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Python Scipy stats.describe()用法及代码示例


scipy.stats.describe(array, axis=0)计算沿数组指定轴传递的数组元素的描述性统计信息。

参数:
array:输入数组或对象具有用于计算统计信息的元素。
axis:要沿其计算统计信息的轴。默认情况下,轴= 0。

返回:基于设置参数的数组元素的统计信息。


代码1:

# FInding statistics of data 
  
from scipy import stats 
  
arr1 = [9, 3, 27]  
   
desc = stats.describe(arr1) 
  
print("No. of observations is:\n", desc) 
输出:

No. of observations is:
DescribeResult(nobs=3, minmax=(3, 27), mean=13.0, variance=156.0, skewness=0.5280049792181878, kurtosis=-1.5)


代码2:多维数据

# FInding statistics of data 
  
from scipy import stats 
  
arr1 = [[1, 3, 27],  
        [3, 4, 6],  
        [7, 6, 3],  
        [3, 6, 8]]  
   
desc = stats.describe(arr1, axis = 0) 
  
  
print("No. of observations at axis = 0:\n\n", desc) 
  
  
print("\n\nNo. of observations at axis = 1:\n\n", desc)
输出:

No. of observations at axis = 0:

DescribeResult(nobs=4, minmax=(array([1, 3, 3]), array([ 7, 6, 27])), mean=array([ 3.5 , 4.75, 11. ]), variance=array([ 6.33333333, 2.25 , 118. ]), skewness=array([ 0.65202366, -0.21383343, 1.03055786]), kurtosis=array([-0.90304709, -1.72016461, -0.75485971]))

No. of observations at axis = 1:

DescribeResult(nobs=4, minmax=(array([1, 3, 3]), array([ 7, 6, 27])), mean=array([ 3.5 , 4.75, 11. ]), variance=array([ 6.33333333, 2.25 , 118. ]), skewness=array([ 0.65202366, -0.21383343, 1.03055786]), kurtosis=array([-0.90304709, -1.72016461, -0.75485971]))



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注:本文由纯净天空筛选整理自vishal3096大神的英文原创作品 sciPy stats.describe() function | Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。