dummy-data

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!!! You can use rowSums (vectorized solution) like this : set.seed(123) dat <- matrix(sample(c(35,1

I am looking for for a pythonic way to handle the following problem. The pandas.get_dummies() method is great to create dummies from a categorical column of a dataframe. For example, if the column has values in ['A', 'B'] , get_dummies() creates 2 dummy variables and assigns 0 or 1 accordingly. Now, I need to handle this situation. A single column, let's call it 'label', has values like ['A', 'B', 'C', 'D', 'A*C', 'C*D'] . get_dummies() creates 6 dummies, but I only want 4 of them, so that a row could have multiple 1s. Is there a way to handle this in a pythonic way? I could only think of some