Find unique rows in a NumPy array
In this article we will discuss how to find unique rows in a NumPy array. To find unique rows in a NumPy array we are using numpy.unique() function of NumPy library.
Syntax : numpy.unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None)
Now, let’s see an example:
Example 1:
Python3
# import libraryimport numpy as np # Create a 2D numpy arrayarr2D = np.array([[11, 11, 12, 11], [13, 11, 12, 11], [16, 11, 12, 11], [11, 11, 12, 11]]) print('Original Array :' , arr2D, sep = '\n') # Get unique rows from# complete 2D-array by # passing axis = 0 in # unique function along# with 2D-arrayuniqueRows = np.unique(arr2D, axis = 0) # print the output resultprint('Unique Rows:', uniqueRows, sep = '\n') |
Output:
Original Array : [[11 11 12 11] [13 11 12 11] [16 11 12 11] [11 11 12 11]] Unique Rows: [[11 11 12 11] [13 11 12 11] [16 11 12 11]]
Example 2:
Python3
# import libraryimport numpy as np # create 2d numpy arrayarray = np.array([[1, 2, 3, 4], [3, 2, 4, 1], [6, 8, 1, 2]]) print("Original array: \n", array) # Get unique rows from# complete 2D-array by # passing axis = 0 in # unique function along# with 2D-arrayuniqueRows = np.unique(array, axis = 0) # print the output resultprint('Unique Rows :', uniqueRows, sep = '\n') |
Output:
Original array: [[1 2 3 4] [3 2 4 1] [6 8 1 2]] Unique Rows : [[1 2 3 4] [3 2 4 1] [6 8 1 2]]
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