R：基于3列制作数据透视表[transpose]

I have this dataframe (df):

我有这个数据帧（df）：

ID  Type  Order Revenue
1   apples  1    $100
1   oranges 2    $100 
2   grapes  1    $500
2   oranges 2    $500
2   grapes  3    $500
2   grapes  4    $500

I want to transpose it to get this dataframe, where the column headers are the "order" column from the original data frame:

我想转置它以获取此数据帧，其中列标题是原始数据框中的“顺序”列：

ID   1       2      3      4     Revenue
1  apples oranges                  $100 
2  grapes oranges grapes grapes    $500

I tried dcast(df, df$ID, df$Order)

我试过dcast（df，df $ ID，df $ Order）

But that doesn't give me what I'm looking for. It gives me the order within the dataframe itself, like this:

但这并没有给我我正在寻找的东西。它给了我数据框本身的顺序，如下所示：

   ID   1   2   3   4
    1   1   2
    2   1   2   3   4 

I basically want the "type" to be populated within the dataframe, given a particular ID and order (this combination is unique.)

我基本上希望在给定特定ID和顺序的情况下在数据框中填充“类型”（这种组合是唯一的。）

Thanks so much in advance!!

非常感谢提前!!

EDIT: I would like the revenue column to be added while using dcast

编辑：我想在使用dcast时添加收入列

1 个解决方案

#1

dcast takes a formula as its second argument. So, you need to provide that along with the value column that needs to fill up the 'wide' format. In this case, the `value.var' is 'Type'

dcast将公式作为第二个参数。因此，您需要提供需要填充“宽”格式的值列。在这种情况下，`value.var'是'Type'

library(reshape2)
dcast(df, ID~Order, value.var='Type', fill='')
#   ID      1       2      3      4
#1  1 apples oranges              
#2  2 grapes oranges grapes grapes

Or you can use spread which takes the argument similar to as showed in your post

或者您可以使用带有与您帖子中显示的类似的参数的spread

library(tidyr)
spread(df, Order, Type, fill='')

Update

For the updated dataset, change the 'formula'

对于更新的数据集，请更改“公式”

  dcast(dfN, ID+Revenue~Order, value.var='Type', fill='')
  #  ID Revenue      1       2      3      4
  #1  1    $100 apples oranges              
  #2  2    $500 grapes oranges grapes grapes

data

df <- structure(list(ID = c(1L, 1L, 2L, 2L, 2L, 2L), Type = c("apples", 
"oranges", "grapes", "oranges", "grapes", "grapes"), Order = c(1L, 
2L, 1L, 2L, 3L, 4L)), .Names = c("ID", "Type", "Order"),
 class =  "data.frame", row.names = c(NA, -6L))