使用查询组合熊猫数据框

Question

我正在解决一个问题，我需要将两个数据帧合并在一起并应用类似于 SQL 中的“where”子句的条件。首先，我有两个数据框：

Member_Timepoints = pd.DataFrame(list(zip([1001,1001,1002,1003],['2016-09-02','2018-01-30','2018-03-17','2019-01-10'])),columns = ['Member_ID','Discharge_Date'])

Enrollment_Information = pd.DataFrame(list(zip([1001,1001,1002,1003,1003,1003,1003], ['2015-07-01','2018-01-01','2018-03-01','2017-11-01','2018-08-01','2019-07-01','2019-09-01'], ['2018-01-01','2262-04-11','2018-08-01','2018-08-01','2019-06-01','2019-08-01','2262-04-11'])), columns = ['Member_ID','Coverage_Effective_Date','Coverage_Cancel_Date'])

Member_Timepoints['Discharge_Date'] = pd.to_datetime(Member_Timepoints['Discharge_Date'])
Enrollment_Information['Coverage_Effective_Date'] = pd.to_datetime(Enrollment_Information['Coverage_Effective_Date'])
Enrollment_Information['Coverage_Cancel_Date'] = pd.to_datetime(Enrollment_Information['Coverage_Cancel_Date'])

我需要在“Member_ID”上将这些数据框连接在一起，并希望使用以下条件作为过滤条件：

Coverage_Effective_Date = Discharge_Date + 30

我推荐Join pandas dataframes based on different conditions 开始，但是，我仍然在努力将数据帧与上述条件合并在一起。

谁能帮我在 Pandas 中使用查询来实现这一点？

Answer 1

在这种情况下，我首先看到的是数据类型和整数加法。您不能添加不同的数据类型。你应该使用timedelta:

from datetime import timedelta
some_date_type + timedelta(days=30)

查询部分合并后可以使用.loc：

data = Enrollment_Information.merge(Member_Timepoints, on=['Member_ID'])
data.loc[(data['Coverage_Cancel_Date'] <= data['Discharge_Date'] ) &
         (data['Coverage_Cancel_Date'] >= data['Discharge_Date']+timedelta(days=30)) ]