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# sciPy function stats.cumfreq () | python

` scipy.stats.cumfreq (a, numbins, defaultreallimits, weights) ` works using the histogram function and calculates the histogram of the cumulative frequency. It includes cumulative frequency values, width of each element, lower real limit, additional points

Parameters:
arr: [array_like] input array.
numbins: [int] number of bins to use for the histogram. [Default = 10]
defaultlimits: (lower, upper) range of the histogram.
weights: [array_like] weights for each array element.

Results:
- cumulative frequency binned values ​​
- width of each bin
- lower real limit
- extra points.

Code # 1:

 ` # cumulative 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.cumfreq (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: [4. 5. 5. 6.] Lower Limit: -3.33333333333 bin size: 8.66666666667 extra-points: 0 `

Code # 2:

 ` # cumulative 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.cumfreq (arr1, numbins ` ` = ` ` 4 ` `, ` `  weights = [. 1 ,. 2 ,. 1 ,. 3 , 1 , 6 ]) ``   print ( "cumfreqs:" , a) print ( "lowlim:" , b) print ( "binsize:" , c) print ( " extrapoints: " , d) `

Exit :

` Array element: [1, 3, 27, 2, 5, 13] cumfreqs: [1.6 7.6 7.6 7.7] lowlim: -3.33333333333 binsize: 8.66666666667 extrapoints: 0 `

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