How do you check if a value is infinity in python?

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In this article, we will check whether the given value is NaN or Infinity. This can be done using the math module. Let’s see how to check each value in detail.

Check if the value is NaN

NaN Stands for “Not a Number” and it is a numeric datatype used as a proxy for values that are either mathematically undefined or cannot be represented.  There are various examples of them like-

1. 0/0 is undefined and NaN is used for representing it.
2. Sqrt(-ve number) cannot be stored as a real number so NaN is used for representing it.
3. Log(-ve number) cannot be stored as a real number so NaN is used for representing it.
4. Inverse sin or Inverse cos of a number < -1 or number > 1 is also NaN.
5. 0 * inf also leads to NaN.

Since NaN is type in itself It is used to assign variables whose values are not yet calculated.

Method 1: To check for NaN we can use math.isnan() function as NaN cannot be tested using == operator.  

Python3

import math

x = math.nan

print(f"x contains {x}")

if(math.isnan(x)):

    print("x == nan")

else:

    print("x != nan")

Output

x contains nan
x == nan

Method 2: NaN is not equal to NaN and therefore we can exploit this property to check for NaN. The following code demonstrates it.

Python3

import math

def isNan(number):

    return number != number

x = math.nan

print(isNan(x))

Check if the Value is Infinite

Method 1: To check for infinite in python the function used is math.isinf() which only checks for infinite. To distinguish between positive and negative infinite we can add more logic that checks if the number is greater than 0 or less than 0. The code shows this in action.

Python3

import math

def check(x):

    if(math.isinf(x) and x > 0):

        print("x is Positive inf")

    elif(math.isinf(x) and x < 0):

        print("x is negative inf")

    else:

        print("x is not inf")

number = math.inf

check(number)

number = -math.inf

check(number)

Output

x is Positive inf
x is negative inf

Method 2: Numpy also exposes two APIs to check for positive and negative infinite. which are np.isneginf()and np.isposinf(). 

Python3

import numpy as np

print(np.isneginf([np.inf, 0, -np.inf]))

print(np.isposinf([np.inf, 0, -np.inf]))

Output

[False False  True]
[ True False False]

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Prerequisites: Pandas

There are various cases where a data frame can contain infinity as value. This article discusses how we can keep track of infinities in our data frame. 

Approach

• Import module
• Create a data frame, for this article, it is done using a dictionary. For including infinity in the data, import NumPy module, and use np.inf for positive infinity and -np.inf for negative infinity.
• Use appropriate methods from the ones mentioned below as per your requirement.

Method 1: Use DataFrame.isinf() function to check whether the dataframe contains infinity or not. It returns boolean value. If it contains any infinity, it will return True. Else, it will return False. 

Syntax:

isinf(array [, out])

Using this method itself, we can derive a lot more information regarding the presence of infinity in our dataframe:

• Checking for infinity as values
• Counting the number of infinity values
• Retrieve column name with infinity as value(s)
• Retrieve row index/indices with infinity as value(s)

Example:

Python3

import pandas as pd

import numpy as np

data = {'Student ID': [10, 11, 12, 13, 14], 

        'Age': [23, 22, 24, 22, 25],

        'Weight': [66, 72, np.inf, 68, -np.inf]}

df = pd.DataFrame(data)

display(df)

print()

print("checking for infinity")

ds = df.isin([np.inf, -np.inf])

print(ds)

print()

print("printing the count of infinity values")

count = np.isinf(df).values.sum()

print("It contains " + str(count) + " infinite values")

c = np.isinf(df['Weight']).values.sum()

print("It contains " + str(c) + " infinite values")

print()

print("printing column name where infinity is present")

col_name = df.columns.to_series()[np.isinf(df).any()]

print(col_name)

print()

print("printing row index with infinity ")

r = df.index[np.isinf(df).any(1)]

print(r)

Output:

Method 2: Usenp.isfinite(dataframe_name)to check the presence of infinite value(s). It returns boolean value. It will return False for infinite values and it will return True for finite values.

Syntax:

isfinite(array [, out])

Example: 

Python3

import pandas as pd

import numpy as np

data = {'Student ID': [10, 11, 12, 13, 14], 'Age': [

    23, 22, 24, 22, 25], 'Weight': [66, 72, np.inf, 68, -np.inf]}

df = pd.DataFrame(data)

d = np.isfinite(df)

display(d)

Output: