[英]Filling NaN with data based on condition
My code looks like that: 我的代码看起来像这样:
if df['FLAG'] == 1:
df['VAL'] = df['VAL'].fillna(median)
elif df['FLAG'] == 0:
df['VAL'] = df['VAL'].fillna(0)
Which returns - The truth value of a DataFrame is ambiguous. 返回 - DataFrame的真值是不明确的。 Use a.empty, a.bool(), a.item(), a.any() or a.all().
使用a.empty,a.bool(),a.item(),a.any()或a.all()。
I have tried with doing like a mask and then applying it with a.all() but it didn't worked out. 我尝试过做像掩码然后用a.all()应用它,但它没有成功。 I'd be very thankful for enlightment!
我非常感谢你的启发!
Edit: I've solution for my problem right here - Link 编辑:我在这里解决我的问题 - 链接
This is an elementwise operation, and you can vectorize this. 这是一个元素操作,您可以对其进行矢量化。 Build an array with
np.where
and pass that to fillna
. 使用
np.where
构建一个数组并将其传递给fillna
。
df['VAL'] = df['VAL'].fillna(np.where(df['FLAG'], median, 0))
你可以这样做
df.loc[df['VAL'].isna(),'Val']=df['FLAG']*median
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.