I have one categorical variable of string type in my dataset. I need to convert it to numerical value for further processing. I know standard way to represent categorical data is to use one-hot encoding. But that will convert each entry of the variable to a vector.
LabelEncoder of sklearn converts each entry to a scalar value. I realise this is a very naive and possibly stupid question but which representation is more commonly used and is there a reason for the bias?