After merging a dataframe with another im left with random NA\'s for the occasional row. I\'d like to set these NA\'s to 0 so I can perform calculations with them.
A solution using mutate_all from dplyr in case you want to add that to your dplyr pipeline:
library(dplyr)
df %>%
mutate_all(funs(ifelse(is.na(.), 0, .)))
Result:
A B C
1 1 1 2
2 2 2 5
3 3 1 2
4 0 2 0
5 1 1 0
6 2 2 0
7 3 1 3
8 0 2 0
9 1 1 3
10 2 2 3
11 3 1 0
12 0 2 3
13 1 1 4
14 2 2 4
15 3 1 0
16 0 2 0
17 1 1 1
18 2 2 0
19 3 1 2
20 0 2 0
If in any case you only want to replace the NA's in numeric columns, which I assume it might be the case in modeling, you can use mutate_if:
library(dplyr)
df %>%
mutate_if(is.numeric, funs(ifelse(is.na(.), 0, .)))
or in base R:
replace(is.na(df), 0)
Result:
A B C
1 1 0 2
2 2 NA 5
3 3 0 2
4 0 NA 0
5 1 0 0
6 2 NA 0
7 3 0 3
8 0 NA 0
9 1 0 3
10 2 NA 3
11 3 0 0
12 0 NA 3
13 1 0 4
14 2 NA 4
15 3 0 0
16 0 NA 0
17 1 0 1
18 2 NA 0
19 3 0 2
20 0 NA 0
Data:
set.seed(123)
df <- data.frame(A=rep(c(0:3, NA), 5), B=rep(c("0", "NA"), 10), C=c(sample(c(0:5, NA), 20, replace = TRUE)))