keyUpdate {kutils}

Update a key in light of a new data frame (add variables and values)

Description

The following chores must be handled. 1. If the data.frame has variables which are not currently listed in the variable key's "name_old" variable, then new variables are added to the key. 2. If the data.frame has new values for the previously existing variables, then those values must be added to the keys. 3. If the old key has "name_new" or "class_new" designated for variables, those MUST be preserved in the new key for all new values of those variables.

Usage

keyUpdate(key, dframe, append = TRUE, safeNumericToInteger = TRUE)

Arguments

key

A variable key

dframe

A data.frame object.

append

If long key, should new rows be added to the end of the updated key? Default is TRUE. If FALSE, new rows will be sorted with the original values.

safeNumericToInteger

Default TRUE: Should we treat variables which appear to be integers as integers? In many csv data sets, the values coded c(1, 2, 3) are really integers, not floats c(1.0, 2.0, 3.0). See safeInteger. ## Need to consider implementing this: ## @param ignoreCase

Details

This function will not alter key values for "class_old", "value_old" or "value_new" for variables that have no new information.

This function deduces if the key provided is in the wide or long format from the class of the object.

Value

Updated variable key.

Author(s)

Ben Kite <[e-mail]>

Examples

## Original data frame has 2 variables
dat1 <- data.frame("Score" = c(1, 2, 3, 42, 4, 2),
                   "Gender" = c("M", "M", "M", "F", "F", "F"))
## New data has all of original dat1, plus a new variable "Weight"
#and has new values for "Gender" and "Score"
dat2 <- plyr::rbind.fill(dat1, data.frame("Score" = 7,
           "Gender" = "other", "Weight" = rnorm(3)))
## Create a long key for the original data, specify some
## recodes for Score and Gender in value_new
key1.long <- keyTemplate(dat1, long = TRUE, varlab = TRUE)

key1.long$value_new <- gsub("42", "10", key1.long$value_new)
key1.long$value_new[key1.long$name_new == "Gender"] <-
       mgsub(c("F", "M"), c("female", "male"),
       key1.long$value_new[key1.long$name_new == "Gender"])  
key1.long[key1.long$name_old == "Score", "name_new"] <- "NewScore"
keyUpdate(key1.long, dat2, append = TRUE)
## Throw away one row, make sure key still has Score values
dat2 <- dat2[-1,]
(key1.long.u <- keyUpdate(key1.long, dat2, append = FALSE))
## Key change Score to character variable
key1.longc <- key1.long
key1.longc[key1.longc$name_old == "Score", "class_new"] <- "character"
keyUpdate(key1.longc, dat2, append = TRUE)
str(dat3 <- keyApply(dat2, key1.longc))
## Now try a wide key
key1.wide <- keyTemplate(dat1)
## Put in new values, same as in key1.long
key1.wide[key1.wide$name_old == "Score", c("name_new", "value_new")] <-
                            c("NewScore", "1|2|3|4|10|.")
key1.wide[key1.wide$name_old == "Gender", "value_new"] <- "female|male|."
## Make sure key1.wide equivalent to key1.long:
## If this is not true, it is a fail
all.equal(long2wide(key1.long), key1.wide, check.attributes = FALSE)
(key1.wide.u <- keyUpdate(key1.wide, dat2))
key1.long.to.wide <- long2wide(key1.long.u)
all.equal(key1.long.to.wide, key1.wide.u, check.attributes = FALSE)
str(keyApply(dat2, key1.wide.u))

mydf.key.path <- system.file("extdata", "mydf.key.csv", package = "kutils")
mydf.key <-  keyImport(mydf.key.path)
##'
set.seed(112233)
N <- 20
## The new Jan data arrived!
mydf2 <- data.frame(x5 = rnorm(N),
                    x4 = rpois(N, lambda = 3),
                    x3 = ordered(sample(c("lo", "med", "hi"),
                                       size = N, replace=TRUE),
                                levels = c("med", "lo", "hi")),
                    x2 = letters[sample(c(1:4,6), N, replace = TRUE)],
                    x1 = factor(sample(c("jan"), N, replace = TRUE)),
                    x7 = ordered(letters[sample(c(1:4,6), N, replace = TRUE)]),
                    x6 = sample(c(1:5), N, replace = TRUE),
                    stringsAsFactors = FALSE)
mydf.key2 <- keyUpdate(mydf.key, mydf2)
mydf.key2
mydf.key2["x1", "value_old"] <- "cindy|bobby|jan|peter|marcia|greg|."
mydf.key2["x1", "value_new"] <- "Cindy<Bobby<Jan<Peter<Marcia<Greg<."
##'
mydf.key.path <- system.file("extdata", "mydf.key.csv", package = "kutils")
mydf.path <- system.file("extdata", "mydf.csv", package = "kutils")
mydf <- read.csv(mydf.path, stringsAsFactors=FALSE)
mydf3 <- rbind(mydf, mydf2)
## Now recode with revised key
mydf4 <- keyApply(mydf3, mydf.key2)
rockchalk::summarize(mydf4)