Data cleaning of dollar values and percentage in R

Question

I\'ve been searching for a number of packages in R to help me in converting dollar values to nice numerical values. I don\'t seem to be able to find one (in plyr package for

Answer 1

One thing that makes R different from other languages you might be used to is that it's better to do things in a "vectorized" way, to operate on a whole vector at a time rather than looping through each individual value. So your dollarToNumber function can be rewritten without the for loop:

dollarToNumber_vectorised <- function(vector) {
  # Want the vector as character rather than factor while
  # we're doing text processing operations
  vector <- as.character(vector)
  vector <- gsub("(\\$|,)","", vector)
  # Create a numeric vector to store the results in, this will give you
  # warning messages about NA values being introduced because the " K" values
  # can't be converted directly to numeric
  result <- as.numeric(vector)
  # Find all the "$N K" values, and modify the result at those positions
  k_positions <- grep(" K", vector)
  result[k_positions] <- as.numeric(gsub(" K","", vector[k_positions])) * 1000
  # Same for the "$ M" value
  m_positions <- grep(" M", vector)
  result[m_positions] <- as.numeric(gsub(" M","", vector[m_positions])) * 1000000
  return(result)
}

It still gives the same output as your original function:

> dollarToNumber_vectorised(allProjects$LiveDollars)
 [1] 3100000 3970000 3020000 1760000 4510000  762650  510860  823370  218590  865940
[11]  587670  221110   71934
# Don't worry too much about this warning
Warning message:
In dollarToNumber_vectorised(allProjects$LiveDollars) :
  NAs introduced by coercion
> dollarToNumber(allProjects$LiveDollars)
 [1] 3100000 3970000 3020000 1760000 4510000  762650  510860  823370  218590  865940
[11]  587670  221110   71934