"If else" changing categorical data to "1", not modifying all data

[lytheros]

Hi everyone, I'm really new to R so I apologize if the answer to this is obvious.
I was trying to change instances of "NA" from the "Country" column of my data to the country that matches the city that the data is located in. It seemed to work, however, it changed all other data under "Country" to "1", and doesn't seem to have replaced the other "NA" when I tried to do the same for other missing country data that had a value for "City". Here's the code I used:

Apartify_GroupA_new <- Apartify_GroupA_new %>% 
  mutate(Country = ifelse(is.na(Country) & Apartify_GroupA_new$City == "Beijing", 
                                      "China",
       Country))
diagnose(Apartify_GroupA_new)

Here is a screenshot of what happened to my data:

Here is another example where the "if else" function seems to have partially worked:

Apartify_GroupA_new <- Apartify_GroupA_new %>% 
  mutate(Bedrooms = ifelse(is.na(Bedrooms) & Apartify_GroupA_new$Beds == "1", 
                                      "1",
       Bedrooms),
       ifelse(is.na(Bedrooms) & Apartify_GroupA_new$Beds == "2",
              "2",
              Bedrooms),
       ifelse(is.na(Bedrooms) & Apartify_GroupA_new$Beds == "4",
              "4",
              Bedrooms))
diagnose(Apartify_GroupA_new)

I really appreciate any help!

[gtmbini]

This might work for you , just change Country as as.character(Country).

Apartify_GroupA_new <- Apartify_GroupA_new %>%
mutate(Country = ifelse(is.na(Country) & Apartify_GroupA_new$City == "Beijing",
"China",
as.character( Country)))

[nirgrahamuk]

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…