python - 在多个条件下合并来自多个数据框的数据

Question

我想合并多个数据框，但前提是键匹配并且日期范围在 df1 中“InitialAdmit”日期范围的 90 天内。我想保留 df1 中的所有行，只合并 df2、df3 等中的其他行，只要它们与键匹配并在日期范围内即可。

注意:先合并 dfs 然后考虑日期范围条件对我不起作用。我首先使用了这种方法，但在很多情况下合并成功，但由于日期范围超出限制，我让脚本删除了该行。我需要以某种方式保留 df1 中的所有行。

Python Pandas: Merging data frames on multiple conditions - 这个问题很相似，但它似乎合并然后应用条件。我认为更好的方法是应用条件，然后在满足条件时合并。不过，我愿意接受建议。

数据框:

a = {'Key': [100000204, 100000255, 100000271,100000286,100000628], 
 'InitialAdmit': ['2012-06-04', '2012-05-03', '2012-01-16', '2012-10-26', '2012-02-21'],
 '90DayRange': ['2012-09-02', '2012-08-01', '2012-04-15', '2013-01-24', '2012-05-21']
}
df1 = pandas.DataFrame(data=a)
df1


b = {'Key': [100000208, 100000255, 100000723,100000286,100000866], 
 'InitialAdmit': ['2012-01-22', '2012-06-03', '2012-10-26', '2012-11-26', '2012-05-11'],
}
df2 = pandas.DataFrame(data=b)
df2 

c = {'Key': [100000255, 100000255, 100000702,100000221,100000628], 
 'InitialAdmit': ['2012-06-22', '2012-10-03', '2012-10-26', '2012-11-26', '2012-04-11'],
}
df3 = pandas.DataFrame(data=c)
df3

脚本:

df_NotIncludedRows = pandas.DataFrame()
df_final = pandas.DataFrame()
dfs = [df2] #I plan to add more dataframes so I'm iterating through this list of dfs 

for df in dfs: #iterate through each df in dfs
    for key in df1["Key"]: #iterate through each key found in column 'Id'
        if key in df["Key"]: # find any matching key from df1 in df2 (part of my issue exists here)
            if (df["Admit"] >= df1["InitialAdmit"]) | (df["Admit"] <= df1["90DayRange"]):
                df_final = pandas.merge(df1,df.loc[:],on='Key',how='left') # my df.loc[:] is a little off i think
            else:
                df_NotIncludedRows = df_NotIncludedRows.append(df.loc[:]) # same df.loc[:] issue i believe   
df_NotIncludedRows

Answer 1

我还是推荐merge then filter，这里我们使用 bool 索引和combine_first

df=df1.merge(df2,on='Key')
m=(df.InitialAdmit_y>=df.InitialAdmit_x)&(df.InitialAdmit_y<=df.InitialAdmit_x)
df1.set_index('Key').combine_first(df[m].set_index('Key'))


Out[215]: 
          90DayRange InitialAdmit InitialAdmit_x InitialAdmit_y
Key                                                            
100000204 2012-09-02   2012-06-04            NaT            NaT
100000255 2012-08-01   2012-05-03     2012-05-03     2012-06-03
100000271 2012-04-15   2012-01-16            NaT            NaT
100000286 2013-01-24   2012-10-26     2012-10-26     2012-11-26
100000628 2012-05-21   2012-02-21            NaT            NaT