How to subset dataframe based on a "not equal to" criteria applied to a large number of columns?

Question

I'm new to R and currently trying to subset my data according to my predefined exclusion criteria for analysis. I'm presently trying to remove all cases that have dementia, as coded by the ICD-10. Problem is that there are multiple variables containing information on each individual's disease status (~70 variables), although as they are coded in the same way, the same condition can be applied to all of them.

Some simulated data:

#Create dataframe containing simulated data
df = data.frame(ID = c(1001, 1002, 1003, 1004, 1005,1006,1007,1008,1009,1010,1011),
                    disease_code_1 = c('I802','H356','G560','D235','B178','F011','F023','C761','H653','A049','J679'),
                    disease_code_2 = c('A071','NA','G20','NA','NA','A049','NA','NA','G300','G308','A045'),
                    disease_code_3 = c('H250','NA','NA','I802','NA','A481','NA','NA','NA','NA','D352'))

#data is structured as below:

     ID disease_code_1 disease_code_2 disease_code_3
1  1001           I802           A071           H250
2  1002           H356             NA             NA
3  1003           G560            G20             NA
4  1004           D235             NA           I802
5  1005           B178             NA             NA
6  1006           F011           A049           A481
7  1007           F023             NA             NA
8  1008           C761             NA             NA
9  1009           H653           G300             NA
10 1010           A049           G308             NA
11 1011           J679           A045           D352

Here, I'm trying to remove any case that has a 'dementia code' across any of the "disease_code" variables.

#Remove cases with dementia from dataframe (e.g. F023, G20)
Newdata_df <- subset(df, (2:4 != "F023"|"G20"|"F009"|"F002"|"F001"|"F000"|"F00"|    
                    "G309"| "G308"|"G301"|"G300"|"G30"| "F01"|"F018"|"F013"|
                    "F012"| "F011"| "F010"|"F01"))

The error that I recieve is:

Error in 2:4 != "F023" | "G20" : 
  operations are possible only for numeric, logical or complex types

Ideally, the subsetted dataframe would look like this:

     ID disease_code_1 disease_code_2 disease_code_3
1  1001           I802           A071           H250
2  1002           H356             NA             NA
4  1004           D235             NA           I802
5  1005           B178             NA             NA
8  1008           C761             NA             NA
11 1011           J679           A045           D352

I know that there is an error in my code although I'm not sure how exactly to fix it. I've tried a few other ways (using dplyr) although haven't had any luck so far.

Any help is greatly appreciated!

Answer 1

We can create a vector with the codes to be removed and use rowSums to remove, i.e.

codes_to_remove <- c("F023", "G20", "F009", "F002", "F001", "F000", "F00", "G309", "G308",
                "G301", "G300", "G30", "F01", "F018", "F013", "F012", "F011", "F010", "F01")

df[rowSums(sapply(df[-1], `%in%`, codes_to_remove)) == 0,]

which gives,

     ID disease_code_1 disease_code_2 disease_code_3
1  1001           I802           A071           H250
2  1002           H356             NA             NA
4  1004           D235             NA           I802
5  1005           B178             NA             NA
8  1008           C761             NA             NA
11 1011           J679           A045           D352

Answer 2

One dplyr possibility could be:

df %>%
 filter_at(vars(2:4), all_vars(! . %in% c("F023","G20","F009","F002","F001","F000","F00",    
            "G309", "G308","G301","G300","G30", "F01","F018","F013",
            "F012", "F011", "F010","F01")))

    ID disease_code_1 disease_code_2 disease_code_3
1 1001           I802           A071           H250
2 1002           H356             NA             NA
3 1004           D235             NA           I802
4 1005           B178             NA             NA
5 1008           C761             NA             NA
6 1011           J679           A045           D352

In this case, it checks whether any of the columns 2:4 contains any of the given codes.

Or:

df %>%
 filter_at(vars(contains("disease_code")), all_vars(! . %in% c("F023","G20","F009","F002","F001","F000","F00",    
            "G309", "G308","G301","G300","G30", "F01","F018","F013",
            "F012", "F011", "F010","F01")))

In this case, it checks whether any of the columns with names disease_code contains any of the given codes.