Как сопоставить текст на основе строки из списка и извлечь подраздел в Python?

Question

Я пытаюсь сгенерировать структуру из текста вызова заработков, который выглядит следующим образом:

"Operator

Ladies and gentlemen, thank you for standing by. And welcome to XYZ Fourth Quarter 2019 Earning Conference Call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today’s conference is being recorded. [Operator Instructions]
I would now like to hand the conference to your speaker today,Person1, Head of Investor Relations. Please go ahead, ma’am**

Person1

Hello everyone, blablablablabla. Now let's see what Person2 has to say.

Person2

Thank you and hello everyone. Blablablabla

Person3

I have no further remarks....thank you once again"

Из этого я создал список с именем list1 = ['Person1','Person2','Person3']. Я сгенерировал пустой фрейм данных с именами столбцов Person1, Person2 и Person3. Теперь мне нужно извлечь текст ниже Person1, Person2 и Person3 на основе значений из списка и заполнить фрейм данных. Это возможно?

Answer 1

data_list = Data.split("\n")
People_Names = [name.strip() for name in People]

temp_data_list= data_list.copy()
data_dict = defaultdict(list)
isfirst=1
data_idx =0
for idx,line in enumerate(data_list):
    if line in People_Names:
        new_data_list = data_list[idx:]
        break
while len(new_data_list)>0 :
    while True:
        if new_data_list[0] in People_Names:
            key =new_data_list[0]
            break
        else:
            data_dict[key]=data_dict[key]+[new_data_list[0]]
            new_data_list.pop(0)
        if len(new_data_list)==0:
            break
    if len(new_data_list)!=0:
        new_data_list.pop(0)

df_dict = {}
for key,val in data_dict.items() :
    df_dict[key] = "\n".join(val)

df = pa.DataFrame(columns = People_Names)
df = df.append(df_dict,ignore_index=True)
#print(df)
df.to_csv("People_Data.csv")

Answer 2

text="""OperatorLadies and gentlemen, thank you for standing by. And welcome to XYZ Fourth Quarter 2019 Earning Conference Call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today’s conference is being recorded. [Operator Instructions]I would now like to hand the conference to your speaker today,Person1, Head of Investor Relations. Please go ahead, ma’am**Person1Hello everyone, blablablablabla. Now let's see what Person2 has to say.Person2Thank you and hello everyone. BlablablablaPerson3I have no further remarks....thank you once again"""

import re
say1=text.split('Person1')[2].split('Person2')[0] #getting text of person1
say2=text.split('Person2')[2].split('Person3')[0] #getting text of person2
say3=text.split('Person3')[1] #getting text of person3

#converting to a dataframe
pd.DataFrame({'Person1':say1,'Person2':say2,'Person3':say3},index=[1])