r - Predominant calculation for Character fields -

i'm trying loop through column names type = character , return 1 data frame contains predominant values of each character column, grouped id field.

is there way replicate following code in kind of loop?:

      df_characters <- df_characters[,sapply(dfr,is.character)]  ##predominance column1##       predom <- select(df_characters, group_id, column_1)       predom <- group_by(predom,group_id, column_1)       predom <- summarise(predom,                              countpredom = n()                              )       predom <- arrange(predom,group_id, desc(countpredom) )       predom <- data.table(predom, key="group_id")       predominant_column_1 <- predom[,head(.sd,1),by=group_id]   ##predominant column_2##       predom <- select(df_characters, group_id, column_2)       predom <- group_by(predom,group_id, column_2)       predom <- summarise(predom,                              countpredom = n()                              )       predom <- arrange(predom,group_id, desc(countpredom) )       predom <- data.table(predom, key="group_id")       predominant_column_2 <- predom[,head(.sd,1),by=group_id]  ##merge final table##       merged <- merge(predominant_column_1 ,predominant_column_2 ,by="group_id") 

also clarify question added dummy table: df_character_table

result shoul result table

so group 1 petre predominant name in column 1 , car predominant mode of travel. column 1 , column 2 predominance should calculated respectively.

thank you

this not best solution works.

 ##########predominant calculations   #character fields   df_characters <- as.data.frame(dfr)   df_characters <- df_characters[,sapply(dfr,is.character)]    # field names without group id   characterstomerge <- c(names(df_characters))    #add groupby id character fields   character_field_list <- c("groupby_id", names(df_characters))   df_characters <- subset(dfr,select = character_field_list)    #column names loop through   df_fieldstomerge <- subset(dfr,select = characterstomerge)     # predominant table   fin_table <- df_characters %>% group_by(groupby_id) %>%                   tally(sort = true) #count observations    # loop , merge tables predominant table   for(i in names(df_fieldstomerge)){    temp_table <- df_characters %>% group_by_("groupby_id", ) %>%                       tally(sort = true)   temp_table  <- temp_table[,head(.sd,1),by=groupby_id] #remove ties   temp_table  <- subset(temp_table,select = c("groupby_id", i)) #remove counts    fin_table <- merge(fin_table, temp_table, by="groupby_id")   }