How can I get specific columns form txt file and save them to new file using python-CodePudding

I have this txt file sentences.txt that contains texts below

a01-000u-s00-00 0 ok 154 19 408 746 1661 89 A|MOVE|to|stop|Mr.|Gaitskell|from

which contains 10 columns I want to use the panda's data frame to extract only the file name (at column 0) and corresponding text (column 10) without the (|) character I wrote this code

def load() -> pd.DataFrame:

 df = pd.read_csv('sentences.txt',sep=' ', header=None)
 data = []
 with open('sentences.txt') as infile:
    for line in infile:
        file_name, _, _, _, _, _, _, _, _, text = line.strip().split(' ')
        data.append((file_name, cl_txt(text)))

 df = pd.DataFrame(data, columns=['file_name', 'text'])
 df.rename(columns={0: 'file_name', 9: 'text'}, inplace=True)
 df['file_name'] = df['file_name'].apply(lambda x: x   '.jpg')
 df = df[['file_name', 'text']]
 return df

def cl_txt(input_text: str) -> str:
 text = input_text.replace(' ', '-')
 text = text.replace('|', ' ')
 return text

load()

the error I got

ParserError: Error tokenizing data. C error: Expected 10 fields in line 4, saw 11

where my expected process.txt file results should look like below without \n

a01-000u-s00-00  A MOVE to stop Mr. Gaitskell from
a01-000u-s00-01  nominating any more Labour life Peers

CodePudding user response：

IIUC, you just need