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