Python Scipy stats.describe()用法及代碼示例

scipy.stats.describe(array, axis=0)計算沿數組指定軸傳遞的數組元素的描述性統計信息。

參數：
array:輸入數組或對象具有用於計算統計信息的元素。
axis:要沿其計算統計信息的軸。默認情況下，軸= 0。

返回：基於設置參數的數組元素的統計信息。

代碼1：

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

輸出：

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

代碼2：多維數據

# 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)

輸出：

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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