Create np.array from pandas dataframe which has a column holding values of the array's indices and another column holding the value at each index?

I have a pandas DataFrame that looks like the following:

All the x-values are unique. The x-values also tell the index of the corresponding number y in a numpy array.

I have an np.zeros array that has a shape of (6,).

How can I efficiently modify the np.zeros array such that it will turn into
np.array([0, 0, 4, 1, 0, 9)? Notice how at index 2, the value is 4 because when x = 2, y = 4 according to the DataFrame.

>Solution :

Try:

arr = np.zeros(6)
arr[df["x"]] = df["y"]

print(arr)

Prints:

[0. 0. 4. 1. 0. 9.]