- Trending Categories
- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- MS Excel
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP
- Physics
- Chemistry
- Biology
- Mathematics
- English
- Economics
- Psychology
- Social Studies
- Fashion Studies
- Legal Studies

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

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

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...

", 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 of the Array −

print("

Number of elements...

", 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("

Result (trunc)...

",np.trunc(arr, arrRes))

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

print("

Result...

",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...

", 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) # 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("

Result (trunc)...

",np.trunc(arr, arrRes)) # Check the value of the new array where our result is stored print("

Result...

",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.]

- Related Articles
- Return the floor of the array elements and store the result in a new location in Numpy
- Return the ceil of the array elements and store the result in a new location in Numpy
- Return the next floating-point value and store the result in a new location in Numpy
- Return the truncated value of the array elements in Numpy
- Test Numpy array values for infiniteness and store the result in a new location
- Test array values for finiteness and store the result in a new location in Numpy
- Test array values for NaT and store the result in a new location in Numpy
- Test array values for NaN and store the result in a new location in Numpy
- Return the truncated value of a specific array element in Numpy
- Compute the absolute values element-wise and store the result in a new location in Numpy
- Return the truncated value of the inputs in Numpy
- Return element-wise True where signbit is set (less than zero) and store the result in a new location in Numpy
- Return the ceil value of the array elements in Numpy
- Create a new array from the masked array and return a new reference in Numpy
- Return a new Three-Dimensional array without initializing entries and store the data in column-major order in Numpy