在熊猫中将一列替换为另一列

Question

我的数据框看起来像-

var view_train = '<?=$this->render("_view")?>';

我希望数据框看起来像-

date           age        english        date2           value
2020-01-08      29          55            NaT              5
2020-01-22      22          45            NaT              0
2020-01-08      29          55         2020-01-08          5
2020-01-18      43          75         2020-05-18          8
NaT             NaN         NaN        2019-02-11          3

如何在大熊猫中做

Answer 1

我想您想要一个具有最大日期值max(date,date2)的单个日期列

df：

    date        age     english date2   value
0   2020-01-08  29.0    55.0    NaN         5
1   2020-01-22  22.0    45.0    NaN         0
2   2020-01-08  29.0    55.0    2020-01-08  5
3   2020-01-18  43.0    75.0    2020-05-18  8
4   NaN         NaN     NaN     2019-02-11  3

---

df['date'] = pd.to_datetime(df['date'])
df['date2'] = pd.to_datetime(df['date2'])
df['date'] = df[['date','date2']].max(axis=1)
df.drop('date2', axis=1, inplace=True)
df.fillna(0,axis=1,inplace=True)

---

df：

    date        age     english value
0   2020-01-08  29.0    55.0    5
1   2020-01-22  22.0    45.0    0
2   2020-01-08  29.0    55.0    5
3   2020-05-18  43.0    75.0    8
4   2019-02-11  0       0       3 

编辑：

如果您只想用date2替换，则：

import numpy as np
df['date'] = pd.to_datetime(df['date'])
df['date2'] = pd.to_datetime(df['date2'])
df['date'] = np.where(df['date2'].isnull(),df['date'],df['date2'])
df.drop('date2', axis=1, inplace=True)
df.fillna(0,axis=1,inplace=True)

Answer 2

import numpy as np
df['date'] = np.where(df['date'].isna(), df['date2'], df['date'])
df = df.drop('date2', axis=1)
df = df.fillna(0)