# Return the fractional and integral parts of array values in Numpy

To return the fractional and integral parts of array values, use the numpy.modf() method in Python Numpy. The fractional and integral parts are negative if the given number is negative.

The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

The condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.

## Steps

At first, import the required library −

import numpy as np

Create an array −

arr = np.array([1.7, 20.4, 100.8, 50, -10.5, np.nan, np.inf])


Display the arrays −

print("Array...", arr)

Get the type of the arrays −

print("Our Array type...", arr.dtype)


Get the dimensions of the Arrays −

print("Our Array Dimensions...", arr.ndim)

Get the number of elements in the Array −

print("Number of elements...", arr.size)


To return the fractional and integral parts of array values, use the numpy.modf() method in Python Numpy −

print("Result...",np.modf(arr))

## Example

import numpy as np

# Create an array
arr = np.array([1.7, 20.4, 100.8, 50, -10.5, np.nan, np.inf])

# Display the array
print("Array...", arr)

# Get the type of the array
print("Our Array type...", arr.dtype)

# Get the dimensions of the Array
print("Our Array Dimensions...", arr.ndim)

# Get the number of elements in the Array
print("Number of elements...", arr.size)

# To return the fractional and integral parts of array values, use the numpy.modf() method in Python Numpy
print("Result...",np.modf(arr))

## Output

Array...
[ 1.7 20.4 100.8 50. -10.5 nan inf]

Our Array type...
float64

Our Array Dimensions...
1

Number of elements...
7

Result...
(array([ 0.7, 0.4, 0.8, 0. , -0.5, nan, 0. ]), array([ 1., 20., 100., 50., -10., nan, inf]))