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# sciPy function stats.relfreq () | python

` 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, ` `" "` `) `   ` 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) `

Exit:

` 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, "" )   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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