I have a large database made up of mixed data types (numeric, character, factor, ordinal factor) with missing values, and I am trying to create a for loop to substitute the missing values using either the mean of the respective column if numerical or the mode if character/factor.
This is what I have until now:
#fake array:
age<- c(5,8,10,12,NA)
a <- factor(c("aa", "bb", NA, "cc", "cc"))
b <- c("banana", "apple", "pear", "grape", NA)
df_test <- data.frame(age=age, a=a, b=b)
df_test$b <- as.character(df_test$b)
for (var in 1:ncol(df_test)) {
if (class(df_test[,var])=="numeric") {
df_test[is.na(df_test[,var]) <- mean(df_test[,var], na.rm = TRUE)
} else if (class(df_test[,var]=="character") {
Mode(df_test$var[is.na(df_test$var)], na.rm = TRUE)
}
}
Where 'Mode' is the function:
Mode <- function (x, na.rm) {
xtab <- table(x)
xmode <- names(which(xtab == max(xtab)))
if (length(xmode) > 1)
xmode <- ">1 mode"
return(xmode)
}
It seems as it is just ignoring the statements though, without giving any error… I have also tried to work the first part out with indexes:
## create an index of missing values
index <- which(is.na(df_test)[,1], arr.ind = TRUE)
## calculate the row means and "duplicate" them to assign to appropriate cells
df_test[index] <- colMeans(df_test, na.rm = TRUE) [index["column",]]
But I get this error: "Error in colMeans(df_test, na.rm = TRUE) : 'x' must be numeric"
Does anybody have any idea how to solve this?
Thank you very much for all the great help! -f
If you simply remove the obvious bugs then it works as intended:
Mode <- function (x, na.rm) {
xtab <- table(x)
xmode <- names(which(xtab == max(xtab)))
if (length(xmode) > 1) xmode <- ">1 mode"
return(xmode)
}
# fake array:
age <- c(5, 8, 10, 12, NA)
a <- factor(c("aa", "bb", NA, "cc", "cc"))
b <- c("banana", "apple", "pear", "grape", NA)
df_test <- data.frame(age=age, a=a, b=b)
df_test$b <- as.character(df_test$b)
print(df_test)
# age a b
# 1 5 aa banana
# 2 8 bb apple
# 3 10 <NA> pear
# 4 12 cc grape
# 5 NA cc <NA>
for (var in 1:ncol(df_test)) {
if (class(df_test[,var])=="numeric") {
df_test[is.na(df_test[,var]),var] <- mean(df_test[,var], na.rm = TRUE)
} else if (class(df_test[,var]) %in% c("character", "factor")) {
df_test[is.na(df_test[,var]),var] <- Mode(df_test[,var], na.rm = TRUE)
}
}
print(df_test)
# age a b
# 1 5.00 aa banana
# 2 8.00 bb apple
# 3 10.00 cc pear
# 4 12.00 cc grape
# 5 8.75 cc >1 mode
I recommend that you use an editor with syntax highlighting and bracket matching, which would make it easier to find these sorts of syntax errors.
来源:https://stackoverflow.com/questions/7731192/replace-mean-or-mode-for-missing-values-in-r