Agfdhyk

I have 2 dataframes containing text as list in each row. This one is called df

Datum   File    File_type   Text    

Datum                                               

2000-01-27  2000-01-27  0864820040_000127_04.txt    _04     [business, date, jan, heineken, starts, integr..

and i have another one, df_lm which looks like this

List_type   Words

0   LM_cnstrain.    [abide, abiding, bound, bounded, commit, commi...

1   LM_litigius.    [abovementioned, abrogate, abrogated, abrogate...

2   LM_modal_me.    [can, frequently, generally, likely, often, ou...

3   LM_modal_st.    [always, best, clearly, definitely, definitive...

4   LM_modal_wk.    [almost, apparently, appeared, appearing, appe...

I want to create new columns in df, where the match of words should be counted, so for example how many words are there from df_lm.Words[0] in df.Text[0]

Note: df has ca 500 rows and df_lm has 6 -> so i need to create 6 new columns in df so that the updated df looks somewhat like this

    Datum   ...LM_cnstrain  LM_litigius  Lm_modal_me  ...

2000-01-27  ...   5            3             4

2000-02-25 ...    7            1             0

I hope i was clear on my question.
Thanks in advance!

EDIT:
i have already done smth. similar by creating a list and loop over it, but as the lists in df_lm are very long this is not an option.

The code looked like this:

result_list

for file in file_list:

    count_growth = 0

    for word in text.split ():

        if word in growth:

            count_growth = count_growth +1

    a={'Grwoth':count_growth}

    result_list.append(a)

According to my comments you can try something like this:

The below code has to run in a loop where text column from 1st df has to be matched with all 6 from next and make column with value from len(c)

desc = df_lm.iloc[0,1]

matches = df.text.isin(desc)

result = df.text[matches]

If this helps you, let me know otherwise will update/delete the answer

So ive come to the following solution:

    for file in file_list:

        count_lm_constraint = 0

        count_lm_litigious = 0

        count_lm_modal_me = 0

          for word in text.split()

        if word in df_lm.iloc[0,1]:

                count_lm_constraint = count_lm_constraint +1 

            if word in df_lm.iloc[1,1]:

                count_lm_litigious = count_lm_litigious +1

            if word in df_lm.iloc[2,1]:

                count_lm_modal_me = count_lm_modal_me +1

            a={"File": name, "Text": text,'lm_uncertain':count_lm_uncertain,'lm_positive':count_lm_positive ....}

result_list.append(a)