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The process to obtain the complement of an array shaped (x,2) by removing rows from an array shaped (y,2) is as follows:

1. Create a new array of shape (y-x,2) to hold the complement of the original array.
2. Iterate over each row in the original array.
3. Check if the row is present in the array shaped (x,2).
4. If the row is not present in the original array, add it to the new complement array.
5. Return the new complement array.

Here is an example code implementation of the above process:

import numpy as np

def array_complement(original_array, rows_to_remove):
    # Find the complement array shape
    complement_shape = (original_array.shape[0] - rows_to_remove.shape[0], 2)
    # Create the complement array
    complement_array = np.zeros(complement_shape)
    # Iterate over each row in the original array
    for i in range(original_array.shape[0]):
        row = original_array[i,:]
        # Check if the row is in the rows to remove
        if np.any(np.all(rows_to_remove == row, axis=1)):
            continue
        # Add the row to the complement array
        complement_array[i,:] = row
    # Remove any rows with zeros (empty rows)
    complement_array = complement_array[~np.all(complement_array == 0, axis=1)]
    return complement_array

This function takes the original array and an array of rows to remove as inputs and returns the complement of the original array. Note that the row comparison is done using the np.all function with the axis=1 argument to compare all elements in the row. The resulting complement array is then cleaned up by removing any rows with zeros (empty rows).