将值从宽更改为长：1）Group_By，2）传播/Dcast [重复]答案

【问题标题】：Changing Values from Wide to Long: 1) Group_By, 2) Spread/Dcast [duplicate]将值从宽更改为长：1）Group_By，2）传播/Dcast [重复]
【发布时间】：2018-08-18 02:14:24
【问题描述】：

我有一个电话号码名称列表，我想按名称对其进行分组，并将它们从长格式变为宽格式，并在各列中填充电话号码

Name        Phone_Number
John Doe     0123456   
John Doe     0123457    
John Doe     0123458    
Jim Doe      0123459
Jim Doe      0123450    
Jane Doe     0123451
Jill Doe     0123457

Name        Phone_Number1   Phone_Number2     Phone_Number3
John Doe     0123456        0123457           0123458
Jim Doe      0123459        0123450           NA
Jane Doe     0123451        NA                NA    
Jill Doe     NA             NA                NA

library(dplyr)
library(tidyr)
library(data.table)

df <- data.frame(Name = c("John Doe", "John Doe", "John Doe", "Jim Doe", "Jim Doe", "Jane Doe", "Jill Doe" ), 
             Phone_Number = c("0123456", "0123457","0123458", "0123459", "0123450","0123451", NA))

df1 <- data.frame(Name = c("John Doe","Jim Doe", "Jane Doe", "Jill Doe" ), 
              Phone_Number1 = c("0123456", "0123459", "0123451", NA),
              Phone_Number2 = c("0123457", "0123450", NA, NA),
              Phone_Number3 = c("0123458", NA, NA, NA))

我尝试了一系列排列，但我做错的只是没有点击。我猜这与如何正确指定它们的键/值对有关。我得到的最接近的是下面的代码：

tidyr::spread

  df %>%
   group_by(Name) %>%
   mutate(id = row_number()) %>%
   spread(Name, Phone_Number) %>%
   select(-id)

data.table::dcast

 df%>% 
  dcast(Name + Phone_Number  ~ Phone_Number, value.var = "Phone_Number")

【问题讨论】：

标签： r data.table reshape tidyr reshape2

【解决方案1】：

为了完整起见，rowid() 函数有一个 prefix 参数，它给出了一个简洁的解决方案：

library(data.table)
dcast(setDT(df), Name ~ rowid(Name, prefix = "Phone_Number"))

       Name Phone_Number1 Phone_Number2 Phone_Number3
1: Jane Doe       0123451          <NA>          <NA>
2: Jill Doe          <NA>          <NA>          <NA>
3:  Jim Doe       0123459       0123450          <NA>
4: John Doe       0123456       0123457       0123458

【讨论】：

【解决方案2】：

您不想添加行号（整个数据的索引），而是使用辅助函数 n() 添加组索引，该函数表示grouped_df 中每个组中的观察数。那么传播应该会顺利...

df %>% group_by(Name) %>%
  mutate(group_index = 1:n() %>% paste0("phone_", .)) %>%
  spread(group_index, Phone_Number)

# A tibble: 4 x 4
# Groups:   Name [4]
 Name phone_1 phone_2 phone_3
 <fctr>  <fctr>  <fctr>  <fctr>
1 Jane Doe 0123451    <NA>    <NA>
2 Jill Doe    <NA>    <NA>    <NA>
3  Jim Doe 0123459 0123450    <NA>
4 John Doe 0123456 0123457 0123458

【讨论】：

【解决方案3】：

通过Name创建一个rowid，这就足够了

library(dplyr)
library(tidyr)
library(data.table)

df <- setDT(data.frame(Name = c("John Doe", "John Doe", "John Doe", "Jim Doe", "Jim Doe", "Jane Doe", "Jill Doe" ), 
                 Phone_Number = c("0123456", "0123457","0123458", "0123459", "0123450","0123451", NA)))

df1 <- data.frame(Name = c("John Doe","Jim Doe", "Jane Doe", "Jill Doe" ), 
                  Phone_Number1 = c("0123456", "0123459", "0123451", NA),
                  Phone_Number2 = c("0123457", "0123450", NA, NA),
                  Phone_Number3 = c("0123458", NA, NA, NA))

df[, rowid := rowid(Name)]
dcast.data.table(df, Name ~ rowid, value.var = "Phone_Number")

       Name       1       2       3
1: Jane Doe 0123451      NA      NA
2: Jill Doe      NA      NA      NA
3:  Jim Doe 0123459 0123450      NA
4: John Doe 0123456 0123457 0123458

正如 cmets 中所指出的，无需为任务创建 rowdi 变量。你可以做如下，更简单整洁的代码

df <- setDT(data.frame(Name = c("John Doe", "John Doe", "John Doe", "Jim Doe", "Jim Doe", "Jane Doe", "Jill Doe" ), 
                       Phone_Number = c("0123456", "0123457","0123458", "0123459", "0123450","0123451", NA)))

dcast.data.table(df, Name ~ paste0("Phone_Number", rowid(Name)), 
                 value.var = "Phone_Number")

       Name Phone_Number1 Phone_Number2 Phone_Number3
1: Jane Doe       0123451            NA            NA
2: Jill Doe            NA            NA            NA
3:  Jim Doe       0123459       0123450            NA
4: John Doe       0123456       0123457       0123458

【讨论】：