我有两个日期时间列-ColumnA和ColumnB。我想使用条件逻辑创建一个新列-ColumnC。
最初，我从YearMonth列（例如201907、201908等）创建了ColumnB。
当ColumnA为NaN时，我想选择ColumnB。 否则，我要选择ColumnA。
当前，我的下面代码使ColumnC具有不同的格式。我不确定如何摆脱所有这些0。我希望整列为YYYY-MM-DD。
ID YearMonth ColumnA ColumnB ColumnC
0 1 201712 2017-12-29 2017-12-31 2017-12-29
1 1 201801 2018-01-31 2018-01-31 2018-01-31
2 1 201802 2018-02-28 2018-02-28 2018-02-28
3 1 201806 2018-06-29 2018-06-30 2018-06-29
4 1 201807 2018-07-31 2018-07-31 2018-07-31
5 1 201808 2018-08-31 2018-08-31 2018-08-31
6 1 201809 2018-09-28 2018-09-30 2018-09-28
7 1 201810 2018-10-31 2018-10-31 2018-10-31
8 1 201811 2018-11-30 2018-11-30 2018-11-30
9 1 201812 2018-12-31 2018-12-31 2018-12-31
10 1 201803 NaN 2018-03-31 1522454400000000000
11 1 201804 NaN 2018-04-30 1525046400000000000
12 1 201805 NaN 2018-05-31 1527724800000000000
13 1 201901 NaN 2019-01-31 1548892800000000000
14 1 201902 NaN 2019-02-28 1551312000000000000
15 1 201903 NaN 2019-03-31 1553990400000000000
16 1 201904 NaN 2019-04-30 1556582400000000000
17 1 201905 NaN 2019-05-31 1559260800000000000
18 1 201906 NaN 2019-06-30 1561852800000000000
19 1 201907 NaN 2019-07-31 1564531200000000000
20 1 201908 NaN 2019-08-31 1567209600000000000
21 1 201909 NaN 2019-09-30 1569801600000000000
df['ColumnB'] = pd.to_datetime(df['YearMonth'], format='%Y%m', errors='coerce').dropna() + pd.offsets.MonthEnd(0)
df['ColumnC'] = np.where(pd.isna(df['ColumnA']), pd.to_datetime(df['ColumnB'], format='%Y%m%d'), df['ColumnA'])
答案 0 :(得分：0)
df ['ColumnC'] = np.where（df ['ColumnA']。isnull（），df ['ColumnB']，df ['ColumnA']）
答案 1 :(得分：0)
就算了！
df['ColumnC'] = np.where(pd.isna(df['ColumnA']), pd.to_datetime(df['ColumnB']), pd.to_datetime(df['ColumnA']))