数据挖掘工具numpy(五)Numpy数据统计运算

一,numpy中常用的统计函数

import numpy as np

a = np.arange(20).reshape(4,5).astype(float)
a[2,3] = np.nan
print(a)

# 按行求和
# print(a.sum(axis=1))

# 按行求均值
# print(a.mean(axis=1))

# 按行求中值
# print(np.median(a,axis=1))

# 按行求最大值
# print(a.max(axis=1))

# 按行求最小值
# print(a.min(axis=1))

# 按行求极值的差值
# print(np.ptp(a,axis=1))

# 按行求标准差
# print(a.std(axis=1))

# -------------output---------------------
[[ 0.  1.  2.  3.  4.]
 [ 5.  6.  7.  8.  9.]
 [10. 11. 12. nan 14.]
 [15. 16. 17. 18. 19.]]

二,numpy获取最大值最小值的索引位置

import numpy as np
temp = np.arange(30).reshape(5,6)
a = np.argmax(temp,axis=1)
b = np.argmin(temp,axis=1)
print(temp,a,b)

# -------------output---------------------
[[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]
 [12 13 14 15 16 17]
 [18 19 20 21 22 23]
 [24 25 26 27 28 29]] [5 5 5 5 5] [0 0 0 0 0]

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转载自blog.csdn.net/TFATS/article/details/106274675
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