def inverted_index_test():
df1 = pd.DataFrame({"A":['a c a','b d'],"B":['a d a','c a']})
print(df1)
print("A分割操作")
df2 = df1['A'].str.split(' ',expand=True)
print(df2)
print("堆叠操作")
df3 = df2.stack()
print(df3)
print("修剪索引")
df4 = df3.reset_index(level=1,drop=True)#level 会删除对应的mutil值
df4 = pd.DataFrame(df4)
print(df4.index)
print(df4)
print("执行join操作")
df5 = df4.join(df1)
print(df5)
输出内容：
Python 3.9.12 (main, Apr 5 2022, 06:56:58)
[GCC 7.5.0] on linux
A B
0 a c a a d a
1 b d c a
A分割操作
0 1 2
0 a c a
1 b d None
堆叠操作
0 0 a
1 c
2 a
1 0 b
1 d
dtype: object
修剪索引
Int64Index([0, 0, 0, 1, 1], dtype='int64')
0
0 a
0 c
0 a
1 b
1 d
执行join操作
0 A B
0 a a c a a d a
0 c a c a a d a
0 a a c a a d a
1 b b d c a
1 d b d c a
标签：index,join,倒排,方式,df4,df1,索引,print From： https://www.cnblogs.com/chenjie0949/p/17054722.html