scipy.stats.relfreq(a, numbins, defaultreallimits, weights) is a relative frequency histogram, using the histogram function.
Parameters :
arr : [array_like] input array.
numbins : Number of bins to use for the histogram. [Default = 10]
defaultreallimits : (lower, upper) range of the histogram.
weights : [array_like] weights for each array element.Results :
– relative frequency binned values
– width of each bin
– lower real limit
– extra points.
Code #1:
# relative frequency from scipy import stats import numpy as np arr1 = [1, 3, 27, 2, 5, 13] print ("Array element : ", arr1, "\n") a, b, c, d = stats.relfreq(arr1, numbins = 4) print ("cumulative frequency : ", a) print ("Lower Limit : ", b) print ("bin size : ", c) print ("extra-points : ", d) |
Output :
Array element : [1, 3, 27, 2, 5, 13] cumulative frequency : [0.66666667 0.16666667 0. 0.16666667] Lower Limit : -3.333333333333333 bin size : 8.666666666666666 extra-points : 0
Code #2:
# relative frequency from scipy import stats import numpy as np arr1 = [1, 3, 27, 2, 5, 13] print ("Array element : ", arr1, "\n") a, b, c, d = stats.relfreq(arr1, numbins = 4, weights = [.1, .2, .1, .3, 1, 6]) print ("cumfreqs : ", a) print ("lowlim : ", b) print ("binsize : ", c) print ("extrapoints : ", d) |
Output :
Array element : [1, 3, 27, 2, 5, 13] cumfreqs : [0.26666667 1. 0. 0.01666667] lowlim : -3.333333333333333 binsize : 8.666666666666666 extrapoints : 0
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