我有一个客户贷款数据库，我想按LoanRefID进行ddply摘要:
LoanRefId Tran_Type TransactionAmount
103 11 LoanIssue 1000.0000
104 11 InitiationFee 171.0000
105 11 Interest 59.6729
106 11 AdministrationFee 64.9332
107 11 RaisedClientInstallment 1295.5757
108 11 ClientInstallment 1295.4700
109 11 PaidUp 0.0000
110 11 Adjustment 0.1361
111 11 PaidUp 0.0000
112 12 LoanIssue 3000.0000
113 12 InitiationFee 399.0000
114 12 Interest 94.9858
115 12 AdministrationFee 38.6975
116 12 RaisedClientInstallment 3532.6350
117 12 ClientInstallment 3532.6100
118 12 PaidUp 0.0000
119 12 Adjustment 0.0733
120 12 PaidUp 0.0000
但是，我只想对每个loanID只汇总某些行。具体来说，我只想总结Tran_Type ==“ClientInstallment”的位置。
我能想到的唯一方法(似乎不起作用)是:
> ddply(test, c("LoanRefId"), summarise, cash_in = sum(test[test$Tran_Type == "ClientInstallment","TransactionAmount"]))
LoanRefId cash_in
1 11 4828.08
2 12 4828.08
这不是每个LoanRefId的总和，仅是在Tran_Type ==“CLientInstallment”的所有金额之和，这是错误的。
有没有更好的方法来进行此逻辑求和？
最佳答案
有人可以添加plyr答案，但如今base R，dplyr或data.table更加广泛地使用。 plyr已更新和升级。值得花时间学习较新的实现，因为它们效率更高且具有很多功能。
基础R
aggregate(TransactionAmount ~ LoanRefId, df[df$Tran_Type == "ClientInstallment",], sum)
# LoanRefId TransactionAmount
#1 11 1295.47
#2 12 3532.61
dplyr
library(dplyr)
df %>%
group_by(LoanRefId) %>%
filter(Tran_Type == "ClientInstallment") %>%
summarise(TransactionAmount = sum(TransactionAmount))
#Source: local data frame [2 x 2]
#
# LoanRefId TransactionAmount
# (int) (dbl)
#1 11 1295.47
#2 12 3532.61
数据表
setDT(df)[Tran_Type == "ClientInstallment", sum(TransactionAmount), by=LoanRefId]
# LoanRefId V1
#1: 11 1295.47
#2: 12 3532.61
注意
data.table语法是多么干净:)。学习的好工具。