一些 Na 值而不是全部

Question

Assume that you have a dataset like starwars. Also assume that you have 2 columns one numeric with 20 NA values and the other with species (human,Droid,machine,etc).

How to convert using pipes , only the na values that belong to category humans to the mean of the heights?

If we convert it to the total it will be wrong as machines may be a lit smaller or higher and as a result we will have some strange values as for the height of the humans.

Ps I know how to do it using replace or ifelse, but how to add the categorization

Answer 1

In the starwars scenario, you can do the following

library(dplyr)

starwars %>% 
  group_by(species) %>% 
  mutate(height = if_else(species == "Human" & is.na(height), mean(height, na.rm = TRUE), as.double(height))) %>% 
  ungroup()

As you can see from here, height is filled with the average only with Human as species

library(dplyr)

starwars %>% 
  group_by(species) %>% 
  mutate(newheight = if_else(species == "Human" & is.na(height), mean(height, na.rm = TRUE), as.double(height))) %>% 
  ungroup() %>% 
  select(species, height, newheight) %>% 
  filter(is.na(height))

#> # A tibble: 6 x 3
#>   species height newheight
#>   <chr>    <int>     <dbl>
#> 1 Human       NA      177.
#> 2 Human       NA      177.
#> 3 Human       NA      177.
#> 4 Human       NA      177.
#> 5 Droid       NA       NA 
#> 6 NA          NA       NA 

In this specific example, you need to transform height into a double because it's an integer , and, since if_else is type-consistent and from the mean you receive a double , you need to transform height accordingly.

Answer 2

If I understand you correctly, you just want to replace NAs by group means?

This should do:

data(starwars)

head(starwars)

#This shows one missing value (NAs) for "Droid"
starwars %>%
  group_by(species) %>%
  summarize(M = mean(height, na.rm=T),
            NAs = sum(is.na(height)))

#Replace NAs by group-wise means
starwars <- starwars %>%
  group_by(species) %>%
  mutate(height = if_else(is.na(height), mean(height, na.rm=T), as.double(height) )) %>%
  ungroup()

#Now no missing value any more and means (M) remains the same
starwars %>%
  group_by(species) %>%
  summarize(M = mean(height, na.rm=T),
            NAs = sum(is.na(height)))

Answer 3

I would use case_when and replace_na , which was designed for these NA-replacing operations.

output<-starwars %>% 
    mutate(height = case_when(species=='Human' ~ replace_na(height, mean(height, na.rm=TRUE))))

If we are interested in Humans only, we do not need to group_by . If we want this transformation for every group, we could use

output<-starwars %>% 
        group_by(species) %>%
        mutate(height = replace_na(height, mean(height, na.rm=TRUE)))

We can also use the zoo package with na.aggregate :

library(zoo)

output<-starwars %>% 
    mutate(height = case_when(species=='Human' ~ na.aggregate(height, na.rm=TRUE)))