## Representing missing and infinite values

Missing values can be represented using np.nan

Infinite values can be represented using np.inf

Example 1

np.nan

Example 2

np.inf

## Checking whether an array contains and nan value or an infinite value

To check if nan value is present in the array we will use isnan() function

isnan() function returns True if an array contains nan or it will return False

To check if an infinite value is present in an array we will use isinf() function

isinf() function returns True if an array contains infinite or it will return False

Example 3

isnan()

Example 4

isinf()

## Comparison operators on arrays

We can compare the arrays by using comparison operators like (==,<,>,>=,<=)

Comparison operators compare the arrays element wise

### == ( equal )

To compare whether the elements are equal in the arrays

Example 5

### != ( not equal )

To compare whether the elements are not equal in the arrays

Example 6

### > ( greater than )

To compare whether the elements are greater than in the arrays

Example 7

### < ( lesser than )

To compare whether the elements are lesser than in the arrays

Example 8

### >= ( greater than or equal to)

To compare whether the elements are greater than or equal to in the arrays

Example 9

### <= ( lesser than or equal to)

To compare whether the elements are lesser than or equal to in the arrays

Example 10

### array-wise comparisons

In array - wise comparisons we compare whether the arrays are same or not

For array-wise comparisons we will use array_equal(array1,array2) function

Example 11

## Logical Operations

We can also apply logical operation on arrays

logical_or(array1,array2) and logical_and(array1,array2) functions are used to perform logical operations on arrays

### logical_or(array1,array2)

It will compare two arrays elementwise and returns true if any one of the element is not a 0 and returns false if both the elements are 0

Example 12

### logical_and(array1,array2)

It will compare two arrays elementwise and returns true if both the element is not a 0 and returns false if both the elements are 0

Example 13

## Extras:-

### np.all(array)

np.all() function returns True if all the elements in an arrays is not 0's and returns False if any element in an array is 0's

### np.any(array)

np.any() function returns True if any elements in an arrays is not 0's and returns False if all the elements in an array is 0's