Question

我的数据框df有'TPrice','THigh','TLow','TOpen','TClose','TPCLOSE'列，现在我想将'TPrice','THigh','TLow','TOpen','TClose'列的值设置为与'TPCLOSE'列相同的行TPrice 1}}列值为零。

显示TPrice为0的一些行：

>>> df[df['TPrice']==0][['TPrice','THigh','TLow','TOpen','TClose','TPCLOSE']][0:5]
    TPrice  THigh  TLow  TOpen  TClose  TPCLOSE
13       0      0     0      0       0     4.19
19       0      0     0      0       0     7.74
32       0      0     0      0       0     3.27
43       0      0     0      0       0    12.98
60       0      0     0      0       0     7.48

然后分配：

>>> df[df['TPrice']==0][['TPrice','THigh','TLow','TOpen','TClose']] = df['TPCLOSE']

但是Pandas并没有真正改变df，因为下面的代码仍然可以找到一些行：

>>> df[df['TPrice']==0][['TPrice','THigh','TLow','TOpen','TClose','TPCLOSE']][0:5]
    TPrice  THigh  TLow  TOpen  TClose  TPCLOSE
13       0      0     0      0       0     4.19
19       0      0     0      0       0     7.74
32       0      0     0      0       0     3.27
43       0      0     0      0       0    12.98
60       0      0     0      0       0     7.48

那怎么办？

杰夫解决方案的更新：

>>> quote_df = get_quote()
>>> quote_df[quote_df['TPrice']==0][['TPrice','THigh','TLow','TOpen','TClose','TPCLOSE','RT','TVol']][0:5]
    TPrice  THigh  TLow  TOpen  TClose  TPCLOSE   RT  TVol
13       0      0     0      0       0     4.19 -100     0
32       0      0     0      0       0     3.27 -100     0
43       0      0     0      0       0    12.98 -100     0
45       0      0     0      0       0    26.74 -100     0
60       0      0     0      0       0     7.48 -100     0
>>> row_selection = quote_df['TPrice']==0
>>> col_selection = ['THigh','TLow','TOpen','TClose']
>>> for col in col_selection:
...     quote_df.loc[row_selection, col] = quote_df['TPCLOSE']
... 
>>> quote_df[quote_df['TPrice']==0][['TPrice','THigh','TLow','TOpen','TClose','TPCLOSE','RT','TVol']][0:5]
    TPrice  THigh  TLow  TOpen  TClose  TPCLOSE   RT  TVol
13       0   4.19  4.19   4.19    4.19     4.19 -100     0
32       0   4.19  4.19   4.19    4.19     3.27 -100     0
43       0   4.19  4.19   4.19    4.19    12.98 -100     0
45       0   4.19  4.19   4.19    4.19    26.74 -100     0
60       0   4.19  4.19   4.19    4.19     7.48 -100     0
>>>

Answer 1

此操作不会自动广播，因此您需要执行此类操作

In [17]: df = DataFrame(dict(A = [1,2,0,0,0],B=[0,0,0,10,11],C=[3,4,5,6,7]))

In [18]: df
Out[18]: 
   A   B  C
0  1   0  3
1  2   0  4
2  0   0  5
3  0  10  6
4  0  11  7

首先计算要屏蔽的行（否则它们可能会随时更改）如果你要修改A（就像你在这里一样）

In [19]: mask = df['A'] == 0

In [20]: for col in ['A','B']:
   ....:     df.loc[mask,col] = df['C']
   ....:     

In [21]: df
Out[21]: 
   A  B  C
0  1  0  3
1  2  0  4
2  5  5  5
3  6  6  6
4  7  7  7

这需要进行更改以使其更自然（因为您将rhs上的一系列分配给lhs上的数据帧，现在它不会像您认为的那样进行广播） https://github.com/pydata/pandas/issues/5206

Answer 2

>>> import pandas as pd
>>> test=pd.DataFrame({'A': [0,1,2], 'B': [3,4,5], 'C': [6,7,8]})
>>> test
   A  B  C
0  0  3  6
1  1  4  7
2  2  5  8
>>> test.apply(lambda x: x.where(test.A!=0, test.C), axis=0)
   A  B  C
0  6  6  6
1  1  4  7
2  2  5  8

如何为Pandas数据帧的某些选定行集中设置多列的值？

2 个答案: