试试下面的代码（里面的评论）：

import pandas as pd
import re

def read_transactional_data(csvfile):
    """Read transactional data file."""
    with open(csvfile) as fp:
        # Extract date from the first line of file
        dti = pd.to_datetime(re.findall(r'\d{4}-\d{2}-\d{2}',fp.readline()))

        # Read csv as usual but skip the next two rows
        df = pd.read_csv(fp,sep=',',header=None,skiprows=2)

        # Remove date separator columns (every 5 columns)
        df = df.drop(columns=list(range(4,len(df.columns),5)))

        # Replace column index by a multi-index (date,variable)
        cols = ['product_code','product_name','sale_amount','sale_qty']
        df.columns = pd.MultiIndex.from_product([dti,cols],names=['date',None])

        # Make a proper indexed dataframe
        df = df.stack(level=0).reset_index(level=0,drop=True) \
               .sort_index().reset_index()
        return df


# From your pastebin file
df = read_transactional_file('data.csv')

>>> df
        date product_code product_name  sale_amount  sale_qty
0 2021-08-01         P001     Product1        200.0       2.0
1 2021-08-01         P002     Product2        300.0       5.0
2 2021-08-01         P001     Product1        400.0       4.0
3 2021-08-02         P001     Product1        200.0       2.0
4 2021-08-02         P003     Product3        500.0      10.0
5 2021-08-02         P003     Product3        550.0      11.0
6 2021-08-02         P002     Product2        300.0       5.0