Assuming I have a data frame like
term cnt
apple 10
apples 5
a apple on 3
blue pears 3
pears 1
How could I filter all partial found strings within this column, e.g. getting as a result
term cnt
apple 10
pears 1
without indicating to which terms I want to filter (apple|pears), but through a self-referencing manner (i.e. it does check each term against the whole column and removes terms that are a partial match). The number of tokens is not limited, nor the consistency of strings (i.e. "mapples" would get matched by "apple"). This would result in an inverted generalized dplyr-based version of
d[grep("^apple$|^pears$", d$term), ]
Additionally, it would be interesting use this departialisation to get a cumulated sum, e.g.
term cnt
apple 18
pears 4
I couldn't get it to work with contains() or grep().
Thanks
Hopefully the complete answer. Not very idiomatic (as Pythonista's call) but someone can suggest improvement to this:
> ssss <- data.frame(c('apple','red apple','apples','pears','blue pears'),c(15,3,10,4,3))
>
> names(ssss) <- c('Fruit','Count')
>
> ssss
Fruit Count
1 apple 15
2 red apple 3
3 apples 10
4 pears 4
5 blue pears 3
>
> root_list <- as.vector(ssss$Fruit[unlist(lapply(ssss$Fruit,function(x){length(grep(x,ssss$Fruit))>1}))])
>
>
> ssss %>% filter(ssss$Fruit %in% root_list)
Fruit Count
1 apple 15
2 pears 4
>
> data <- data.frame(lapply(root_list, function(x){y <- stringr::str_extract(ssss$Fruit,x); ifelse(is.na(y),'',y)}))
>
> cols <- colnames(data)
>
> #data$x <- do.call(paste0, c(data[cols]))
> #for (co in cols) data[co] <- NULL
>
> ssss$Fruit <- do.call(paste0, c(data[cols]))
>
> ssss %>% group_by(Fruit) %>% summarise(val = sum(Count))
# A tibble: 2 x 2
Fruit val
<chr> <dbl>
1 apple 28
2 pears 7
>