如果你的档案真的是这样），则可以使用标准库模块itertools中的groupby：

from itertools import groupby

def key(line): return line.startswith("|Family|")

family_line, file_no = None, 0
with open("file.csv", "r") as fin:
    for is_family_line, lines in groupby(fin, key=key):
        if is_family_line:
            family_line = list(lines).pop()
        elif family_line is None:
            header = "".join(lines)
        else:
            file_no += 1
            with open(f"file{file_no}.csv", "w") as fout:
                fout.write(header + family_line)
                for line in lines:
                    fout.write(line)

Pandas的解决方案是：

import pandas as pd

df = pd.read_csv("file.csv", header=None, delimiter="|").fillna("")
blocks = df.iloc[:, 1].eq("Family").cumsum()
header_df = df[blocks.eq(0)]
for no, sdf in df.groupby(blocks):
    if no > 0:
        sdf = pd.concat([header_df, sdf])
        sdf.to_csv(f"file{no}.csv", index=False, header=False, sep="|")

import pandas as pd
pd.read_csv('file.csv',delimiter='|')
groups = df.groupby('Family')
for name, group in groups:
    group.to_csv(name + '.csv', index=False)

下面是一个纯python的工作方法：

# Read file
with open('file.csv', 'r') as file:
    text = file.read()

# Split using |Family|
splitted_text = text.split("|Family|")

# Remove unwanted content before first |Family|
splitted_text = splitted_text[1:]

# Add |Family| back to each part
splitted_text = ['|Family|' + item for item in splitted_text]

# Write files
for i, content in enumerate(splitted_text ):
    with open('file{}.csv'.format(i), 'w') as file:
        file.write(content)