Multiple decisions in R

Hello Community,

my question regards making multiple decisions like & and |. I imported a rather big dataset from an excel sheet (9211 obs., 482 variables). Now, I only want to keep the rows, which have an "1" in one of the first columns (this indicates an Error in the Data and I want to know, how many there are).

What I did was, in short, something like

     Data <- read.csv2("Data.csv", header =FALSE)
     Data_fail <- subset(Data, (V3 == 1 | V4 == 1 | V5 == 1 | V6 == 1 | V7 == 1), select=c(V1:V60))

In my actual code I'm not only considering V3 to V7 but V3 to V60, repeating the |-decision until V60, which is a lot to write. Is there any way to make it easier? Like (V3|:V60) == 1, or V3 == 1 | V4 == 1 | ... | V60 == 1?


f <- function(x){x==1.6} 
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Hello nirgrahamuk,

thank you for your answer. I'm very new to rStudio, so I don't know if I implemented your solution in the right way.

I compiled the code you suggested and set

Data_fail <- f(Data)

But this returns a very large Matrix with the only entries being "NA" or "FALSE". But what I need is the same output I got with my longer solution.

In my example replace iris with Data
Replace Petal.Length with V3 etc.

Thanks, I tried it in the way:

f <- function(x)(x==1)
Data_fail <- filter(rowwise(Data), any(f(V3), f(V4)))

This seems to work, but I still have to type every "f(V...)" for all columns from V3 to V60. What I`m looking for would be something like


But this doesn't seem to work with this solution.


f <- function(x){x==.8} 
set.seed(42) # for reproducible random ness in example data
example_df <-,1),nrow = 10,ncol=10))

empty_choose_names <- filter(example_df,FALSE) %>% select(V3:V7)
(to_do <- names(empty_choose_names))

(list_of_fs <- map_chr(to_do,
    )) %>% paste0(collapse = ","))

str_to_exec <- paste0("filter(rowwise(example_df),any(",list_of_fs,"))")

(myresult <- eval(str2lang(str_to_exec)))
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