scipy.stats.relfreq¶
- scipy.stats.relfreq(a, numbins=10, defaultreallimits=None, weights=None)[source]¶
Returns a relative 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 then 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 : relfreq : ndarray
Binned values of relative frequency.
lowerreallimit : float
Lower real limit
binsize : float
Width of each bin.
extrapoints : int
Extra points.
Examples
>>> a = np.array([1, 4, 2, 1, 3, 1]) >>> relfreqs, lowlim, binsize, extrapoints = sp.stats.relfreq(a, numbins=4) >>> relfreqs array([ 0.5 , 0.16666667, 0.16666667, 0.16666667]) >>> np.sum(relfreqs) # relative frequencies should add up to 1 0.99999999999999989