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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.]