Re: [R] Loop over columns of dataframe and change values condtionally
Hello,
In the particular case you have, to change to NA based on condition, use
`is.na<-`.
Here is some test data, 3 times the same df.
set.seed(2021)
df3 <- df2 <- df1 <- data.frame(
x = c(0, 0, 1, 2, 3),
y = c(1, 2, 3, 0, 0),
z = rbinom(5, 1, prob = c(0.25, 0.75)),
a = letters[1:5]
)
# change all columns
is.na(df1) <- df1 == 0
df1
# only one column
is.na(df2[, 2]) <- df2[, 2] == 0
df2
# change several columns given by an index
is.na(df3[c(1, 3)]) <- df3[c(1, 3)] == 0
df3
Hope this helps,
Rui Barradas
Às 14:35 de 02/09/21, Luigi Marongiu escreveu:
Hello,
it is possible to select the columns of a dataframe in sequence with:
```
for(i in 1:ncol(df)) {
df[ , i]
}
# or
for(i in 1:ncol(df)) {
df[ i]
}
```
And change all values with, for instance:
```
for(i in 1:ncol(df)) {
df[ , i] <- df[ , i] + 10
}
```
Is it possible to apply a condition? What would be the syntax?
For instance, to change all 0s in a column to NA would `df[i][df[i ==
0] = NA` be right?
Thank you
__
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Re: [R] Loop over columns of dataframe and change values condtionally
Hi
you could operate with whole data frame (sometimes)
head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
chenge all
> head(iris[,1:4]+10)
Sepal.Length Sepal.Width Petal.Length Petal.Width
1 15.113.5 11.410.2
2 14.913.0 11.410.2
3 14.713.2 11.310.2
4 14.613.1 11.510.2
5 15.013.6 11.410.2
6 15.413.9 11.710.4
change only some
> iris[,1:4][iris[,1:4]<2] <- iris[,1:4][iris[,1:4]<2]+10
> head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 11.410.2 setosa
2 4.9 3.0 11.410.2 setosa
3 4.7 3.2 11.310.2 setosa
4 4.6 3.1 11.510.2 setosa
5 5.0 3.6 11.410.2 setosa
6 5.4 3.9 11.710.4 setosa
Cheers
Petr
> -Original Message-
> From: R-help On Behalf Of Luigi Marongiu
> Sent: Thursday, September 2, 2021 3:35 PM
> To: r-help
> Subject: [R] Loop over columns of dataframe and change values condtionally
>
> Hello,
> it is possible to select the columns of a dataframe in sequence with:
> ```
> for(i in 1:ncol(df)) {
> df[ , i]
> }
> # or
> for(i in 1:ncol(df)) {
> df[ i]
> }
> ```
> And change all values with, for instance:
> ```
> for(i in 1:ncol(df)) {
> df[ , i] <- df[ , i] + 10
> }
> ```
> Is it possible to apply a condition? What would be the syntax?
> For instance, to change all 0s in a column to NA would `df[i][df[i == 0] =
NA`
> be right?
> Thank you
>
>
> --
> Best regards,
> Luigi
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Loop over columns of dataframe and change values condtionally
Hello,
it is possible to select the columns of a dataframe in sequence with:
```
for(i in 1:ncol(df)) {
df[ , i]
}
# or
for(i in 1:ncol(df)) {
df[ i]
}
```
And change all values with, for instance:
```
for(i in 1:ncol(df)) {
df[ , i] <- df[ , i] + 10
}
```
Is it possible to apply a condition? What would be the syntax?
For instance, to change all 0s in a column to NA would `df[i][df[i ==
0] = NA` be right?
Thank you
--
Best regards,
Luigi
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
