Python 用 nan 替换 NumPy 整数数组中的零
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Replace the zeros in a NumPy integer array with nan
提问by Heinz
I wrote a python script below:
我在下面写了一个python脚本：
import numpy as np
arr = np.arange(6).reshape(2, 3)
arr[arr==0]=['nan']
print arr
But I got this error:
但我收到了这个错误：
Traceback (most recent call last):
File "C:\Users\Desktop\test.py", line 4, in <module>
arr[arr==0]=['nan']
ValueError: invalid literal for long() with base 10: 'nan'
[Finished in 0.2s with exit code 1]
How to replace zeros in a NumPy array with nan?
如何用nan替换NumPy数组中的零？
采纳答案by Alex Riley
np.nanhas type float: arrays containing it must also have this datatype (or the complexor objectdatatype) so you may need to cast arrbefore you try to assign this value.
np.nanhas type float：包含它的数组也必须具有此数据类型（或complexorobject数据类型），因此您可能需要arr在尝试分配此值之前进行强制转换。
The error arises because the string value 'nan'can't be converted to an integer type to match arr's type.
出现错误是因为字符串值'nan'无法转换为整数类型以匹配arr的类型。
>>> arr = arr.astype('float')
>>> arr[arr == 0] = 'nan' # or use np.nan
>>> arr
array([[ nan, 1., 2.],
[ 3., 4., 5.]])
