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
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Best regards, Luigi