Python numpy array add / update / delete row on value from other array

Question

I have a numpy array and depending on the value from another array, I would like to either update the value of the row, or delete it, or add one.

Example:

I have arr, the one with all values and to keep updated with value from new_arr. If a value in the first column of new_arr exists in arr, then the second column of arr is updated. If the value does no exist, then add a new row. If the second column in new_arr == 0, then delete the row in arr with the matching first column.

arr = np.array([[1, 10],
                [2, 15],
                [3,  5],
                [4, 10]])

new_arr = np.array([[2, 20], # 2 exists in arr and 20 > 0 --> update in arr
                    [5, 20], # 5 does not exists in arr --> add row in arr
                    [1, 0]]) # 1 exists in arr but col 2 == 0--> delete row in arr

Then I would like to obtain:

arr = np.array([[2, 20],
                [3,  5],
                [4, 10],
                [5, 20]])

Observe that arr is ordered by the first column. Also arr has a maximum lenght of 1000 rows.

Any simple and fast method please?

Initially arr and new_arr are lists. I've turned them into numpy arrays. However, as I do not do any strong calculation with arr, most likely it would be faster to keep it as a list.

Answer 1

Keeping the input arrays as numpy constructs, here's how I would do it.

def process_arrays(np1, np2):
    np1d = dict((np1[x][0], np1[x][1]) for x in range(len(np1)))
    np2d = dict((np2[x][0], np2[x][1]) for x in range(len(np2)))
    for ky2 in np2d.keys():
        if ky2 in np1d.keys():
            if np2d[ky2] == 0:
                del np1d[ky2]
            else:
                np1d[ky2] = np2d[ky2]
        else:
            np1d[ky2] = np2d[ky2]
    return np.array(np1d)   

Given you input executing:

process_arrays(arr, newArr)  

Yields:

array({2: 20, 3: 5, 4: 10, 5: 20}, dtype=object)