SciPy

scipy.stats.cumfreq

scipy.stats.cumfreq(a, numbins=10, defaultreallimits=None, weights=None)[source]

Returns a cumulative frequency histogram, using the histogram function.

Parameters:

a : array_like

Input array.

numbins : int, optional

The number of bins to use for the histogram. Default is 10.

defaultreallimits : tuple (lower, upper), optional

The lower and upper values for the range of the histogram. If no value is given, a range slightly larger than the range of the values in a is used. Specifically (a.min() - s, a.max() + s), where s = (1/2)(a.max() - a.min()) / (numbins - 1).

weights : array_like, optional

The weights for each value in a. Default is None, which gives each value a weight of 1.0

Returns:

cumcount : ndarray

Binned values of cumulative frequency.

lowerlimit : float

Lower real limit

binsize : float

Width of each bin.

extrapoints : int

Extra points.

Examples

>>> from scipy import stats
>>> x = [1, 4, 2, 1, 3, 1]
>>> cumfreqs, lowlim, binsize, extrapoints = stats.cumfreq(x, numbins=4)
>>> cumfreqs
array([ 3.,  4.,  5.,  6.])
>>> cumfreqs, lowlim, binsize, extrapoints =     ...     stats.cumfreq(x, numbins=4, defaultreallimits=(1.5, 5))
>>> cumfreqs
array([ 1.,  2.,  3.,  3.])
>>> extrapoints
3

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