问题描述
我有一个数据框 pd.我想更改列 irr 的值，具体取决于它是高于还是低于阈值.
I have a dataframe pd. I would like to change a value of column irr depending on whether it is above or below a thresh hold.
我怎样才能在一行中做到这一点?现在我有
How can I do this in a single line? Now I have
pd['irr'] = pd['irr'][pd['cs']*0.63 > pd['irr']] = 1.0
pd['irr'] = pd['irr'][pd['cs']*0.63 <= pd['irr']] = 0.0
问题当然是我改了irr，在下一行再次检查.
The problem of course is that I change irr and check it again in the next line.
是否有类似 pandas 的三元条件运算符?
Is there something like a ternary conditional operator for pandas?
推荐答案
在 pandas 中没有，在 numpy 中是.
In pandas no, in numpy yes.
您可以使用 numpy.where 或将条件创建的 boolean Series 转换为 float - True 是 1.0 和 >Falses 是 0.0:
You can use numpy.where or convert boolean Series created by condition to float - Trues are 1.0 and Falses are 0.0:
pd['irr'] = np.where(pd['cs']*0.63 > pd['irr'], 1.0, 0.0)
或者:
pd['irr'] = (pd['cs']*0.63 > pd['irr']).astype(float)
示例:
pd = pd.DataFrame({'cs':[1,2,5],
'irr':[0,100,0.04]})
print (pd)
cs irr
0 1 0.00
1 2 100.00
2 5 0.04
pd['irr'] = (pd['cs']*0.63 > pd['irr']).astype(float)
print (pd)
cs irr
0 1 1.0
1 2 0.0
2 5 1.0
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