larray.Array.describe_by

Array.describe_by(*args, percentiles=None) → Array[source]

Descriptive summary statistics, excluding NaN values, along axes or for groups.

By default, it includes the number of non-NaN values, the mean, standard deviation, minimum, maximum and the 25, 50 and 75 percentiles.

Parameters

*argsint or str or Axis or Group or any combination of those, optional: Axes or groups to include in the result after aggregating. Defaults to aggregate over the whole array.
percentilesarray-like, optional.: list of integer percentiles to include. Defaults to [25, 50, 75].

Returns

Array

See also

Array.describe

Examples

>>> data = [[0, 6, 3, 5, 4, 2, 1, 3], [7, 5, 3, 2, 8, 5, 6, 4]]
>>> arr = Array(data, 'gender=Male,Female;year=2013..2020').astype(float)
>>> arr
gender\year  2013  2014  2015  2016  2017  2018  2019  2020
       Male   0.0   6.0   3.0   5.0   4.0   2.0   1.0   3.0
     Female   7.0   5.0   3.0   2.0   8.0   5.0   6.0   4.0
>>> arr.describe_by('gender')
gender\statistic  count  mean  std  min   25%  50%   75%  max
            Male    8.0   3.0  2.0  0.0  1.75  3.0  4.25  6.0
          Female    8.0   5.0  2.0  2.0  3.75  5.0  6.25  8.0
>>> arr.describe_by('gender', (X.year[:2015], X.year[2018:]))
gender  year\statistic  count  mean  std  min  25%  50%  75%  max
  Male           :2015    3.0   3.0  3.0  0.0  1.5  3.0  4.5  6.0
  Male           2018:    3.0   2.0  1.0  1.0  1.5  2.0  2.5  3.0
Female           :2015    3.0   5.0  2.0  3.0  4.0  5.0  6.0  7.0
Female           2018:    3.0   5.0  1.0  4.0  4.5  5.0  5.5  6.0
>>> arr.describe_by('gender', percentiles=[50, 90])
gender\statistic  count  mean  std  min  50%  90%  max
            Male    8.0   3.0  2.0  0.0  3.0  5.3  6.0
          Female    8.0   5.0  2.0  2.0  5.0  7.3  8.0