set multiple column values for multiple rows with loc

I have this Dataframe:

     A  B  C  D  E  F  G  H  I  J  K
0    .  .  .  .  .  .  X  L  .  .  .
1    .  .  .  .  .  .  X  A  .  .  .
.
.
.
300  .  .  .  .  .  .  X  R  .  .  .
301  .  .  .  .  .  . nan R  .  .  .
302  .  .  .  .  .  .  X  R  .  .  .
303  .  .  .  .  .  . nan R  .  .  .

I am trying to change columns G and I to U if H = R.
Expected output:

     A  B  C  D  E  F  G  H  I  J  K
0    .  .  .  .  .  .  X  L  .  .  .
1    .  .  .  .  .  .  X  A  .  .  .
.
.
.
300  .  .  .  .  .  .  U  R  U  .  .
301  .  .  .  .  .  .  U  R  U  .  .
302  .  .  .  .  .  .  U  R  U  .  .
303  .  .  .  .  .  .  U  R  U  .  .

Is there a way to pass multiple columns to the loc here instead of doing this twice or having to loop twice like this which looks non-pythonic:

df.loc[df[‘H’] == ‘R’, ‘G’] = ‘U’

df.loc[df[‘H’] == ‘R’, ‘I’] = ‘U’

I thought this would be trivial but can’t find any clear solution.

>Solution :

As @Tim already mentioned you can proceed like the following :
import pandas as pd

data = {
    'A': ['.']*304,
    'B': ['.']*304,
    'C': ['.']*304,
    'D': ['.']*304,
    'E': ['.']*304,
    'F': ['.']*304,
    'G': ['.']*301 + ['nan', 'X', 'nan'],
    'H': ['L', 'A'] + ['R']*301,
    'I': ['.']*304,
    'J': ['.']*304,
    'K': ['.']*304
}

df = pd.DataFrame(data)

# Modify 'G' and 'I' columns where 'H' is 'R'
df.loc[df['H'] == 'R', ['G', 'I']] = 'U'

print(df)

If you want to get for H=R and then sets G to U and I to M for example in a single liner :

df.loc[df['H'] == 'R', ['G', 'I']] = df.loc[df['H'] == 'R'].assign(G='U', I='M')[['G', 'I']]