Заменить слово в столбце значениями из другого столбца в фрейме данных pandas

Использование .apply и лямбда:

df["Comment"] = df.apply(lambda x: x["Comment"].replace("NameTag", x["Name"]), axis=1)

import pandas as pd

data = {'ID': ['A1', 'A2'], 'Name': ['Alex', 'Alice'], 'Comment': ['the name NameTag belonging to IDTag is a common name', 'Judging the NameTag of IDTag, I feel its a girl\'s name']}

df = pd.DataFrame(data)
df['Personalized'] = df.Comment.replace(['NameTag'] * len(df), df.Name, regex=True)

print(df.Personalized)

Отпечатки

0    the name Alex belonging to IDTag is a common name
1    Judging the Alex of IDTag, I feel its a girl's...

Используйте понимание списка:

df["Comment"] = [c.replace("NameTag", n).replace("IDTag", i) 
                 for c, n, i in zip(df['Comment'], df['Name'], df['ID'])]
print (df)
    ID    Name                                            Comment
0  A1    Alex    the name Alex  belonging to A1  is a common name
1  A2   Alice   Judging the Alice  of A2 , I feel its a girl's...

Учитывая дублированный dataFrame «тест»:

test = pd.DataFrame({
    'ID': ['A1', 'A2'], 
    'Name': ['Alex', 'Alice'], 
    'Comment': ["the name NameTag belonging to IDTag is a common name", "Judging the NameTag of IDTag, I feel its a girl's name"]})

test

Выход:

ID  Name    Comment
0   A1  Alex    the name NameTag belonging to IDTag is a commo...
1   A2  Alice   Judging the NameTag of IDTag, I feel its a gir...

Этот цикл for делает то, что вам нужно, я думаю,

for row in range(test.shape[0]):
    name = test['Name'].loc[row]
    id = test['ID'].loc[row]
    test['Comment'].loc[row] = test['Comment'].loc[row].replace('NameTag', name)
    test['Comment'].loc[row] = test['Comment'].loc[row].replace('IDTag', id)

test

Выход:

    ID  Name    Comment
0   A1  Alex    the name Alex belonging to A1 is a common name
1   A2  Alice   Judging the Alice of A2, I feel its a girl's name

Для общего метода, который работает с любым количеством столбцов, вы можете использовать регулярное выражение и понимание списка:

import re

cols = ['ID', 'Name']

pattern = '|'.join([f'{x}Tag' for x in cols]) # 'IDTag|NameTag'
r = re.compile(fr"\b({pattern})\b")

df['Comment'] = [r.sub(lambda m: d.get(m.group(1)), s)
                 for d, s in zip(df[cols].add_suffix('Tag').to_dict('index').values(),
                                 df['Comment'])]

Выход:

   ID   Name                                            Comment
0  A1   Alex     the name Alex belonging to A1 is a common name
1  A2  Alice  Judging the Alice of A2, I feel its a girl's name

Пытаться :

import pandas as pd

df = pd.DataFrame({
     'ID':['A1','A2'],
     'Name':['Alex','Alice'],
     'Comment':["the name NameTag belonging to IDTag is a common name","Judging the NameTag of IDTag, I feel its a girl's name"]
})

for i  in range(len(df['Comment'])):
    df.loc[i,'Comment'] = df.loc[i,'Comment'].replace('IDTag',df.loc[i,'ID']).replace('NameTag',df.loc[i,'Name'])
  
    

Выходной фрейм данных