如何根据 R 中的记录标识符分配唯一 ID?

How can I assign unique IDs based on a record identifier in R?

我的任务:根据电影数据统计预算和收入数字。

我正在从基本上采用以下格式的文本文件中读取数据:

MV,Movie 1 Name
BT,Budget for Movie 1
GR,Gross Revenue Movie 1

但数据可能包含也可能不包含BT或GR,或者有时包含倍数,例如:

MV,Movie1
BT,1000000
GR,500000 (week1)
GR,500000 (week2)
GR,500000 (week3)
GR,500000 (week1)
MV,Movie2
BT,10000
GR,50000 (week1)
GR,500000 (week2)
MV,Movie3
MV,Movie4
BT,1000000

我想要创建的数据框如下所示:

mID  recType  recData
  1  MV       Movie1
  1  BT       1000000
  1  GR       500000 (week1)
  1  GR       500000 (week2)
  1  GR       500000 (week3)
  1  GR       500000 (week1)
  2  MV       Movie2
  2  BT       10000
  2  GR       50000 (week1)
  2  GR       500000 (week2)
  3  MV       Movie3
  4  MV       Movie4
  4  BT       1000000

我的程序员说只需在 java 或 .NET 中编写一个数据清理应用程序,以便在将数据引入 R 之前清理数据,但我想看看互联网可以帮助我。

为超过 90,000 部电影为此编写一个循环,处理时间长得令人讨厌。

注意:最终目标是将此数据用作对电影盈利能力进行分类的主要来源,并将其与流派、演员和其他数据的外部文件进行交叉引用。

(IMDB 需要更好的数据设置)

谢谢!

尝试

df1$mID <- cumsum(grepl('^Movie', df1$recData))
#df1$mID <- cumsum(df1$recType=='MV')
df1[,c(3,1:2)]
#   mID recType        recData
#1    1      MV         Movie1
#2    1      BT        1000000
#3    1      GR 500000 (week1)
#4    1      GR 500000 (week2)
#5    1      GR 500000 (week3)
#6    1      GR 500000 (week1)
#7    2      MV         Movie2
#8    2      BT          10000
#9    2      GR  50000 (week1)
#10   2      GR 500000 (week2)
#11   3      MV         Movie3
#12   4      MV         Movie4
#13   4      BT        1000000

或使用data.table(会更快)

library(data.table)
setDT(df1)[, mID:= cumsum(recType=='MV')][]