对于那些习惯并喜欢data.table语法的人来说，一个（可能不是最佳的）版本可能看起来像这样：

library(data.table)

DT <- data.table(df)
setnames(DT,"Sender","User1")
DT <- dcast(DT[,User:=paste("User", .SD[,.I]), by=Operation],
            Operation + User1 + Action~ User, value.var="Recipient")
DT

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您可以使用pivot_wider来获取更宽格式的数据。

library(dplyr)

df %>%
  rename(User1 = Sender) %>%
  group_by(Operation) %>%
  mutate(col = paste0('User', row_number() + 1)) %>%
  tidyr::pivot_wider(names_from = col, values_from = Recipient) %>%
  select(Operation, User1, everything()) -> result

result

#  Operation  User1   Action User2      User3      User4     
#  <chr>      <chr>   <chr>  <chr>      <chr>      <chr>     
#1 Operation1 Sender1 Update Recipient3 Recipient6 Recipient5
#2 Operation2 Sender2 Update Recipient4 NA         NA        
#3 Operation3 Sender3 Update Recipient5 NA         NA        
#4 Operation4 Sender2 Delete Recipient3 Recipient6 NA        
#5 Operation5 Sender3 Delete Recipient4 NA         NA        
#6 Operation6 Sender1 Delete Recipient3 NA         NA

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数据

df <- structure(list(Sender = c("Sender1", "Sender2", "Sender3", "Sender1", 
"Sender2", "Sender3", "Sender1", "Sender2", "Sender1"), Action = c("Update", 
"Update", "Update", "Update", "Delete", "Delete", "Update", "Delete", 
"Delete"), Recipient = c("Recipient3", "Recipient4", "Recipient5", 
"Recipient6", "Recipient3", "Recipient4", "Recipient5", "Recipient6", 
"Recipient3"), Operation = c("Operation1", "Operation2", "Operation3", 
"Operation1", "Operation4", "Operation5", "Operation1", "Operation4", 
"Operation6")), class = "data.frame", row.names = c(NA, -9L))

型

使用reshape。

reshape(transform(dat, User.1=Sender, User=Recipient, 
                  x=ave(!is.na(Sender), Operation, FUN=cumsum) + 1), 
        v.names="User", timevar="x", idvar="Operation", 
        drop=c("Recipient", "Sender"), 
        direction="wide")
#   Action  Operation  User.1     User.2     User.3     User.4
# 1 Update Operation1 Sender1 Recipient3 Recipient6 Recipient5
# 2 Update Operation2 Sender2 Recipient4       <NA>       <NA>
# 3 Update Operation3 Sender3 Recipient5       <NA>       <NA>
# 5 Delete Operation4 Sender2 Recipient3 Recipient6       <NA>
# 6 Delete Operation5 Sender3 Recipient4       <NA>       <NA>
# 9 Delete Operation6 Sender1 Recipient3       <NA>       <NA>

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或reshape2::dcast。

reshape2::dcast(transform(dat, User.1=Sender, User=Recipient, 
                          Recipient=ave(!is.na(Sender), Operation, 
                      FUN=function(x) paste0("User.", cumsum(x) + 1))),
       ... ~ Recipient, value.var="User")[-1]
#   Action  Operation  User.1     User.2     User.3     User.4
# 1 Update Operation1 Sender1 Recipient3 Recipient6 Recipient5
# 2 Update Operation2 Sender2 Recipient4       <NA>       <NA>
# 3 Update Operation3 Sender3 Recipient5       <NA>       <NA>
# 5 Delete Operation4 Sender2 Recipient3 Recipient6       <NA>
# 6 Delete Operation5 Sender3 Recipient4       <NA>       <NA>
# 9 Delete Operation6 Sender1 Recipient3       <NA>       <NA>

型

• 数据 *

dat <- read.table(header=TRUE, text="Sender  Action  Recipient   Operation
Sender1 Update  Recipient3  Operation1
Sender2 Update  Recipient4  Operation2
Sender3 Update  Recipient5  Operation3
Sender1 Update  Recipient6  Operation1
Sender2 Delete  Recipient3  Operation4
Sender3 Delete  Recipient4  Operation5
Sender1 Update  Recipient5  Operation1
Sender2 Delete  Recipient6  Operation4
Sender1 Delete  Recipient3  Operation6")

型