How to check nan python

5 Methods to Check For NaN Values in Python

Here are the five ways to check for a NaN values in Python:

1. Using math.isnan(): It checks whether a value is NaN (Not a Number).
2. Using numpy.isnan(): It checks for NaN and returns the result as a boolean array.
3. Using pandas.isna(): It detects missing values.
4. Using custom function
5. By checking the range

Method 1: Using math.isnan()

The math.isnan() is a built-in Python method that checks whether a value is NaN (Not a Number). The isnan() method returns True if the specified value is a NaN. Otherwise, it returns False.

Syntax

Parameter

num: It is a required parameter which is the value to check.

Example

import math test_data_a = 21 test_data_b = -19 test_data_c = float("nan") print(math.isnan(test_data_a)) print(math.isnan(test_data_b)) print(math.isnan(test_data_c))

Method 2: Using the numpy.isnan() method

The numpy.isnan() method tests the element-wise for NaN and returns the result as a boolean array.

import numpy as np test_data_a = 21 test_data_b = -19 test_data_c = float("nan") print(np.isnan(test_data_a)) print(np.isnan(test_data_b)) print(np.isnan(test_data_c))

And the np.isnan() function returns True if it finds the NaN value.

Method 3: Using the pd.na() function

The pd.isna() is a Pandas function that can check if the value is NaN.

import pandas as pd test_data_a = 21 test_data_b = -19 test_data_c = float("nan") print(pd.isna(test_data_a)) print(pd.isna(test_data_b)) print(pd.isna(test_data_c))

And the pd.na() function returns True if it finds the NaN value.

Method 4: By Creating a function

The most common way to check for NaN values in Python is to check if the variable is equal to itself. If it is not, then it must be NaN value. So let’s create a function that checks the value to itself.

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

We cannot compare the NaN value against itself. If it returns False, both values are the same, and the two NaNs are not the same. That is why from the above output, we can conclude that it is the NaN value.

Method 5: Checking the range

Another property of NaN that can be used to check for NaN is the range. All floating point values fall within the range of minus infinity to infinity.

However, NaN values do not come within this range. Hence, NaN can be identified if the value does not fall within the range from minus infinity to infinity.

def isNaN(num): if float('-inf') < float(num) < float('inf'): return False else: return True data = float("nan") print(isNaN(data))

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5 Methods to Check for NaN values in in Python

How to check if a single value is NaN in python. There are approaches are using libraries (pandas, math and numpy) and without using libraries.

NaN stands for Not A Number and is one of the common ways to represent the missing value in the data. It is a special floating-point value and cannot be converted to any other type than float.

NaN value is one of the major problems in Data Analysis. It is very essential to deal with NaN in order to get the desired results.

Finding and dealing with NaN within an array, series or dataframe is easy. However, identifying a stand alone NaN value is tricky. In this article I explain five methods to deal with NaN in python. The first three methods involves in-built functions from libraries. The last two relies on properties of NaN for finding NaN values.

Method 1: Using Pandas Library

isna() in pandas library can be used to check if the value is null/NaN. It will return True if the value is NaN/null.

import pandas as pd
x = float("nan")
print(f"It's pd.isna : ")OutputIt's pd.isna : True

Method 2: Using Numpy Library

isnan() in numpy library can be used to check if the value is null/NaN. It is similar to isna() in pandas.

import numpy as np
x = float("nan")
print(f"It's np.isnan : ")OutputIt's np.isnan : True

Method 3: Using math library

Math library provides has built-in mathematical functions. The library is applicable to all real numbers. cmath library can be used if dealing with complex numbers.
Math library has built in function isnan() to check null/NaN values.

import math
x = float("nan")
print(f"It's math.isnan : ")OutputIt's math.isnan : True

Method 4: Comparing with itself

When I started my career working with big IT company, I had to undergo a training for the first month. The trainer, when introducing the concept of NaN values mentioned that…

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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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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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