float('nan') results in Nan (not a number). But how do I check for it? Should be very easy, but I cannot find it.
float('nan')导致Nan(不是数字)。但我该如何检查呢?应该很容易,但我找不到它。
13 个解决方案
#1
Checks if the float x is a NaN (not a number). NaNs are part of the IEEE 754 standards. Operation like but not limited to inf * 0, inf / inf or any operation involving a NaN, e.g. nan * 1, return a NaN.
检查浮点x是否为NaN(不是数字)。 NaN是IEEE 754标准的一部分。操作类似于但不限于inf * 0,inf / inf或涉及NaN的任何操作,例如, nan * 1,返回NaN。
New in version 2.6.
版本2.6中的新功能。
>>> import math
>>> x=float('nan')
>>> math.isnan(x)
True
>>>
#2
The usual way to test for a NaN is to see if it's equal to itself:
测试NaN的常用方法是查看它是否与自身相同:
def isNaN(num):
return num != num
#3
numpy.isnan(number) tells you if it's NaN or not in Python 2.5.
numpy.isnan(number)告诉你它是否在Python 2.5中是NaN。
#4
I actually just ran into this, but for me it was checking for nan, -inf, or inf. I just used
我实际上只是碰到了这个,但对我来说,它正在检查nan,-inf或inf。我刚刚用过
if float('-inf') < float(num) < float('inf'):
This is true for numbers, false for nan and both inf, and will raise an exception for things like strings or other types (which is probably a good thing). Also this does not require importing any libraries like math or numpy (numpy is so damn big it doubles the size of any compiled application).
这对于数字来说是正确的,对于nan和inf都是假的,并且会为字符串或其他类型(这可能是一件好事)引发异常。此外,这不需要导入任何库,如数学或numpy(numpy太大了,它的任何编译应用程序的大小翻倍)。
#5
or compare the number to itself. NaN is always != NaN, otherwise (e.g. if it is a number) the comparison should succeed.
或者将数字与自身进行比较。 NaN总是!= NaN,否则(例如,如果它是一个数字),比较应该成功。
#6
here is an answer working with:
这是一个答案:
- python non-unique NaN:
float('nan') - numpy unique NaN (singleton) :
np.nan - any other objects: string or whatever (does not raise exceptions if encountered)
python非唯一NaN:float('nan')
numpy unique NaN(singleton):np.nan
任何其他对象:字符串或其他任何东西(如遇到则不引发异常)
Here it is:
这里是:
import numpy as np
def is_nan(x):
return (x is np.nan or x != x)
And some examples:
还有一些例子:
values = [float('nan'), np.nan, 55, "string", lambda x : x]
for value in values:
print "{:<8} : {}".format(repr(value), is_nan(value))
Output:
nan : True
nan : True
55 : False
'string' : False
<function <lambda> at 0x000000000927BF28> : False
#7
Another method if you're stuck on <2.6, you don't have numpy, and you don't have IEEE 754 support:
另一种方法,如果你坚持<2.6,你没有numpy,并且你没有IEEE 754支持:
def isNaN(x):
return str(x) == str(1e400*0)
#8
With python < 2.6 I ended up with
随着python <2.6,我最终得到了
def isNaN(x):
return str(float(x)).lower() == 'nan'
This works for me with python 2.5.1 on a Solaris 5.9 box and with python 2.6.5 on Ubuntu 10
这适用于Solaris 5.9机器上的python 2.5.1和Ubuntu 10上的python 2.6.5
#9
Well I entered this post, because i've had some issues with the function:
好吧,我进入了这篇文章,因为我的功能存在一些问题:
math.isnan()
There are problem when you run this code:
运行此代码时出现问题:
a = "hello"
math.isnan(a)
It raises exception. My solution for that is to make another check:
它引发了例外。我的解决方案是再次检查:
def is_nan(x):
return isinstance(x, float) and math.isnan(x)
#10
I am receiving the data from a web-service that sends NaN as a string 'Nan'. But there could be other sorts of string in my data as well, so a simple float(value) could throw an exception. I used the following variant of the accepted answer:
我从Web服务接收数据,该服务将NaN作为字符串'Nan'发送。但是我的数据中可能还有其他类型的字符串,因此简单的float(value)可能会抛出异常。我使用了以下接受的答案变体:
def isnan(value):
try:
import math
return math.isnan(float(value))
except:
return False
Requirement:
isnan('hello') == False
isnan('NaN') == True
isnan(100) == False
isnan(float('nan')) = True
#11
All the methods to tell if the variable is NaN or None:
判断变量是NaN还是None的所有方法:
None type
In [1]: from numpy import math
In [2]: a = None
In [3]: not a
Out[3]: True
In [4]: len(a or ()) == 0
Out[4]: True
In [5]: a == None
Out[5]: True
In [6]: a is None
Out[6]: True
In [7]: a != a
Out[7]: False
In [9]: math.isnan(a)
Traceback (most recent call last):
File "<ipython-input-9-6d4d8c26d370>", line 1, in <module>
math.isnan(a)
TypeError: a float is required
In [10]: len(a) == 0
Traceback (most recent call last):
File "<ipython-input-10-65b72372873e>", line 1, in <module>
len(a) == 0
TypeError: object of type 'NoneType' has no len()
NaN type
In [11]: b = float('nan')
In [12]: b
Out[12]: nan
In [13]: not b
Out[13]: False
In [14]: b != b
Out[14]: True
In [15]: math.isnan(b)
Out[15]: True
#12
For nan of type float
对于纳米型浮子
>>> import pandas as pd
>>> value = float(nan)
>>> type(value)
>>> <class 'float'>
>>> pd.isnull(value)
True
>>>
>>> value = 'nan'
>>> type(value)
>>> <class 'str'>
>>> pd.isnull(value)
False
#13
for strings in panda take pd.isnull:
对于熊猫中的字符串,请参阅pd.isnull:
if not pd.isnull(atext):
for word in nltk.word_tokenize(atext):
the function as feature extraction for NLTK
该功能作为NLTK的特征提取
def act_features(atext):
features = {}
if not pd.isnull(atext):
for word in nltk.word_tokenize(atext):
if word not in default_stopwords:
features['cont({})'.format(word.lower())]=True
return features
#1
Checks if the float x is a NaN (not a number). NaNs are part of the IEEE 754 standards. Operation like but not limited to inf * 0, inf / inf or any operation involving a NaN, e.g. nan * 1, return a NaN.
检查浮点x是否为NaN(不是数字)。 NaN是IEEE 754标准的一部分。操作类似于但不限于inf * 0,inf / inf或涉及NaN的任何操作,例如, nan * 1,返回NaN。
New in version 2.6.
版本2.6中的新功能。
>>> import math
>>> x=float('nan')
>>> math.isnan(x)
True
>>>
#2
The usual way to test for a NaN is to see if it's equal to itself:
测试NaN的常用方法是查看它是否与自身相同:
def isNaN(num):
return num != num
#3
numpy.isnan(number) tells you if it's NaN or not in Python 2.5.
numpy.isnan(number)告诉你它是否在Python 2.5中是NaN。
#4
I actually just ran into this, but for me it was checking for nan, -inf, or inf. I just used
我实际上只是碰到了这个,但对我来说,它正在检查nan,-inf或inf。我刚刚用过
if float('-inf') < float(num) < float('inf'):
This is true for numbers, false for nan and both inf, and will raise an exception for things like strings or other types (which is probably a good thing). Also this does not require importing any libraries like math or numpy (numpy is so damn big it doubles the size of any compiled application).
这对于数字来说是正确的,对于nan和inf都是假的,并且会为字符串或其他类型(这可能是一件好事)引发异常。此外,这不需要导入任何库,如数学或numpy(numpy太大了,它的任何编译应用程序的大小翻倍)。
#5
or compare the number to itself. NaN is always != NaN, otherwise (e.g. if it is a number) the comparison should succeed.
或者将数字与自身进行比较。 NaN总是!= NaN,否则(例如,如果它是一个数字),比较应该成功。
#6
here is an answer working with:
这是一个答案:
- python non-unique NaN:
float('nan') - numpy unique NaN (singleton) :
np.nan - any other objects: string or whatever (does not raise exceptions if encountered)
python非唯一NaN:float('nan')
numpy unique NaN(singleton):np.nan
任何其他对象:字符串或其他任何东西(如遇到则不引发异常)
Here it is:
这里是:
import numpy as np
def is_nan(x):
return (x is np.nan or x != x)
And some examples:
还有一些例子:
values = [float('nan'), np.nan, 55, "string", lambda x : x]
for value in values:
print "{:<8} : {}".format(repr(value), is_nan(value))
Output:
nan : True
nan : True
55 : False
'string' : False
<function <lambda> at 0x000000000927BF28> : False
#7
Another method if you're stuck on <2.6, you don't have numpy, and you don't have IEEE 754 support:
另一种方法,如果你坚持<2.6,你没有numpy,并且你没有IEEE 754支持:
def isNaN(x):
return str(x) == str(1e400*0)
#8
With python < 2.6 I ended up with
随着python <2.6,我最终得到了
def isNaN(x):
return str(float(x)).lower() == 'nan'
This works for me with python 2.5.1 on a Solaris 5.9 box and with python 2.6.5 on Ubuntu 10
这适用于Solaris 5.9机器上的python 2.5.1和Ubuntu 10上的python 2.6.5
#9
Well I entered this post, because i've had some issues with the function:
好吧,我进入了这篇文章,因为我的功能存在一些问题:
math.isnan()
There are problem when you run this code:
运行此代码时出现问题:
a = "hello"
math.isnan(a)
It raises exception. My solution for that is to make another check:
它引发了例外。我的解决方案是再次检查:
def is_nan(x):
return isinstance(x, float) and math.isnan(x)
#10
I am receiving the data from a web-service that sends NaN as a string 'Nan'. But there could be other sorts of string in my data as well, so a simple float(value) could throw an exception. I used the following variant of the accepted answer:
我从Web服务接收数据,该服务将NaN作为字符串'Nan'发送。但是我的数据中可能还有其他类型的字符串,因此简单的float(value)可能会抛出异常。我使用了以下接受的答案变体:
def isnan(value):
try:
import math
return math.isnan(float(value))
except:
return False
Requirement:
isnan('hello') == False
isnan('NaN') == True
isnan(100) == False
isnan(float('nan')) = True
#11
All the methods to tell if the variable is NaN or None:
判断变量是NaN还是None的所有方法:
None type
In [1]: from numpy import math
In [2]: a = None
In [3]: not a
Out[3]: True
In [4]: len(a or ()) == 0
Out[4]: True
In [5]: a == None
Out[5]: True
In [6]: a is None
Out[6]: True
In [7]: a != a
Out[7]: False
In [9]: math.isnan(a)
Traceback (most recent call last):
File "<ipython-input-9-6d4d8c26d370>", line 1, in <module>
math.isnan(a)
TypeError: a float is required
In [10]: len(a) == 0
Traceback (most recent call last):
File "<ipython-input-10-65b72372873e>", line 1, in <module>
len(a) == 0
TypeError: object of type 'NoneType' has no len()
NaN type
In [11]: b = float('nan')
In [12]: b
Out[12]: nan
In [13]: not b
Out[13]: False
In [14]: b != b
Out[14]: True
In [15]: math.isnan(b)
Out[15]: True
#12
For nan of type float
对于纳米型浮子
>>> import pandas as pd
>>> value = float(nan)
>>> type(value)
>>> <class 'float'>
>>> pd.isnull(value)
True
>>>
>>> value = 'nan'
>>> type(value)
>>> <class 'str'>
>>> pd.isnull(value)
False
#13
for strings in panda take pd.isnull:
对于熊猫中的字符串,请参阅pd.isnull:
if not pd.isnull(atext):
for word in nltk.word_tokenize(atext):
the function as feature extraction for NLTK
该功能作为NLTK的特征提取
def act_features(atext):
features = {}
if not pd.isnull(atext):
for word in nltk.word_tokenize(atext):
if word not in default_stopwords:
features['cont({})'.format(word.lower())]=True
return features