pandas_df.groupby()

import pandas as pd

df = pd.DataFrame(
{"text_id":[0,0,1,1],"question":['唐六典中说式占有哪三式？', "六壬著作有哪些？",  '汉的意思是什么？', "利玛窦何时来华？"],"A":["雷公式，太一式，六壬式", "《壬归》校译释论", '汉子', "清朝"],"B":["太史，太师，太公", "《唐六典》", "银河", "明朝"],"answer":[1, 1, 2, 2]
})

# 根据text_id字段分组
group = df.groupby("text_id")

# 取组值为0的这一组
group.get_group(0)

group.groups

{0: Int64Index([0, 1], dtype='int64'), 1: Int64Index([2, 3], dtype='int64')}

group.size()

text_id
0    2
1    2
dtype: int64

# 2
len(group)

# n是分组字段的值
for n,g in group:print(n)

0
1

# 获得一份副本，不然下面的操作容易报警告
# 对该副本的操作不会影响原对象
df_c = df.copy()# 更改某个字段值的表示1
df_c['answer'] = df_c['answer'].replace({1:'A', 2:'B'})# 更改某个字段值的表示2
df_c['answer'] = df_c['answer'].map({1:'A', 2:'B'})

参考：------链接--------