將 txt 文件轉換為 python 中的數據框

Question

我有一個包含一些數據的文本文件。 我需要將我的文本文件拆分為數據框。 這是我的文本文件：

    2012/02/03 18:55:54 SampleClass1 verb detail for id 19471668
    verb detail for id 185289
    verb detail for id 185289
    verb detail for id 1852849
    2012/03/03 18:55:54 SampleClass8 detail for id 2181536
    2012/04/03 18:55:54 SampleClass1 verb detail for id 1765383670
    2012/05/03 18:55:54 SampleClass9 verb detail for id 1666944491
    2012/06/03 18:55:54 SampleClass8 detail for id 799914029 verb detail for id 185229

我想分別拆分日期和時間以及一些字符串，然后我需要將其轉換為數據框。

我預期的 output：

date       time     desc
2012/02/03 18:55:54 SampleClass9 verb detail for id 1947166588
                    verb  detail for id 185289
                    verb detail for id 185289
                    verb detail for id 1852849

2012/03/03 18:55:54 SampleClass8 detail for id 218851536
                    verb detail for id 1852829
                    verb detail for id 185289
                    verb detail for id 1852849
2012/04/03 18:55:54 SampleClass1 verb detail for id 1765383670
                    verb detail for id 1852829
                    verb detail for id 1852829
                    verb detail for id 1852849
2012/05/03 18:55:54 SampleClass9 verb detail for id 1666944491
                    verb detail for id 1852829
                     verb detail for id 1852829
                     verb detail for id 18528429
2012/06/03 18:55:54 SampleClass8 detail for id 799914029 verb detail for id 1852844029
                    verb detail for id 1852829
                    verb detail for id 1852829
                    verb detail for id 18528429

Answer 1

根據您輸入的數據，下面的代碼可以完成這項工作。

import csv
import pandas as pd
    
file = "/path/to/file/"
# Open CSV file
with open(file, "r", newline="") as fp:
    # Read the text file and use a space delimiter
    reader = csv.reader(fp, delimiter=" ")
    rows = []
    # loop through the rows
    for row in reader:
        # if empty row then continue
        if not row:
            continue
        #if the first character of the row is a number join the columns after
        # column 2, as columns one and two are already separated
        elif row[0][0].isdigit():
            rows.append(row[:2]+ [' '.join(row[2:])])
        # else add two columns and then join the columns
        else:
            rows.append(['','']+ [' '.join(row)])
        df = pd.DataFrame(rows, columns=['date','time','desc'])