sciPy stats . scoratpercentile()函数| Python
原文:https://www . geeksforgeeks . org/scipy-stats-scoratpercentile-function-python/
**scipy.stats.scoreatpercentile(a, score, kind='rank')**函数帮助我们计算输入数组给定百分位的得分。
百分位数= 50 的分数是中位数。如果期望的分位数位于两个数据点之间，我们根据插值的值在它们之间进行插值。
参数: arr:【array _ like】输入数组。 per:【array _ like】我们需要分数的百分位数。 极限:【元组】计算百分位数的下限和上限。 轴:【int】轴，我们需要沿着这个轴计算分数。
结果:相对于数组元素的百分位得分。
代码#1:
# scoreatpercentile
from scipy import stats
import numpy as np
# 1D array
arr = [20, 2, 7, 1, 7, 7, 34, 3]
print("arr : ", arr)
print ("\nScore at 50th percentile : ",
stats.scoreatpercentile(arr, 50))
print ("\nScore at 90th percentile : ",
stats.scoreatpercentile(arr, 90))
print ("\nScore at 10th percentile : ",
stats.scoreatpercentile(arr, 10))
print ("\nScore at 100th percentile : ",
stats.scoreatpercentile(arr, 100))
print ("\nScore at 30th percentile : ",
stats.scoreatpercentile(arr, 30))
Output:
arr : [20, 2, 7, 1, 7, 7, 34, 3]
Score at 50th percentile : 7.0
Score at 90th percentile : 24.2
Score at 10th percentile : 1.7
Score at 100th percentile : 34.0
Score at 30th percentile : 3.4
代码#2:
# scoreatpercentile
from scipy import stats
import numpy as np
arr = [[14, 17, 12, 33, 44],
[15, 6, 27, 8, 19],
[23, 2, 54, 1, 4, ]]
print("arr : ", arr)
print ("\nScore at 50th percentile : ",
stats.scoreatpercentile(arr, 50))
print ("\nScore at 50th percentile : ",
stats.scoreatpercentile(arr, 50, axis = 1))
print ("\nScore at 50th percentile : ",
stats.scoreatpercentile(arr, 50, axis = 0))
Output:
arr : [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4]]
Score at 50th percentile : 15.0
Score at 50th percentile : [ 17\. 15\. 4.]
Score at 50th percentile : [ 15\. 6\. 27\. 8\. 19.]
版权属于：月萌API www.moonapi.com，转载请注明出处
