Propagate/forward-fill nan values in numpy array-CodePudding

I need to forward-fill nan values in a numpy array along the columns (axis=0). I am looking for a pure numpy solution that yields the same result as pd.fillna(method="ffill").

import numpy as np
import pandas as pd

arr = np.array(
    [
        [5, np.nan, 3],
        [4, np.nan, np.nan],
        [6, 2, np.nan],
        [2, np.nan, 6],
    ]
)

expected = pd.DataFrame(arr).fillna(method="ffill", axis=0)  # I need this line in pure numpy

print(f"Original array:\n {arr}\n")
print(f"Expected array:\n {expected.values}\n")

Original array:
 [[ 5. nan  3.]
 [ 4. nan nan]
 [ 6.  2. nan]
 [ 2. nan  6.]]

Expected array:
 [[ 5. nan  3.]
 [ 4. nan  3.]
 [ 6.  2.  3.]
 [ 2.  2.  6.]]

CodePudding user response：

Bottleneck push function is a good option to forward fill. It's normally used internally in packages like Xarray.

from bottleneck import push
push(arr, axis=0)

CodePudding user response：

No inbuilt function in numpy to do this. Below simple code will generate desired result using numpy array only.

row,col = arr.shape
mask = np.isnan(arr)
for i in range(1,row):
    for j in range(col):
        if mask[i][j]:
            arr[i][j] =arr[i-1][j]