sciPy stats.cumfreq()函数| Python

scipy.stats.cumfreq(a, numbins, defaultreallimits, weights)使用 histogram函数并计算累积频率直方图。它包括累积频率分箱值、每个分箱的宽度、实际下限、加分。

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. 

代码#1：

Python3

# cumulative 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.cumfreq(arr1, numbins = 4)
   
print ("cumulative frequency : ", a)
print ("Lower Limit : ", b)
print ("bin size : ", c)
print ("extra-points : ", d)

输出：

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

代码#2：

Python3

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

输出：

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