Compare with nan python

Проверить значения NaN в Python

В этом посте мы обсудим, как проверить NaN (не число) в Python.

1. Использование math.isnan() функция

Простое решение для проверки NaN в Python используется математическая функция math.isnan() . Он возвращается True если указанный параметр является NaN а также False в противном случае.

2. Использование numpy.isnan() функция

Чтобы проверить NaN с NumPy вы можете сделать так:

3. Использование pandas.isna() функция

Если вы используете модуль pandas, рассмотрите возможность использования pandas.isna() функция обнаружения NaN ценности.

4. Использование != оператор

Интересно, что благодаря спецификациям IEEE вы можете воспользоваться тем, что NaN никогда не равен самому себе.

Это все о проверке значений NaN в Python.

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How To Check NaN Value In Python

in this post, We’ll learn how to check NAN value in python. The NaN stands for ‘Not A Number’ which is a floating-point value that represents missing data.

You can determine in Python whether a single value is NaN or NOT. There are methods that use libraries (such as pandas, math, and numpy) and custom methods that do not use libraries.

NaN stands for Not A Number, is one of the usual ways to show a value that is missing from a set of data. It is a unique floating-point value and can only be converted to the float type.

In this article, I will explain four methods to deal with NaN in python.

• Check Variable Using Custom method
• Using math.isnan() Method
• Using numpy.nan() Method
• Using pd.isna() Method

What is NAN in Python

None is a data type that can be used to represent a null value or no value at all. None isn’t the same as 0 or False, nor is it the same as an empty string. In numerical arrays, missing values are NaN; in object arrays, they are None.

Using Custom Method

We can check the value is NaN or not in python using our own method. We’ll create a method and compare the variable to itself.

def isNaN(num): return num!= num data = float("nan") print(isNaN(data))

Using math.isnan()

The math.isnan() is a Python function that determines whether a value is NaN (Not a Number). If the provided value is a NaN, the isnan() function returns True . Otherwise, False is returned.

Let’s check a variable is NaN using python script.

import math a = 2 b = -8 c = float("nan") print(math.isnan(a)) print(math.isnan(b)) print(math.isnan(c))

Using Numpy nan()

The numpy.nan() method checks each element for NaN and returns a boolean array as a result.

Let’s check a NaN variable using NumPy method:

import numpy as np a = 2 b = -8 c = float("nan") print(np.nan(a)) print(np.nan(b)) print(np.nan(c))

Using Pandas nan()

The pd.isna() method checks each element for NaN and returns a boolean array as a result.

The below code is used to check a variable NAN using the pandas method:

import pandas as pd a = 2 b = -8 c = float("nan") print(pd.isna(a)) print(pd.isna(b)) print(pd.isna(c))

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Check for NaN Values in Python

1. Use the math.isnan() Function to Check for nan Values in Python
2. Use the numpy.isnan() Function to Check for nan Values in Python
3. Use the pandas.isna() Function to Check for nan Values in Python
4. Use the obj != obj to Check for nan Values in Python

The nan is a constant that indicates that the given value is not legal — Not a Number .

Note that nan and NULL are two different things. NULL value indicates something that doesn’t exist and is empty.

In Python, we deal with such values very frequently in different objects. So it is necessary to detect such constants.

In Python, we have the isnan() function, which can check for nan values. And this function is available in two modules- NumPy and math . The isna() function in the pandas module can also check for nan values.

Use the math.isnan() Function to Check for nan Values in Python

The isnan() function in the math library can be used to check for nan constants in float objects. It returns True for every such value encountered. For example:

import math import numpy as np  b = math.nan print(np.isnan(b)) 

Note that the math.nan constant represents a nan value.

Use the numpy.isnan() Function to Check for nan Values in Python

The numpy.isnan() function can check in different collections like lists, arrays, and more for nan values. It checks each element and returns an array with True wherever it encounters nan constants. For example:

import numpy as np  a = np.array([5, 6, np.NaN])  print(np.isnan(a)) 

np.NaN() constant represents also a nan value.

Use the pandas.isna() Function to Check for nan Values in Python

The isna() function in the pandas module can detect NULL or nan values. It returns True for all such values encountered. It can check for such values in a DataFrame or a Series object as well. For example,

import pandas as pd import numpy as np  ser = pd.Series([5, 6, np.NaN])  print(pd.isna(ser)) 

0 False 1 False 2 True dtype: bool 

Use the obj != obj to Check for nan Values in Python

For any object except nan , the expression obj == obj always returns True . For example,

print([] == []) print("1" == "1") print([1, 2, 3] == [1, 2, 3]) print(float("nan") == float("nan")) 

Therefore, we could use obj != obj to check if the value is nan . It is nan if the return value is True .

import math b = math.nan  def isNaN(num):  return num != num  print(isNaN(b)) 

This method however, might fail with lower versions of Python (

Manav is a IT Professional who has a lot of experience as a core developer in many live projects. He is an avid learner who enjoys learning new things and sharing his findings whenever possible.

Related Article — Python Math

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Check for NaN Values in Python

I am a professional Python Blogger and Content creator. I have published numerous articles and created courses over a period of time. Presently I am working as a full-time freelancer and I have experience in domains like Python, AWS, DevOps, and Networking.

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