As we know Numpy is a general-purpose array-processing package that provides a high-performance multidimensional array object, and tools for working with these arrays. Let’s discuss how can we reverse a Numpy array.
Using flip() function to Reverse a Numpy array
The numpy.flip() function reverses the order of array elements along the specified axis, preserving the shape of the array.
import numpy as np
# initialising numpy array ini_array = np.array([ 1 , 2 , 3 , 6 , 4 , 5 ])
# using shortcut method to reverse res = np.flip(ini_array)
# printing result print ( "final array" , str (res))
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Output:
final array [5 4 6 3 2 1]
Using the list slicing method to reverse a Numpy array
This method makes a copy of the list instead of sorting it in order. To accommodate all of the current components, making a clone requires additional room. More RAM is used up in this way. Here, we’re utilizing Python’s slicing method to invert our list.
import numpy as np
# initialising numpy array ini_array = np.array([ 1 , 2 , 3 , 6 , 4 , 5 ])
# printing initial ini_array print ( "initial array" , str (ini_array))
# printing type of ini_array print ( "type of ini_array" , type (ini_array))
# using shortcut method to reverse res = ini_array[:: - 1 ]
# printing result print ( "final array" , str (res))
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Output:
initial array [1 2 3 6 4 5] type of ini_array <class 'numpy.ndarray'> final array [5 4 6 3 2 1]
Using flipud function to Reverse a Numpy array
The numpy.flipud() function flips the array(entries in each column) in up-down direction, shape preserved.
import numpy as np
# initialising numpy array ini_array = np.array([ 1 , 2 , 3 , 6 , 4 , 5 ])
# printing initial ini_array print ( "initial array" , str (ini_array))
# printing type of ini_array print ( "type of ini_array" , type (ini_array))
# using flipud method to reverse res = np.flipud(ini_array)
# printing result print ( "final array" , str (res))
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Output:
initial array [1 2 3 6 4 5] type of ini_array <class 'numpy.ndarray'> final array [5 4 6 3 2 1]