创建布尔掩码时,您将整数与nans
进行比较.在您的情况下,将df['x']=np.nan
与50进行比较时,掩码df['x'] >= 50
将始终为False
,如果将其转换为整数,则掩码df['x'] >= 50
将等于0
.您只需为['x', 'y']
列中包含任何np.nan
的所有行创建一个等于True
的布尔掩码,然后将np.nan
分配给这些行.
代码:
import pandas as pd
import numpy as np
mydata = {'x' : [10, 50, np.nan, 32, 47, np.nan, 20, 5, 100, 62],
'y' : [10, 1, 5, np.nan, 47, np.nan, 8, 5, 100, 3]}
df = pd.DataFrame(mydata)
df["z"] = ((df["x"] >= 50) & (df["y"] <= 20)).astype("uint32")
df.loc[df[["x", "y"]].isna().any(axis=1), "z"] = np.nan
输出:
x y z
0 10.0 10.0 0.0
1 50.0 1.0 1.0
2 NaN 5.0 NaN
3 32.0 NaN NaN
4 47.0 47.0 0.0
5 NaN NaN NaN
6 20.0 8.0 0.0
7 5.0 5.0 0.0
8 100.0 100.0 0.0
9 62.0 3.0 1.0
或者,如果您想要一行,可以使用嵌套的np.where
条语句:
df["z"] = np.where(
df.isnull().any(axis=1), np.nan, np.where((df["x"] >= 50) & (df["y"] <= 20), 1, 0)
)