使用OR根据两列过滤数据框

Shenanigator

我需要过滤一个数据框以减少更新用户属性的时间。

+----------+------------+------------+
| userCol1 |  dateCol1  |  dateCol2  |
+----------+------------+------------+
| user1    | 2020-01-16 | 2019-12-30 |
| user2    | 2019-10-31 | 2020-01-12 |
| user3    | 2019-08-15 | 2019-09-30 |
| user4    | 2019-08-25 | NaN        |
+----------+------------+------------+

以上是数据框的示例。我需要为datecol1或的最新日期的任何用户过滤它datecol2 is <= today-90 days。在上面的示例中，上述数据框应在该数据框中产生user2并user4保留在数据框中以进行处理。

我编写的代码（尚未经过测试，所以我不知道它是否有效）不会过滤数据帧，而是尝试遍历整个对象；这是代码。

 for row in df3.itertuples() :
     print(row.username)
     print(row.Password_Last_Set)
     print(row.Password_Last_forgot)
     if row.Password_Last_Forgot is 'NaN' and row.Password_Last_Set <= today.timedelta(days=90) :
         print('password expired based on last set, no forgot passwords')
     elif row.Password_Last_Forgot is not 'NaN' and row.Password_Last_Forgot > row.Password_Last_Set and row.Password_Last_Forgot <= today.timedelta(days=90) :
         print('password expired based on last forgot')
      elif row.Password_Last_Forgot is not 'NaN' and row.Password_Last_Forgot < row.Password_Last_Set and row.Password_Last_Set <= today.timedelta(days=90) :
         print('password expired based on last set')

在遍历用户以对其余用户执行操作之前，如何过滤？

耶斯列尔

使用boolean indexing与max用于最新的日期时间：

df[['dateCol1','dateCol2']] = df[['dateCol1','dateCol2']].apply(pd.to_datetime)

cols = ['dateCol1','dateCol2']
df1 = df.loc[df[cols].max(axis=1)<=pd.Timestamp.now() - pd.Timedelta(90, unit='d'), 'userCol1']
print (df1)
2    user3
3    user4
Name: userCol1, dtype: object

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