如果条件满足，pandas 创建一列等于另一列
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pandas create one column equal to another if condition is satisfied
提问by As3adTintin
I have two columns as below:
我有两列如下：
id, colA, colB
0, a, 13
1, a, 52
2, b, 16
3, a, 34
4, b, 946
etc...
I am trying to create a third column, colC, that is colBif colA == a, otherwise 0.
我正在尝试创建第三列colC，即colBif colA == a， else 0。
This is what I was thinking, but it does not work:
这是我的想法，但它不起作用：
data[data['colA']=='a']['colC'] = data[data['colA']=='a']['colB']
I was also thinking about using np.where(), but I don't think that would work here.
我也在考虑使用np.where()，但我认为这在这里行不通。
Any thoughts?
有什么想法吗？
回答by EdChum
Use locwith a mask to assign:
loc与掩码一起使用以分配：
In [300]:
df.loc[df['colA'] == 'a', 'colC'] = df['colB']
df['colC'] = df['colC'].fillna(0)
df
Out[300]:
id colA colB colC
0 0 a 13 13
1 1 a 52 52
2 2 b 16 0
3 3 a 34 34
4 4 b 946 0
EDIT
编辑
or use np.where:
或使用np.where：
In [296]:
df['colC'] = np.where(df['colA'] == 'a', df['colC'],0)
df
Out[296]:
id colA colB colC
0 0 a 13 13
1 1 a 52 52
2 2 b 16 0
3 3 a 34 34
4 4 b 946 0
回答by vmg
df['colC'] = df[df['colA'] == 'a']['colB']
should result in exactly what you want, afaik.
应该会产生你想要的结果，afaik。
Then replace the NaN's with zeroes with df.fillna(inplace=True)
然后用零替换 NaN df.fillna(inplace=True)
