pandas: first two elements in a string column matches dictionary key

I have a dataframe as follows:

import pandas as pd

df = pd.DataFrame({'data1':['the weather is nice today','This is interesting','the weather is good'],
             'data2':['It is raining','The plant is green','the weather is sunny']})

and I have a dictionary as follows:

my_dict = {'the weather':'today','the plant':'tree'}

I would like to replace the first two words in the data2 column if they are found in the dictionary key. I have done the following:

for old, new in dic.items():    
    if pd.Series([' '.join(map(str, l)) for l in df['data2'].str.lower().str.split().map(lambda x: x[0:2])]).str.contains('|'.join(old.capitalize()).any():
       df['data2'] = df['data2'].str.replace(old, new.capitalize(), regex=False)
    else:
       print('does not exist')

but when i print(df), nothing has been replaced.

the expected output:

                       data1                 data2
0  the weather is nice today         It is raining
1        This is interesting    Tree is green
2        the weather is good    Today is sunny

>Solution :

If I understand correctly, this is one way to do it (there may be more efficient ways):

df.data2 = df.data2.str.lower()
for k in my_dict:
  df.data2 = df.data2.str[:len(k)].replace(k, my_dict[k]) + df.data2.str[len(k):]

df.data2 = df.data2.str.capitalize()

Lowercasing and capitalization weren’t in your question but were part of your code, so I put them in (otherwise it would fail because the capitalization doesn’t match in your sample code).