staircase.StairsSlicer.hist#

StairsSlicer.hist(*args, **kwargs)#

Calculates histogram data for each of the step function slices

Parameters:
bins“unit”, sequence or pandas.IntervalIndex

If bins is “unit” then the histogram bins will have unit length and cover the range of step function values. If bins is a sequence, it defines a monotonically increasing array of bin edges. If bins are defined by pandas.IntervalIndex they should be non-overlapping and monotonic increasing.

closed{“left”, “right”}, default “left”

Indicates whether the histogram bins are left-closed right-open or right-closed left-open. Only relevant when bins is not a pandas.IntervalIndex

stat{“sum”, “frequency”, “density”, “probability”}, default “sum”
The aggregate statistic to compute in each bin. Inspired by seaborn.histplot() stat parameter.

  • sum the magnitude of observations

  • frequency values of the histogram are divided by the corresponding bin width

  • density normalises values of the histogram so that the area is 1

  • probability normalises values so that the histogram values sum to 1

Returns:
pandas.Dataframe

Each row corresponds to a step function slice. Each column corresponds to a bin.

Examples

>>> df = sc.make_test_data(seed=0)
>>> sf = sc.Stairs(df, "start", "end", "value")
>>> sf.plot()
../../_images/staircase-StairsSlicer-hist-1.png 
>>> cuts = pd.date_range("2021", periods=12, freq="MS")
>>> sf.slice(cuts).hist(bins=[300, 400, 500, 600], stat="probability")
                          [300.0, 400.0)  [400.0, 500.0)  [500.0, 600.0)
[2021-01-01, 2021-02-01)        0.216756        0.783244        0.000000
[2021-02-01, 2021-03-01)        0.927480        0.072520        0.000000
[2021-03-01, 2021-04-01)        0.000000        0.443907        0.556093
[2021-04-01, 2021-05-01)        0.000000        0.487269        0.512731
[2021-05-01, 2021-06-01)        0.618996        0.381004        0.000000
[2021-06-01, 2021-07-01)        0.592523        0.407477        0.000000
[2021-07-01, 2021-08-01)        0.000000        0.684812        0.315188
[2021-08-01, 2021-09-01)        0.000000        0.985954        0.014046
[2021-09-01, 2021-10-01)        0.029444        0.970556        0.000000
[2021-10-01, 2021-11-01)        0.000000        0.992876        0.007124
[2021-11-01, 2021-12-01)        0.000000        0.875370        0.124630
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