[Solved] df.loc: write data in certain rows

[ju21878436312]

I import a text file and would like to write a comment in certain rows, which I access with df.loc.
However, I get the error "# When setting, missing keys are not allowed, even with .loc:".
Could someone tell me, how to avaid it? I have checked the documentation, where a similar way worked out .

import pandas as pd
import numpy as np

df = pd.read_csv('2021-06-15_data.txt', delimiter= '\t',parse_dates=[[0, 1]], header=None, names=["Date","Time","Channel","time","0.3","0.5","1.0","3.0","5.0","10.0"])
df['Date_Time'] = df['Date_Time'] + pd.Timedelta(days = 365*20)

# print types works fine
print(df.head(5)) 
df.dtypes

# iloc works fine
print("iloc") 
df.iloc[5:7]

# loc works fine
print("loc")
df.loc[(df['Date_Time']  >= '2021-06-10 09:51:04')&(df['Date_Time']  < '2021-06-10 09:51:26')] 

# create new column 
df['Comment']=""

# write data in column 'Comment', only for certain rows creates KeyError
df.loc[(df['Date_Time']  >= '2021-06-10 09:51:04')&(df['Date_Time']  < '2021-06-10 09:51:26'),df['Comment']]="zero"

2021-06-15_data.txt:

15.06.2001	09:50:42	1	10	5	4	4	1	1	1
15.06.2001	09:50:53	1	10	0	0	0	0	0	0
15.06.2001	09:51:04	1	10	0	0	0	0	0	0
15.06.2001	09:51:15	1	10	0	0	0	0	0	0
15.06.2001	09:51:26	1	10	0	0	0	0	0	0
15.06.2001	09:51:37	1	10	0	0	0	0	0	0
15.06.2001	09:51:48	1	10	0	0	0	0	0	0
15.06.2001	09:51:59	1	10	0	0	0	0	0	0
15.06.2001	09:52:10	1	10	0	0	0	0	0	0
15.06.2001	09:52:21	1	10	0	0	0	0	0	0

[ju21878436312]

I found the solution:

# write data in column 'Comment', only for certain rows creates KeyError
df.loc[(df['Date_Time']  >= '2021-06-10 09:50:31')&(df['Date_Time']  < '2021-06-10 09:51:00'),'Comment']="zero" 
df