Azure ML and r scripts

Question

I have dataframe with columns

date    open    high    low     close   adjclose    volume

I want to add one more column named "result"(1 if close > open, 0 if close < open)

I do

# Map 1-based optional input ports to variables
data <- maml.mapInputPort(1) # class: data.frame



# calculate pass/fail
data$result <- as.factor(sapply(data$close,function(res) 
    if (res - data$open >= 0) '1' else '0'))

# Select data.frame to be sent to the output Dataset port
maml.mapOutputPort("data");

But I have only 1 in result. Where is the problem?

Answer 1

The if/else can return only a single TRUE/FALSE and is not vectorized for length > 1. It may be suitable to use ifelse (but that is also not required and would be less efficient compared to direct coersion of logical vector to binary ( as.integer ). In the OP's code, the 'close' column elements are looped ( sapply ) and subtracted from the whole 'open' column. The intention might be to do elementwise subtraction. In that case, - between the columns is much cleaner and efficient (as these operations are vectorized)

data$result <- with(data, factor(as.integer((close - open) >= 0)))

In the above, we get the difference between the columns ('close', 'open'), check if it is greater than or equal to 0 (returns logical vector), convert it to binary ( as.integer - TRUE -> 1, FALSE -> 0) and then change it to factor type (if needed)