子集在一列中具有相同值的所有行，按另一列分组，其中第三列的至少一行包含 R 中的特定字母

Question

I am gathering data from a database, where I have two different ID identifiers (ID1, Nr). I want to collect all the rows, that have duplicated ID1, grouped by "Nr", WHERE at least one record in Names has a letter "a".

df <- data_frame(ID1 = c('100', '100', '100', '100', '100', '100', '100', '100', '100'),
                 Nr = c('1', '1', '1', '2', '2', '2', '2', '3', '4'),
                 Names = c('aaa bb', 'aa bbb', 'ccc', 'ccc', 'ccc', 'ddd', 'ccc', 'ccc', 'add'))

So, the desired output would be:

output <- data_frame(ID1= c('100', '100', '100', '100'),
                     Nr = c('1', '1', '1', '4'),
                     Names = c('aaa bb', 'aa bbb', 'ccc', 'add'))

Thank you in advance!

Answer 1

You can group_by Nr column and use grepl :

library(dplyr)
df %>% group_by(Nr) %>% filter(any(grepl('a', Names)))

#  ID1   Nr    Names 
# <chr> <chr> <chr> 
#1 100   1     aaa bb
#2 100   1     aa bbb
#3 100   1     ccc   
#4 100   4     add   

The same logic can be implemented in base R

subset(df, ave(grepl('a', Names), Nr, FUN = any))

as well as data.table :

library(data.table)
setDT(df)[, .SD[any(grepl('a', Names))], Nr]

In the orignal dataset if you have more ID 's you might want to include it in group_by as well.