pvanalytics.quality.outliers.tukey(data, k=1.5)#

Identify outliers based on the interquartile range.

A value x is considered an outlier if it does not satisfy the following condition

\[Q_1 - k(Q_3 - Q_1) \le x \le Q_3 + k(Q_3 - Q_1)\]

where \(Q_1\) is the value of the first quartile and \(Q_3\) is the value of the third quartile.

  • data (Series) – The data in which to find outliers.

  • k (float, default 1.5) – Multiplier of the interquartile range. A larger value will be more permissive of values that are far from the median.


A series of booleans with True for each value that is an outlier.

Return type


Examples using pvanalytics.quality.outliers.tukey#

Tukey Outlier Detection

Tukey Outlier Detection