|
1
2
3
|
from
pandas
import
DataFrame
import
pandas as pd
import
numpy as np
|
生成DataFrame数据
|
1
|
df
=
DataFrame(np.random.randn(
4
,
5
), columns
=
[
'A'
,
'B'
,
'C'
,
'D'
,
'E'
])
|
DataFrame数据预览：
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1
2
3
4
5
|
A B C D E
0
0.673092
0.230338
-
0.171681
0.312303
-
0.184813
1
-
0.504482
-
0.344286
-
0.050845
-
0.811277
-
0.298181
2
0.542788
0.207708
0.651379
-
0.656214
0.507595
3
-
0.249410
0.131549
-
2.198480
-
0.437407
1.628228
|
计算各列数据总和并作为新列添加到末尾
|
1
|
df[
'Col_sum'
]
=
df.
apply
(
lambda
x: x.
sum
(), axis
=
1
)
|
计算各行数据总和并作为新行添加到末尾
|
1
|
df.loc[
'Row_sum'
]
=
df.
apply
(
lambda
x: x.
sum
())
|
最终数据结果：
|
1
2
3
4
5
6
|
A B C D E Col_sum
0
0.673092
0.230338
-
0.171681
0.312303
-
0.184813
0.859238
1
-
0.504482
-
0.344286
-
0.050845
-
0.811277
-
0.298181
-
2.009071
2
0.542788
0.207708
0.651379
-
0.656214
0.507595
1.253256
3
-
0.249410
0.131549
-
2.198480
-
0.437407
1.628228
-
1.125520
Row_sum
0.461987
0.225310
-
1.769627
-
1.592595
1.652828
-
1.022097
|