我有两个非常大的dfs（x = 379638行和y [routes] = 4103141行）。我想将y合并到x中，并且我使用两个dfs之间的每个公共变量来执行此操作。但是，尽管我使用了所有可变的变量，但我的合并代码仍在添加额外的5000行（合并的df = 384586行）。我的代码是默认的all.x = FALSE ....因此我不确定这里发生了什么，因为我正在使用每个df中的每个变量进行合并。有谁知道我做错了什么？
以下是我的两个dfs中的两个迷你样本（只需复制并粘贴到您的控制台中查看）以及我的代码。
df<-merge(x,routes, by=c('hai_dispense_number', 'hai_age', 'sex', 'date_of_claim', 'quantity', 'hai_ddd', 'hai_strength', 'eligibility_end_date', 'hai_atc'))
首先是df（x）
x<- read.table(header=T, text=" hai_dispense_number sex hai_age eligibility_end_date quantity date_of_claim hai_atc hai_strength hai_ddd
13 PatientHAI0000092 F 42 2011-02-28 9 2010-06-16 N05BA01 2.00 10.0
14 PatientHAI0000092 F 42 2011-02-28 3 2010-06-16 N05CF02 5.00 10.0
41 PatientHAI0000110 F 31 2011-07-31 10 2010-09-09 N05BA12 250.00 1.0
72 PatientHAI0000360 F 58 2014-10-31 30 2010-04-21 N05CF02 10.00 10.0
82 PatientHAI0000360 F 58 2014-10-31 30 2010-07-19 N05CF02 10.00 10.0
111 PatientHAI0000522 M 38 2012-08-31 10 2010-07-06 N05CF01 7.50 7.5
134 PatientHAI0000731 F 28 2010-12-29 7 2010-06-15 N05CF01 7.50 7.5
137 PatientHAI0000731 F 28 2010-12-29 15 2010-08-18 N05BA12 500.00 1.0
139 PatientHAI0000731 F 29 2012-02-12 42 2010-09-10 N05BA12 0.25 1.0
159 PatientHAI0000798 F 41 2011-08-31 14 2010-06-30 N05CF01 7.50 7.5
")
第二次df（路线）
routes<- read.table(header=T, text="hai_dispense_number sex hai_age quantity date_of_claim hai_atc hai_roa hai_strength hai_ddd eligibility_end_date
1 PatientHAI0217603 F 75 14 2010-04-16 N05BA12 O 0.25 1.00 2016-04-30
2 PatientHAI1614296 F 74 30 2010-04-28 N05CD06 O 1.00 1.00 2015-11-30
3 PatientHAI0408690 F 91 28 2010-04-15 N05BA12 O 0.25 1.00 2013-06-30
4 PatientHAI0050917 M 67 56 2010-04-15 N05BE01 O 10.00 30.00 2020-12-31
5 PatientHAI0143945 M 64 30 2010-04-14 N05BA01 O 5.00 10.00 2010-07-31
8 PatientHAI2149890 M 72 84 2010-04-27 N05BA08 O 1.50 10.00 2011-06-30
10 PatientHAI1903034 F 80 45 2010-04-01 N05CD07 O 20.00 20.00 2020-12-31
11 PatientHAI0205229 F 80 56 2010-04-22 N05CD07 O 20.00 20.00 2020-12-31
13 PatientHAI0317751 F 71 30 2010-04-26 N05CD05 O 0.25 0.25 2016-11-30
14 PatientHAI1986979 M 22 15 2010-04-19 N05BA01 O 10.00 10.00 2012-11-30
")
有关重复的其他信息：
在x中有些重复自然存在 - 这没关系 - 我需要保留这些。例如，见下面的最后两行
natural_dups<- read.table(header=T, text=" hai_dispense_number sex hai_age eligibility_end_date quantity date_of_claim hai_atc hai_strength hai_ddd
1597868 Patient HAI0002446 F 82 2011-08-31 42 2010-08-25 N05BA01 2 10
5495829 Patient HAI0002446 F 83 2011-08-31 30 2010-11-25 N05BA01 2 10
5580466 Patient HAI0002446 F 83 2011-08-31 30 2010-11-05 N05BA01 2 10
5686765 Patient HAI0002446 F 83 2011-08-31 30 2010-12-22 N05BA01 2 10
6146708 Patient HAI0002446 F 83 2011-08-31 30 2011-02-23 N05BA01 2 10
6351254 Patient HAI0002446 F 83 2013-05-31 28 2011-03-23 N05BA01 2 10
6686613 Patient HAI0002446 F 83 2013-05-31 28 2011-05-20 N05BA01 2 10
6686620 Patient HAI0002446 F 83 2013-05-31 28 2011-05-20 N05BA01 2 10
")
但是，在合并之后，这里添加了一个额外的第三行
merged_dups<- read.table(header=T, text=" hai_dispense_number hai_age sex date_of_claim quantity hai_ddd hai_strength eligibility_end_date hai_atc hai_roa
184 Patient HAI0002446 83 F 2011-05-20 28 10 2 2013-05-31 N05BA01 O
185 Patient HAI0002446 83 F 2011-05-20 28 10 2 2013-05-31 N05BA01 O
186 Patient HAI0002446 83 F 2011-05-20 28 10 2 2013-05-31 N05BA01 O
")