How to fill null values in a column conditionally in pandas

Question

I have the following dataframe :

time                    label
2020-03-03 08:35:03.585 ok
2020-03-03 08:05:01.288 ok
2020-03-03 11:50:01.944 faulty
2020-03-03 08:45:04.540 ok
2020-03-12 10:30:02.227 None
2020-03-12 11:10:02.385 None
2020-03-05 11:15:03.526 None
2020-03-10 10:55:01.084 faulty
2020-03-05 11:35:04.563 None

I would like to only fill null values in label column where time is less than 2020-03-10 .

i tried

 df[df["label"].isna()] =np.where(df['triggerTs'] < '2020-03-10', 'ok' ,'no label')

But apparently it is not the correct way to do it because returns this error

ValueError: Must have equal len keys and value when setting with an iterable

Answer 1

In your solution is necessary filter missing rows for both sides for same length of assigned array to label column:

m = df["label"].isna()
df.loc[m, 'label'] = np.where(df.loc[m, 'time'] < '2020-03-10', 'ok' ,'no label')
print (df)
                     time     label
0 2020-03-03 08:35:03.585        ok
1 2020-03-03 08:05:01.288        ok
2 2020-03-03 11:50:01.944    faulty
3 2020-03-03 08:45:04.540        ok
4 2020-03-12 10:30:02.227  no label
5 2020-03-12 11:10:02.385  no label
6 2020-03-05 11:15:03.526        ok
7 2020-03-10 10:55:01.084    faulty
8 2020-03-05 11:35:04.563        ok