# Return the truncated value of the array elements and store the result in a new location in Numpy

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To return the trunc of the array elements, element-wise, use the numpy.trunc() method in Python Numpy. The new location where we will store the result is a new array.

The function returns the truncated value of each element in x. This is a scalar if x is a scalar. The truncated value of the scalar x is the nearest integer i which is closer to zero than x is. In short, the fractional part of the signed number x is discarded.

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.

## Steps

At first, import the required library −

import numpy as np

Create an array using the array() method −

arr = np.array([48.7, 100.8, 50.7, 67.9, 34.5, 69.8])


Display the array −

print("Array...\n", arr)

Get the type of the array −

print("\nOur Array type...\n", arr.dtype)


Get the dimensions of the Array: −

print("\nOur Array Dimensions...\n", arr.ndim)

Get the number of elements of the Array −

print("\nNumber of elements...\n", arr.size)


Create another array with the same shape to store the result −

arrRes = np.array([5.2, 10.1, 15.7, 20.2, 25.9, 45.9])

To return the trunc of the array elements, element-wise, use the numpy.trunc() method in Python Numpy. The new location where we will store the result is arrRes −

print("\nResult (trunc)...\n",np.trunc(arr, arrRes))


Check the value of the new array where our result is stored −

print("\nResult...\n",arrRes)

## Example

import numpy as np

# Create an array using the array() method
arr = np.array([48.7, 100.8, 50.7, 67.9, 34.5, 69.8])

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

# Get the type of the array
print("\nOur Array type...\n", arr.dtype)

# Get the dimensions of the Array
print("\nOur Array Dimensions...\n", arr.ndim)

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

# Create another array with the same shape to store the result
arrRes = np.array([5.2, 10.1, 15.7, 20.2, 25.9, 45.9])

# To return the trunc of the array elements, element-wise, use the numpy.trunc() method in Python Numpy
# The new location where we will store the result is arrRes
print("\nResult (trunc)...\n",np.trunc(arr, arrRes))

# Check the value of the new array where our result is stored
print("\nResult...\n",arrRes)

## Output

Array...
[ 48.7 100.8 50.7 67.9 34.5 69.8]

Our Array type...
float64

Our Array Dimensions...
1

Number of elements...
6

Result (trunc)...
[ 48. 100. 50. 67. 34. 69.]

Result...
[ 48. 100. 50. 67. 34. 69.]