how to I replace numeric values with a string in an R dataframe?
$begingroup$
I want to replace all numeric values in a column in my data frame with a string value. The following doesn't seem to work.
df <- within(df, myCol[is.numeric(myCol)] <- 'NOTMISSING')
Even though the df has some values as NA and others as numbers, all values are being replaced with NOTMISSING.
Also tried
df <- within(df, myCol[is_numeric(myCol)] <- 'NOTMISSING')
Any pointers highly appreciated.
r dataframe
asked Sep 19 '18 at 16:31
ramsrams
1011
$endgroup$
bumped to the homepage by Community♦ 1 hour ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I want to replace all numeric values in a column in my data frame with a string value. The following doesn't seem to work.
df <- within(df, myCol[is.numeric(myCol)] <- 'NOTMISSING')
Even though the df has some values as NA and others as numbers, all values are being replaced with NOTMISSING.
Also tried
df <- within(df, myCol[is_numeric(myCol)] <- 'NOTMISSING')
Any pointers highly appreciated.
r dataframe
asked Sep 19 '18 at 16:31
ramsrams
1011
$endgroup$
bumped to the homepage by Community♦ 1 hour ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
1
$begingroup$
Do you have a dummy dataframe that you can provide?
$endgroup$
– n1k31t4
Sep 19 '18 at 19:40
$begingroup$
df[is.numeric(df)]="string".
$endgroup$
– user2974951
Sep 20 '18 at 6:31
add a comment |
$begingroup$
I want to replace all numeric values in a column in my data frame with a string value. The following doesn't seem to work.
df <- within(df, myCol[is.numeric(myCol)] <- 'NOTMISSING')
Even though the df has some values as NA and others as numbers, all values are being replaced with NOTMISSING.
Also tried
df <- within(df, myCol[is_numeric(myCol)] <- 'NOTMISSING')
Any pointers highly appreciated.
r dataframe
asked Sep 19 '18 at 16:31
ramsrams
1011
$endgroup$
I want to replace all numeric values in a column in my data frame with a string value. The following doesn't seem to work.
df <- within(df, myCol[is.numeric(myCol)] <- 'NOTMISSING')
Even though the df has some values as NA and others as numbers, all values are being replaced with NOTMISSING.
Also tried
df <- within(df, myCol[is_numeric(myCol)] <- 'NOTMISSING')
Any pointers highly appreciated.
r dataframe
r dataframe
asked Sep 19 '18 at 16:31
ramsrams
1011
asked Sep 19 '18 at 16:31
ramsrams
1011
asked Sep 19 '18 at 16:31
ramsrams
1011
asked Sep 19 '18 at 16:31
ramsrams
1011
asked Sep 19 '18 at 16:31
ramsrams
1011
1011
bumped to the homepage by Community♦ 1 hour ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 1 hour ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
1
$begingroup$
Do you have a dummy dataframe that you can provide?
$endgroup$
– n1k31t4
Sep 19 '18 at 19:40
$begingroup$
df[is.numeric(df)]="string".
$endgroup$
– user2974951
Sep 20 '18 at 6:31
add a comment |
1
$begingroup$
Do you have a dummy dataframe that you can provide?
$endgroup$
– n1k31t4
Sep 19 '18 at 19:40
$begingroup$
df[is.numeric(df)]="string".
$endgroup$
– user2974951
Sep 20 '18 at 6:31
1
1
$begingroup$
Do you have a dummy dataframe that you can provide?
$endgroup$
– n1k31t4
Sep 19 '18 at 19:40
$begingroup$
Do you have a dummy dataframe that you can provide?
$endgroup$
– n1k31t4
Sep 19 '18 at 19:40
$begingroup$
df[is.numeric(df)]="string".$endgroup$
– user2974951
Sep 20 '18 at 6:31
$begingroup$
df[is.numeric(df)]="string".$endgroup$
– user2974951
Sep 20 '18 at 6:31
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
From the documentation of is.numeric:
The default method for is.numeric returns TRUE if its argument is of mode "numeric" (type > "double" or type "integer") and not a factor, and FALSE otherwise.
So for a vector, is.numeric returns a single TRUE, it doesn't test each element as you might expect.
is.numeric(c(5, 4, 3))
[1] TRUE
is.numeric(c(5, 4, NA))
[1] TRUE
That's why either all or none of the values are changed to NOTMISSING.
@eg-r's fix is correct. Here's a tidyverse way to accomplish the same.
> df<-tibble(myCol=c(5, 4, NA))
> df
# A tibble: 3 x 1
myCol
<dbl>
1 5
2 4
3 NA
> df %>% mutate(myCol = ifelse(is.na(myCol), myCol, "NOTMISSING"))
# A tibble: 3 x 1
myCol
<chr>
1 NOTMISSING
2 NOTMISSING
3 <NA>
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
$endgroup$
add a comment |
$begingroup$
NAs can be numeric (especially if the other values in that column are all numeric). Try this :
df$myCol = ifelse(is.numeric(df$myCol) & !is.na(df$myCol), "NOTMISSING", df$myCol)
Or if all you want to do is turn all values in that column that are not NA as that string, you can change your original code to :
df <- within(df, myCol[!is.na(myCol)] <- 'NOTMISSING')
answered Sep 22 '18 at 0:40
eg-reg-r
16614
$endgroup$
add a comment |
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2 Answers
2
active
oldest
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2 Answers
2
active
oldest
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$begingroup$
From the documentation of is.numeric:
The default method for is.numeric returns TRUE if its argument is of mode "numeric" (type > "double" or type "integer") and not a factor, and FALSE otherwise.
So for a vector, is.numeric returns a single TRUE, it doesn't test each element as you might expect.
is.numeric(c(5, 4, 3))
[1] TRUE
is.numeric(c(5, 4, NA))
[1] TRUE
That's why either all or none of the values are changed to NOTMISSING.
@eg-r's fix is correct. Here's a tidyverse way to accomplish the same.
> df<-tibble(myCol=c(5, 4, NA))
> df
# A tibble: 3 x 1
myCol
<dbl>
1 5
2 4
3 NA
> df %>% mutate(myCol = ifelse(is.na(myCol), myCol, "NOTMISSING"))
# A tibble: 3 x 1
myCol
<chr>
1 NOTMISSING
2 NOTMISSING
3 <NA>
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
$endgroup$
add a comment |
$begingroup$
From the documentation of is.numeric:
The default method for is.numeric returns TRUE if its argument is of mode "numeric" (type > "double" or type "integer") and not a factor, and FALSE otherwise.
So for a vector, is.numeric returns a single TRUE, it doesn't test each element as you might expect.
is.numeric(c(5, 4, 3))
[1] TRUE
is.numeric(c(5, 4, NA))
[1] TRUE
That's why either all or none of the values are changed to NOTMISSING.
@eg-r's fix is correct. Here's a tidyverse way to accomplish the same.
> df<-tibble(myCol=c(5, 4, NA))
> df
# A tibble: 3 x 1
myCol
<dbl>
1 5
2 4
3 NA
> df %>% mutate(myCol = ifelse(is.na(myCol), myCol, "NOTMISSING"))
# A tibble: 3 x 1
myCol
<chr>
1 NOTMISSING
2 NOTMISSING
3 <NA>
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
$endgroup$
add a comment |
$begingroup$
From the documentation of is.numeric:
The default method for is.numeric returns TRUE if its argument is of mode "numeric" (type > "double" or type "integer") and not a factor, and FALSE otherwise.
So for a vector, is.numeric returns a single TRUE, it doesn't test each element as you might expect.
is.numeric(c(5, 4, 3))
[1] TRUE
is.numeric(c(5, 4, NA))
[1] TRUE
That's why either all or none of the values are changed to NOTMISSING.
@eg-r's fix is correct. Here's a tidyverse way to accomplish the same.
> df<-tibble(myCol=c(5, 4, NA))
> df
# A tibble: 3 x 1
myCol
<dbl>
1 5
2 4
3 NA
> df %>% mutate(myCol = ifelse(is.na(myCol), myCol, "NOTMISSING"))
# A tibble: 3 x 1
myCol
<chr>
1 NOTMISSING
2 NOTMISSING
3 <NA>
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
$endgroup$
From the documentation of is.numeric:
The default method for is.numeric returns TRUE if its argument is of mode "numeric" (type > "double" or type "integer") and not a factor, and FALSE otherwise.
So for a vector, is.numeric returns a single TRUE, it doesn't test each element as you might expect.
is.numeric(c(5, 4, 3))
[1] TRUE
is.numeric(c(5, 4, NA))
[1] TRUE
That's why either all or none of the values are changed to NOTMISSING.
@eg-r's fix is correct. Here's a tidyverse way to accomplish the same.
> df<-tibble(myCol=c(5, 4, NA))
> df
# A tibble: 3 x 1
myCol
<dbl>
1 5
2 4
3 NA
> df %>% mutate(myCol = ifelse(is.na(myCol), myCol, "NOTMISSING"))
# A tibble: 3 x 1
myCol
<chr>
1 NOTMISSING
2 NOTMISSING
3 <NA>
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
answered Nov 23 '18 at 17:18
John RauserJohn Rauser
1014
1014
add a comment |
add a comment |
$begingroup$
NAs can be numeric (especially if the other values in that column are all numeric). Try this :
df$myCol = ifelse(is.numeric(df$myCol) & !is.na(df$myCol), "NOTMISSING", df$myCol)
Or if all you want to do is turn all values in that column that are not NA as that string, you can change your original code to :
df <- within(df, myCol[!is.na(myCol)] <- 'NOTMISSING')
answered Sep 22 '18 at 0:40
eg-reg-r
16614
$endgroup$
add a comment |
$begingroup$
NAs can be numeric (especially if the other values in that column are all numeric). Try this :
df$myCol = ifelse(is.numeric(df$myCol) & !is.na(df$myCol), "NOTMISSING", df$myCol)
Or if all you want to do is turn all values in that column that are not NA as that string, you can change your original code to :
df <- within(df, myCol[!is.na(myCol)] <- 'NOTMISSING')
answered Sep 22 '18 at 0:40
eg-reg-r
16614
$endgroup$
add a comment |
$begingroup$
NAs can be numeric (especially if the other values in that column are all numeric). Try this :
df$myCol = ifelse(is.numeric(df$myCol) & !is.na(df$myCol), "NOTMISSING", df$myCol)
Or if all you want to do is turn all values in that column that are not NA as that string, you can change your original code to :
df <- within(df, myCol[!is.na(myCol)] <- 'NOTMISSING')
answered Sep 22 '18 at 0:40
eg-reg-r
16614
$endgroup$
NAs can be numeric (especially if the other values in that column are all numeric). Try this :
df$myCol = ifelse(is.numeric(df$myCol) & !is.na(df$myCol), "NOTMISSING", df$myCol)
Or if all you want to do is turn all values in that column that are not NA as that string, you can change your original code to :
df <- within(df, myCol[!is.na(myCol)] <- 'NOTMISSING')
answered Sep 22 '18 at 0:40
eg-reg-r
16614
answered Sep 22 '18 at 0:40
eg-reg-r
16614
answered Sep 22 '18 at 0:40
eg-reg-r
16614
answered Sep 22 '18 at 0:40
eg-reg-r
16614
16614
add a comment |
add a comment |
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1
$begingroup$
Do you have a dummy dataframe that you can provide?
$endgroup$
– n1k31t4
Sep 19 '18 at 19:40
$begingroup$
df[is.numeric(df)]="string".$endgroup$
– user2974951
Sep 20 '18 at 6:31