scipy.stats.percentileofscore¶

scipy.stats.
percentileofscore
(a, score, kind='rank')[source]¶ 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
 aarray_like
Array of scores to which score is compared.
 scoreint 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
 pcosfloat
Percentileposition of score (0100) relative to a.
See also
Examples
Threequarters of the given values lie below a given score:
>>> from scipy import stats >>> stats.percentileofscore([1, 2, 3, 4], 3) 75.0
With multiple matches, note how the scores of the two matches, 0.6 and 0.8 respectively, are averaged:
>>> stats.percentileofscore([1, 2, 3, 3, 4], 3) 70.0
Only 2/5 values are strictly less than 3:
>>> stats.percentileofscore([1, 2, 3, 3, 4], 3, kind='strict') 40.0
But 4/5 values are less than or equal to 3:
>>> stats.percentileofscore([1, 2, 3, 3, 4], 3, kind='weak') 80.0
The average between the weak and the strict scores is
>>> stats.percentileofscore([1, 2, 3, 3, 4], 3, kind='mean') 60.0