numpy.trunc () in Python

numpy.trunc (x [, out]) = ufunc & # 39; trunc & # 39;): This math function returns the truncated value of array elements. The scalar truncation x is the closest integer i that is closer to zero than x. It simply means that this function discards the fractional part of the signed number x.

Parameters:

a: [array_like] Input array

Return:
The truncated of each element, with float data-type

Code # 1: Work

# Python program explaining
# trunc () function

 

import numpy as np

 

in_array = [. 5 , 1.5 , 2.5 , 3.5 , 4.5 , 10.1 ]

print ( "Input array:" , in_array)

 

truncoff_values ​​ = np.trunc (in_array)

print ( "Rounded values:" , truncoff_values)

 

  

in_array = [. 53 , 1.54 ,. 71 ]

print ( "Input array:" , in_array)

 

truncoff_values ​​ = np.trunc (in_array)

print ( "Rounded values:" , truncoff_values)

 

in_array = [. 5538 , 1.33354 ,. 71445 ]

print ( " Input array: " , in_array)

  

truncoff_values ​​ = np.trunc (in_array)

print ( "Rounded values:" , truncoff_values)

Output:

 Input array: [0.5, 1.5, 2.5, 3.5, 4.5, 10.1] Rounded values: [0. 1. 2. 3. 4. 10.] Input array: [0.53, 1.54, 0.71] Rounded values: [0. 1. 0.] Input array: [0.5538, 1.33354, 0.71445] Rounded values: [0. 1. 0.] 

Code 2: Work

# Python program explaining
# trunc () function

 

import numpy as np

  

in_array = [ 1.67 , 4.5 , 7 , 9 , 12 ]

print ( "Input array:" , in_array)

 

truncoff_values ​​ = np.trunc (in_array)

print ( "Rounded values:" , truncoff_v alues)

 

 

in_array = [ 133.000 , 344.54 , 437.56 , 44.9 , 1.2 ]

print ( "Input array:" , in_array)

 

truncoff_values ​​ = np. trunc (in_array)

print ( " Rounded values ​​upto 2: " , truncoff _values)

Output:

 Input array: [1.67, 4.5, 7, 9, 12] Rounded values: [1. 4. 7. 9. 12.] Input array: [133.0, 344.54, 437.56, 44.9, 1.2] Rounded values ​​upto 2: [133. 344. 437. 44. 1.] 

Links: https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.trunc.html#numpy.trunc
,





Get Solution for free from DataCamp guru