How can unique rows be extracted from a NumPy array?

Python
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#1

I have an issue with the code snippet provided below. The code seems to be functioning correctly, but I am struggling to comprehend its logic and visualize how it extracts unique rows from a NumPy array. Could someone please explain the process of extracting unique rows using this code? Alternatively, if there’s a simpler example code, could someone use that to explain the concept for me?

1 Like
#2

Yes, the code you attached may be difficult to understand. However, you can use the following alternate code to achieve the same thing using NumPy, and it is much easier to understand:

  • The code makes use of the np.unique() function on the input array. To find the unique rows, we specify axis=0.
  • The function returns an array containing only the unique rows of the input array, sorted in ascending order.
#3

Yes, you can use an easy alternative method using both NumPy and Pandas libraries to obtain unique rows from a NumPy array. For better comprehension, refer to the example code provided below:

  • In this example we start with importing the NumPy and Pandas libraries.
  • Create a NumPy array and convert it into a Pandas DataFrame.
  • Use the pd.drop_duplicates() function from Pandas to eliminate duplicate values.
  • Convert the resulting unique DataFrame back into a NumPy array using the df.to_numpy() method.
  • This straightforward process yields the desired final NumPy array.