Checking conditions and adding items to a data frame

I'm trying to develop a function which will allow me to input n开发者_如何学Pythonew elements to a data frame and then check if they contain certain words.

df <- data.frame(keyword=c("He drives a Honda", "He goes to Ohio State"), 
        car=c(1,0), school=c(0,1))
df

               keyword car school
     He drives a Honda   1      0
 He goes to Ohio State   0      1

In this data frame, car and school are binary values which contain 1 if a word from the car/school vector is part of the keyword. If a word isn't present in the keyword, then 0 is assigned.

car <- c("Honda", "Chevy", "Toyota", "Ford")
school <- c("Michigan", "Ohio State", "Missouri")

I want to use a function to input new keywords into the data frame, while iterating over the keywords for specific values from the car and school vectors.

main <- function(keyword){
    n = strsplit(as.character(keyword), " ")[[1]]
    for( i in keyword ){
       if( any(n==car) ){
          df$car <- c(1)
       }
       if( any(n==school )){
          df$school <- c(1)
    }
}

}

This function isn't complete and it produces the following error. Because the car and school vectors are of length 3, it seems to be producing an error.

> main("He likes Ford and goes to Ohio State")            
Warning message:
In n == school :
  longer object length is not a multiple of shorter object length

I'm also not sure how to add the 0/1 values to the df. For the "He likes Ford and goes to Ohio State" keyword, I should have 1 in both the car and school columns.

                              keyword       car          school
                    He drives a Honda        1             0
                He goes to Ohio State        0             1
He likes Honda and goes to Ohio State        1             1

Please help. It seems like the ifelse() function would be really useful for this task, but I haven't been able to properly implement it.

I think the easiest way is to use a compound regular expression:

library(stringr)

car <- c("Honda", "Chevy", "Toyota", "Ford")
school <- c("Michigan", "Ohio State", "Missouri")

car_match <- str_c(car, collapse = "|")
school_match <- str_c(school, collapse = "|")


df <- data.frame(keyword=c("He drives a Honda", 
  "He goes to Ohio State", 
  "He likes Ford and goes to Ohio State"))

main <- function(df) {
  df$car <- str_detect(df$keyword, car_match)
  df$school <- str_detect(df$keyword, school_match)
  df
}
main(df)

Few minor problems, but easily fixed with a couple of %in%. Also you need a special logical expression to account for 'Ohio State' which was tripping up strsplit because of the space.

df <- data.frame(keyword=c("He drives a Honda", 
  "He goes to Ohio State", 
  "He likes Ford and goes to Ohio State"),
  car=0, school=0)

main <- function(df) {
  car <- c("Honda", "Chevy", "Toyota", "Ford")
  school <- c("Michigan", "Missouri")
  for (i in 1:nrow(df)) {
    Words = strsplit(as.character(df[i, 'keyword']), " ")[[1]]
    if(any(Words %in% car)) df[i, 'car'] <- 1
    if(any(Words == 'Ohio')) {
      if(Words[which(Words == 'Ohio') + 1] == 'State') df[i, 'school'] <- 1
    }   
    if(any(Words %in% school)) df[i, 'school'] <- 1 
  }
  return(df)
}

main(df)

                               keyword car school
1                    He drives a Honda   1      0
2                He goes to Ohio State   0      1
3 He likes Ford and goes to Ohio State   1      1

Here's a version that I believe will work without having to specify every two-word search term by hand, as in the case of "Ohio State" in wkmor1's solution. The trick is to use grep instead:

main <- function(str,df){
    carSearch <- unlist(lapply(car,grep,x=str,fixed=TRUE))
    schoolSearch <- unlist(lapply(school,grep,x=str,fixed=TRUE))
    t1 <- length(carSearch) != 0
    t2 <- length(schoolSearch) != 0
    if (t1 | t2){
        newRow <- data.frame(keyword=str,car=ifelse(t1,1,0),
                              school=ifelse(t2,1,0))
        df <- rbind(df,newRow)
        return(df)
    }
}