores.

  • “weak”: This kind corresponds to the definition of a cumulative

    distribution function. A percentileofscore of 80% means that 80% of values are less than or equal to the provided score.

  • “strict”: Similar to “weak”, except that only values that are

    strictly less than the given score are counted.

  • “mean”: The average of the “weak” and “strict” scores, often used in

    testing. See

Returns :

pcos : float

Percentile-position of score (0-100) relative to a.


Three-quarters of the given values lie below a given score:

>>> percentileofscore([1, 2, 3, 4], 3)

With multiple matches, note how the scores of the two matches, 0.6 and 0.8 respectively, are averaged:

>>> percentileofscore([1, 2, 3, 3, 4], 3)

Only 2/5 values are strictly less than 3:

>>> percentileofscore([1, 2, 3, 3, 4], 3, kind='strict')

But 4/5 values are less than or equal to 3:

>>> percentileofscore([1, 2, 3, 3, 4], 3, kind='weak')

The average between the weak and the strict scores is

>>> percentileofscore([1, 2, 3, 3, 4], 3, kind='mean')

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