How to globally convert NaN to NA in dataframe?

`data[sapply(data, is.nan)] <- NA` is a nice compact command, but I
still get NaN when using the summary function, for instance one of the
columns give:
```
Min.   : NA
1st Qu.: NA
Median : NA
Mean   :NaN
3rd Qu.: NA
Max.   : NA
NA's   :110
```
I tried to implement the second solution but:
```
df <- lapply(x, function(xx) {
  xx[is.nan(xx)] <- NA
})

str(df)

List of 1
 $ sd_ef_rash_loc___palm: logi NA
```
What am I getting wrong?
Thanks

On Thu, Sep 2, 2021 at 3:30 PM Andrew Simmons <akwsimmo at gmail.com> wrote:

Hello,


I would use something like:


x <- c(1:5, NaN) |> sample(100, replace = TRUE) |> matrix(10, 10) |>

as.data.frame()

x[] <- lapply(x, function(xx) {
    xx[is.nan(xx)] <- NA_real_
    xx
})


This prevents attributes from being changed in 'x', but accomplishes the

same thing as you have above, I hope this helps!

On Thu, Sep 2, 2021 at 9:19 AM Luigi Marongiu <marongiu.luigi at gmail.com>

wrote:

Hello,
I have some NaN values in some elements of a dataframe that I would
like to convert to NA.
The command `df1$col[is.nan(df1$col)]<-NA` allows to work column-wise.
Is there an alternative for the global modification at once of all
instances?
I have seen from

https://stackoverflow.com/questions/18142117/how-to-replace-nan-value-with-zero-in-a-huge-data-frame/18143097#18143097

that once could use:
```

is.nan.data.frame <- function(x)
do.call(cbind, lapply(x, is.nan))

data123[is.nan(data123)] <- 0
```
replacing o with NA, but I got
```
str(df)

logi NA

```
when modifying my dataframe df.
What would be the correct syntax?
Thank you



--
Best regards,
Luigi