我的數據框看起來像 -date age english date2 value2020-01-08 29 55 NaT 52020-01-22 22 45 NaT 02020-01-08 29 55 2020-01-08 52020-01-18 43 75 2020-05-18 8NaT NaN NaN 2019-02-11 3我希望我的數據框看起來像 -date age english value2020-01-08 29 55 52020-01-22 22 45 02020-01-08 29 55 52020-05-18 43 75 82019-02-11 0 0 3如何在熊貓中做到這一點
2 回答
青春有我
TA貢獻1784條經驗 獲得超8個贊
我猜你想要一個具有最大日期值的日期列max(date,date2)
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
編輯：
如果您只想替換為date2如果存在：
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)
HUWWW
TA貢獻1874條經驗 獲得超12個贊
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)添加回答
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