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How to Create a Single Dummy Variable with conditions in multiple columns?


I am trying to efficiently create a binary dummy variables (1/0) in my data set based on whether or not one or more of 7 variables (col9-15) in the data set take on a specific value (35), but I don't want to test all columns.

While as.numeric is ideal usually, I can only get it to work with one column at a time:

data$indicator <- as.numeric(data$col1 == 35)

Any idea how I can modify the above code so that if any of data$col9 - data$col15 are "35" then my indicator variable takes on a 1?

Thanks!!!


Solution

  • You can use rowSums (vectorized solution) like this :

    set.seed(123)
    dat <- matrix(sample(c(35,1:100),size=15*20,rep=T),ncol=15,byrow=T)
    cbind(dat,rowSums(dat[,9:15] == 35) > 0)
       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16]
     [1,]   29   79   41   89   94    4   53   90   55    46    96    45    68    57    10     0
     [2,]   90   24    4   33   96   89   69   64  100    66    71    54    60    29    14     0
     [3,]   97   91   69   80    2   48   76   21   32    23    14    41    41    37    15     0
     [4,]   14   23   47   26   86    4   44   80   12    56    20    12    76    90    37     0
     [5,]   67    9   38   27   82   45   81   82   80    44    76    63    71    35    48     1
     [6,]   22   38   61   35   11   24   67   42   79    10    43    99    90    89    17     0
     [7,]   13   65   34   66   32   18   79    9   47    51    60    33    49    96    48     0
     [8,]   89   92   61   41   14   94   30    6   95    72    14    55    96    59    40     0
     [9,]   65   32   31   22   37   99   15    9   14    69    62    90    67    74    52     0
    [10,]   66   83   79   98   44   31   41    1   18    85    23    24     7    24    73     0
    [11,]   85   50   39   24   11   39   57   21   44    22    50    35    65    37    35     1
    [12,]   53   74   22   41   26   63   18   87   75    67    62    37    53    88    58     0
    [13,]   84   31   71   26   60   48   26   57   92    91    27    32    99    62    94     0
    [14,]   47   41   66   15   57   24   97   60   52    40    88    36    29    17    17     0
    [15,]   48   25   21   68    4   70   35   41   82    92    28    97    73    69     5     0
    [16,]   39   48   56   70   92   62   43   54    5    26    40    19    84    15    81     0
    [17,]   55   66   17   63   31   73   40   97   97    73    25    22    59    27    53     0
    [18,]   79   16   40   47   87   93   89   68   95    52    58    33    35     2    50     1
    [19,]   87   35    7   16   77   74   98   47    7    65    76    13    40    22     5     0
    [20,]   39    6   22    5   67   30   10    7   88    76    82    99    10    10    80     0
    

    EDIT

    I replace the cbind by transform. Since the column will be boolean I coerce it to get 0/1.

     transform(dat,x=as.numeric((rowSums(dat[,9:15] == 35) > 0)))
    

    The result is a data.frame.( coerced from matrix by transform)

    EDIT2 ( as suggested by @flodel)

    data$indicator <- as.integer(rowSums(data[paste0("col", 9:15)] == 35) > 0)
    

    where data is the OP's data.frame.