In dplyr I can replace NA with 0 using the following code. The issue is this inserts a list into my data frame which screws up further analysis down the line. I don't even understand lists or atomic vectors or any of that at this point. I just want to pick certain columns, and replace all occurrences of NA with zero. And maintain the columns integer status.
library(dplyr)
df <- tibble(x = c(1, 2, NA), y = c("a", NA, "b"), z = list(1:5, NULL, 10:20))
df
df %>% replace_na(list(x = 0, y = "unknown"))
That works but transforms the column into a list. How do I do it without transforming the column into a list?
And here's how to do it in base R. But not sure how to work this into a mutate statement:
df$x[is.na(df$x)] <- 0
To replace all NAs in a dataframe use
df %>% replace(is.na(.), 0)