我在矩阵
中得到歧义元素的意思 import pandas as pd
ds2 = [[ 4, 1],
[ 5, 3],
[ 6, 1],
[ 7, 2],
[ 7, 2],
[ 8, 2],
[12, 1],
[ 9, 3],
[12, 1],
[13, 2],
[22, 3]]
ds2= pd.DataFrame(ds2)
print type(ds2)
print ds2
ds2 = ds2.groupby(0).mean()
print type(ds2)
print ds2
输出:
<class 'pandas.core.frame.DataFrame'>
0 1
0 4 1
1 5 3
2 6 1
3 7 2
4 8 2
5 9 3
6 12 1
7 13 2
8 22 3
<class 'pandas.core.frame.DataFrame'>
1
0
4 1
5 3
6 1
7 2
8 2
9 3
12 1
13 2
22 3
类型保持不变,但矩阵的方式看起来有变化,有没有办法在处理后保持矩阵视图?
答案 0 :(得分:1)
将参数as_index=False
传递给groupby
方法:
In [140]:
ds2 = [[ 4, 1],
[ 5, 3],
[ 6, 1],
[ 7, 2],
[ 7, 2],
[ 8, 2],
[12, 1],
[ 9, 3],
[12, 1],
[13, 2],
[22, 3]]
ds2= pd.DataFrame(ds2)
ds2.groupby(0, as_index=False).mean()
Out[140]:
0 1
0 4 1
1 5 3
2 6 1
3 7 2
4 8 2
5 9 3
6 12 1
7 13 2
8 22 3
默认情况下,任何传递的列都将用于构成索引。
来自文档:
as_index : boolean, default True
For aggregated output, return object
with group labels as the index. Only relevant for DataFrame input.
as_index=False is effectively “SQL-style” grouped output