How to Convert Data.Frame Column from Factor to Numeric

How to convert data.frame column from Factor to numeric

breast$class <- as.numeric(as.character(breast$class))

If you have many columns to convert to numeric

indx <- sapply(breast, is.factor)
breast[indx] <- lapply(breast[indx], function(x) as.numeric(as.character(x)))

Another option is to use stringsAsFactors=FALSE while reading the file using read.table or read.csv

Just in case, other options to create/change columns

 breast[,'class'] <- as.numeric(as.character(breast[,'class']))

 breast <- transform(breast, class=as.numeric(as.character(breast)))

How to convert a data frame column to numeric type?

Since (still) nobody got check-mark, I assume that you have some practical issue in mind, mostly because you haven't specified what type of vector you want to convert to numeric. I suggest that you should apply transform function in order to complete your task.

Now I'm about to demonstrate certain "conversion anomaly":

# create dummy data.frame
d <- data.frame(char = letters[1:5], 
                fake_char = as.character(1:5), 
                fac = factor(1:5), 
                char_fac = factor(letters[1:5]), 
                num = 1:5, stringsAsFactors = FALSE)

Let us have a glance at data.frame

> d
  char fake_char fac char_fac num
1    a         1   1        a   1
2    b         2   2        b   2
3    c         3   3        c   3
4    d         4   4        d   4
5    e         5   5        e   5

and let us run:

> sapply(d, mode)
       char   fake_char         fac    char_fac         num 
"character" "character"   "numeric"   "numeric"   "numeric" 
> sapply(d, class)
       char   fake_char         fac    char_fac         num 
"character" "character"    "factor"    "factor"   "integer"

Now you probably ask yourself "Where's an anomaly?" Well, I've bumped into quite peculiar things in R, and this is not the most confounding thing, but it can confuse you, especially if you read this before rolling into bed.

Here goes: first two columns are character. I've deliberately called 2^nd one fake_char. Spot the similarity of this character variable with one that Dirk created in his reply. It's actually a numerical vector converted to character. 3^rd and 4^th column are factor, and the last one is "purely" numeric.

If you utilize transform function, you can convert the fake_char into numeric, but not the char variable itself.

> transform(d, char = as.numeric(char))
  char fake_char fac char_fac num
1   NA         1   1        a   1
2   NA         2   2        b   2
3   NA         3   3        c   3
4   NA         4   4        d   4
5   NA         5   5        e   5
Warning message:
In eval(expr, envir, enclos) : NAs introduced by coercion

but if you do same thing on fake_char and char_fac, you'll be lucky, and get away with no NA's:

> transform(d, fake_char = as.numeric(fake_char), 
               char_fac = as.numeric(char_fac))

  char fake_char fac char_fac num
1    a         1   1        1   1
2    b         2   2        2   2
3    c         3   3        3   3
4    d         4   4        4   4
5    e         5   5        5   5

If you save transformed data.frame and check for mode and class, you'll get:

> D <- transform(d, fake_char = as.numeric(fake_char), 
                    char_fac = as.numeric(char_fac))

> sapply(D, mode)
       char   fake_char         fac    char_fac         num 
"character"   "numeric"   "numeric"   "numeric"   "numeric" 
> sapply(D, class)
       char   fake_char         fac    char_fac         num 
"character"   "numeric"    "factor"   "numeric"   "integer"

So, the conclusion is: Yes, you can convert character vector into a numeric one, but only if it's elements are "convertible" to numeric. If there's just one character element in vector, you'll get error when trying to convert that vector to numerical one.

And just to prove my point:

> err <- c(1, "b", 3, 4, "e")
> mode(err)
[1] "character"
> class(err)
[1] "character"
> char <- as.numeric(err)
Warning message:
NAs introduced by coercion 
> char
[1]  1 NA  3  4 NA

And now, just for fun (or practice), try to guess the output of these commands:

> fac <- as.factor(err)
> fac
???
> num <- as.numeric(fac)
> num
???

Kind regards to Patrick Burns! =)

Converting a dataframe from factors to numerical creates all NA's

Sticking to the last approach of the OP; the function used to convert the NA's needs to be replaced with an, albeit less efficient, function that can deal with NA's, which is;

as.numeric(as.character(x))

The code then becomes:

df <- as.data.frame(df)
as.numeric.factor <- function(x) {as.numeric(as.character(x))}
df[] = lapply(df, as.numeric.factor) 
df[df < 0] <- NA
df <- df[,colMeans(is.na(df)) <= 0.999]
df <- data.table(df)
cols = sapply(df, is.numeric)
cols = names(cols)[cols]
dfclevel = df[, lapply(.SD, mean, na.rm=TRUE), .SDcols = cols, by=matchcode]

Convert from factor to numeric a column in data.frames within a list

I think the problem is that your function in your second lapply is only returning the vector of the numeric factor levels, not your entire data.frame. I believe the following should work:

foo <- function(y) {
  y$Var1 <- as.numeric(levels(y$Var1))[y$Var1]
  return(y)
}

lst_table <- lapply(lst_table, foo)

R: How to convert factors into numeric for a DATA FRAME?

We can try

 yourdat[] <- lapply(yourdat, function(x) if(is.factor(x)) as.numeric(levels(x))[x]
                              else x)

convert factor and character to numeric in a dataframe

It would help to have some example data to work with, but try:

df$your_factor_variable_now_numeric <- 
                as.numeric(as.character(df$your_old_factor_variable))

And use it only to convert a factor variable, not the complete dataframe. You can also have a look at type.convert. If you want to convert all factors in the dataframe, you can use something along the lines

 df[] <- lapply(df, function(x) as.numeric(as.character(x)))

Note that this converts all factors and might not be what you want if you have factors that do not represent numeric values. If unnecessary conversion is a problem, or if there are non-numeric factors or characters in the data, the following would be appropriate:

 numerify <- function(x) if(is.factor(x)) as.numeric(as.character(x)) else x
 df[] <- lapply(df, numerify)

On a more general point though, the type of your variables should not prevent you from filtering, if, with filtering, you mean subsetting the dataframe. However, the type conversion should be solved with the above code.

Convert factor to numeric in data frame

One way of doing this:

tbl_alles[sapply(tbl_alles, is.factor)] <- lapply(tbl_alles[sapply(tbl_alles, is.factor)], function(x) as.numeric(as.character(x)))

This function will look up columns of type factor and convert them to class numeric

Another option (maybe a bit faster) is using data.table package

library(data.table)
setDT(tbl_alles)[, names(tbl_alles) := lapply(.SD, function(x) if(is.factor(x)) as.numeric(as.character(x)) else x)]

If your whole data set is of type factor and you want to transfer all the columns to numeric type, you could do

tbl_alles[] <- lapply(tbl_alles, function(x) as.numeric(as.character(x)))

Convert multiple columns from factor to numeric but obtaining NAs in R

as.character/as.numeric expects a vector as input. With df[, cols] you are passing a dataframe to it (check class(df[, cols])).

If you are talking about the accepted answer in the link it says to change the code in for loop and doesn't suggest to pass entire dataframe. To change class of multiple columns you can use for loop, apply or lapply.

df[cols] <- lapply(df[cols], function(x) as.numeric(as.character(x)))

How to Convert Data.Frame Column from Factor to Numeric