quantile

Syntax

quantile(X, q, [interpolation='linear'])

Details

Calculates values at the given quantile in X.

DolphinDB's quantile features a concise syntax and ignores null values natively, making it suitable for real-time computation on massive datasets. NumPy's quantile is designed for multidimensional arrays and supports passing an array to compute multiple quantiles in batch. SciPy's quantile not only allows you to specify different quantiles for each data slice, but also supports the Harrell-Davis statistical estimator and the nan_policy parameter, so it can handle samples with missing values natively.

Parameters

X is a numeric vector, matrix or table.

q is a floating number between 0 and 1.

interpolation is a string indicating how to interpolate if the quantile is between element i and j in X with i<j. It can take the following values:

  • 'linear' (default): i+(j-i)*fraction, where fraction is the decimal part of q*size(X).

  • 'lower': i

  • 'higher': j

  • 'nearest': i or j whichever is nearest.

  • 'midpoint': (i+ j)/2

Returns

A DOUBLE scalar/vector.

Examples

a=[6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36];
quantile(a,0.25);
// output: 25.5

quantile(a,0.5);
// output: 40

quantile(a,0.75);
// output: 42.5

quantile(a,0.75, 'lower');
// output: 42

Related function: quantileSeries, percentile