比较列字符下一行

Question

我的数据是：

Name House Street Apt City Postal Phone 
Bob Joe  954 BLUE DRIVE NA A PLACE Z5K4N2 999-495-6544 
Smith Jane 555 BLUE DRIVE NA A PLACE Z5K4N5 999-435-6172 
Smith Jane 555 BLUE DRIVE NA A PLACE Z5K4N5 999-450-6763 

我想比较名称（动态，数据由众议院排序），如果相等，房子＃是平等的，拼接的相应两个电话号码并删除未连接的行。

所以它看起来像这样经过：

我尝试

Name House Street  Apt City Postal Phone 
Bob Joe  954 BLUE DRIVE NA A PLACE Z5K4N2 999-495-6544 
Smith Jane 555 BLUE DRIVE NA A PLACE Z5K4N5 999-435-6172 OR 999-450-6763  

：

for(x in 1:nrow(data)) { 

    if(data$Name[x] == data$Name[x+1]) { 
    data$NameDupes <- data$Name[x] } 
} 

然后使用后

aggregate: aggregate(Phone ~ Name + Street + City + Postal + Apt + House, data = df, paste, collapse = " OR ") 

，然后在此之后，使用连接上我原来的df。

开放的思想

感谢

Answer 1

从dplyr一个解决方案。

library(dplyr) 

dt2 <- dt %>% 
    group_by(House, Street, Apt, City, Postal) %>% 
    summarise(Name = first(Name), Phone = paste(Phone, collapse = " OR ")) %>% 
    ungroup() %>% 
    arrange(desc(House)) %>% 
    select(colnames(dt)) 
dt2 
# A tibble: 2 x 7 
     Name House  Street Apt City Postal      Phone 
     <chr> <int>  <chr> <lgl> <chr> <chr>      <chr> 
1 Bob Joe 954 BLUE DRIVE NA A PLACE Z5K4N2     999-495-6544 
2 Smith Jane 555 BLUE DRIVE NA A PLACE Z5K4N5 999-435-6172 OR 999-450-6763 

DATA

dt <- read.table(text = "Name House Street Apt City Postal Phone 
'Bob Joe'  954 'BLUE DRIVE' NA 'A PLACE' Z5K4N2 '999-495-6544' 
'Smith Jane' 555 'BLUE DRIVE' NA 'A PLACE' Z5K4N5 '999-435-6172' 
'Smith Jane' 555 'BLUE DRIVE' NA 'A PLACE' Z5K4N5 '999-450-6763'", 
header = TRUE, stringsAsFactors = FALSE) 

Answer 2

不同的答案比@ycw的......使用data.table。 （因为我是包装的粉丝）。

使用数据

dt <- read.table(text = "Name House Street Apt City Postal Phone 
'Bob Joe'  954 'BLUE DRIVE' NA 'A PLACE' Z5K4N2 '999-495-6544' 
'Smith Jane' 555 'BLUE DRIVE' NA 'A PLACE' Z5K4N5 '999-435-6172' 
'Smith Jane' 555 'BLUE DRIVE' NA 'A PLACE' Z5K4N5 '999-450-6763'", 
header = TRUE, stringsAsFactors = FALSE) 

我们执行一个伟大的班轮

library(data.table) 
dt = as.data.table(dt) 
dt[,.(Phone = paste(Phone,collapse = " OR ")),by = .(Name,House,Street,Apt,City,Postal)] 

输出

 Name House  Street Apt City Postal      Phone 
1: Bob Joe 954 BLUE DRIVE NA A PLACE Z5K4N2     999-495-6544 
2: Smith Jane 555 BLUE DRIVE NA A PLACE Z5K4N5 999-435-6172 OR 999-450-6763