Python 通过排除表中另一列中的特定值来填充一列

对于数据帧

df

，如果列

a

中的值为空

NaNs

或

其他

，我将尝试按值填充列

b

：

df = pd.DataFrame({'a':['Coffee','Muffin','Donut','Others',pd.np.nan, pd.np.nan]})
        a
0  Coffee
1  Muffin
2   Donut
3  Others
4     NaN
5     NaN

df.loc[~df['a'].fillna('Others').eq('Others'), 'b'] = '2017-01-01'
print (df)
        a           b
0  Coffee  2017-01-01
1  Muffin  2017-01-01
2   Donut  2017-01-01
3  Others         NaN
4     NaN         NaN
5     NaN         NaN

预期结果如下：

        a           b
0  Coffee  2017-01-01
1  Muffin  2017-01-01
2   Donut  2017-01-01
3  Others         NaN
4     NaN         NaN
5     NaN         NaN

我尝试过的没有排除NaNs的内容：

df.loc[~df['a'].isin(['nan', 'Others']), 'b'] = '2017-01-01'

        a           b
0  Coffee  2017-01-01
1  Muffin  2017-01-01
2   Donut  2017-01-01
3  Others         NaN
4     NaN  2017-01-01
5     NaN  2017-01-01

---

谢谢

使用

np.nan

代替

nan

：

df.loc[~df['a'].isin([np.nan, 'Others']), 'b'] = '2017-01-01'

或在比较之前，用

其他替换缺少的值

：

df = pd.DataFrame({'a':['Coffee','Muffin','Donut','Others',pd.np.nan, pd.np.nan]})
        a
0  Coffee
1  Muffin
2   Donut
3  Others
4     NaN
5     NaN

df.loc[~df['a'].fillna('Others').eq('Others'), 'b'] = '2017-01-01'
print (df)
        a           b
0  Coffee  2017-01-01
1  Muffin  2017-01-01
2   Donut  2017-01-01
3  Others         NaN
4     NaN         NaN
5     NaN         NaN

看看这个：

import numpy as np
import pandas as pd

df = pd.DataFrame({'a': ['Coffee', 'Muffin', 'Donut', 'Others', pd.np.nan, pd.np.nan]})
conditions = [
    (df['a'] == 'Others'),
    (df['a'].isnull())
]
choices = [np.nan, np.nan]
df['color'] = np.select(conditions, choices, default='2017-01-01')

print(df)

---

你能给我看一下你输入的得到结果的代码吗？对不起，我错过了。已更新。如果不是“NaN”或“others”，您似乎正在尝试填写日期字符串是的，只是示例数据。谢谢，我有一个问题，为什么您需要两个日期作为

选项

？每个条件一个选项