This dataframe is the principal with the original tweets. "original_ds_.csv"

id              tweet              
---------------------------------------------
78           "onetoone"              
86           "maybe tomorrow"        
72           "thnk you"                

Then, I extracted the tweet conversation for each tweet. As a result, I have a dataframe called "threads.csv"

This dataset represents the conversation tweets extracted from an original tweet

id              tweet              conver_id
---------------------------------------------
34           "hello world"            78
36           "nice to have"           78
56           "just an exam"           72 

-The conver_id is the column which represents the id who started the conversation (extracted from the dataset original_ds_.csv)

-The conver_id is the "id" of the original_ds.csv

-It is possible have one or more tweets associated to one original tweet in the dataset as the first.

Now my question is, how can I do this:

If the id on original_ds_.csv is the same in the column conv_id of the threads.csv add a new column in the threads.csv called File_Name with the value SPANISH

The logic is a by strange to me, but if a understand correctly, starting from these dataframes:

df1 = pd.DataFrame({'tweet': list('ABC')}, index=[78,86,72])
df2 = pd.DataFrame({'tweet': list('DEF'), 'conver_id': (78,78,12)}, index=(34,36,56))

>>> df1tweet
78     A
86     B
72     C>>> df2tweet  conver_id
34     D         78
36     E         78
56     F         12

you can check for each element of df2['conver_id'] if it is in df1.index and map to SPANISH is True:

df2['File_Name'] = (np.vectorize({True: 'SPANISH',False: ''}.get)(df2['conver_id'].isin(df1.index)))

output:

   tweet  conver_id File_Name
34     D         78   SPANISH
36     E         78   SPANISH
56     F         12                  

If this is not what you want, please update your question with the expected output