在使用pivot_wider转换数据时如何排除重复观察？

Question

我目前正在处理一个数据项目，需要压缩数据，以便数据框中的名称不重复。问题是某些数据行重复。下面我附上了一个示例数据框：

df_have <- data.frame(
  Name = c("Maya", "Maya", "Maya," "Sierra", "Sophia", "Sophia", "Sophia", 
           "Sophia", "Cecilia", "Cecilia"),
  ID = c(24, 56, 24, 54, 12, 12, 15, 24, 12, 11)
)

这是所需的数据框：

df_want <- data.frame(
  Name = c("Maya", "Sierra", "Sophia", "Cecilia"),
  ID1 = c(24, 54, 12, 12),
  ID2 = c(56, 0, 15, 11),
  ID3 = c(0, 0, 24, 0)
)

我之前发布过一个与此非常相似的问题。由此看来，我当前对数据执行的转换如下：

ids |>
  mutate(idno = row_number(), .by = Name) |>
  pivot_wider(
    values_from = ID,
    names_from = idno,
    values_fill = 0,
    names_prefix = "ID"
  )

但是，这并不排除重复值。我正在使用 R 来转换数据。里面唯一的命令

pivot_wider 

我所熟悉的重复项仅适用于列名称，而不适用于条目本身。另外，我已经尝试过

duplicated 

命令，但这删除了所有重复项，而不仅仅是所需的重复项。预先感谢您的帮助。

Answer 1

您关于使用不同的评论是扭曲的，显然没有意义，因为它产生的数据正是您声明想要的数据。 您的示例是否不能完全代表您的问题？

df_have <- data.frame(
  Name = c("Maya", "Maya", "Maya", "Sierra", "Sophia", "Sophia", "Sophia", 
           "Sophia", "Cecilia", "Cecilia"),
  ID = c(24, 56, 24, 54, 12, 12, 15, 24, 12, 11)
)
# And here is the desired data frame:
  
  (df_want <- tibble(
    Name = c("Maya", "Sierra", "Sophia", "Cecilia"),
    ID1 = c(24, 54, 12, 12),
    ID2 = c(56, 0, 15, 11),
    ID3 = c(0, 0, 24, 0)
  ))
# I previously posted a question very similar to this. From that, the transformation I am currently performing on the data is as follows:
  
  df_result <- df_have |> distinct() |> 
  mutate(idno = row_number(), .by = Name) |>
  pivot_wider(
    values_from = ID,
    names_from = idno,
    values_fill = 0,
    names_prefix = "ID"
  )
  
  identical(df_want,df_result)

Answer 2

否则，快速循环可以工作

df_have$ID_names <- 1

for(i in 2:nrow(df_have)){
  
  if(df_have[i,1]!=df_have[i-1,1]){
    
    df_have[i,3] <- 1
    
  }else {df_have[i,3] <- df_have[i-1,3]+1
  }

}

df_have$ID_names <- paste("ID",df_have$ID_names,sep="")

library(tidyr)
df_want <- spread(df_have,key = ID_names,value = ID)
df_want[is.na(df_want)] <- 0