如何从第 4 列 grouped_by 第 1 列中的 id 的第 3 列中获取最大值（范围 1-2）？

Question

I want R to replace all the rows with the same chargepoint_skey and socketsinuse by just one row with that particular chargepoint_skey and socketsinuse. Ofcourse this needs to be done for all the individual chargepoint_skeys. So a kind of summarize. How can I get this done?

My code so far to get the dataframe (see image):

vraag_5 <- FACT_CHARGESSESION_JOINDIMLOCATION %>%
             select(ChargePoint_skey, Socket_ID) %>%
             group_by(ChargePoint_skey) %>%
             mutate(Socket_ID = str_replace_all(Socket_ID, "XXXXXX", "0")) %>%
             mutate(socketsinuse = max(Socket_ID))

Update after changing code:

dataframe3

Answer 1

Try changing your code to:

vraag_5 <- FACT_CHARGESSESION_JOINDIMLOCATION %>%
                mutate(Socket_ID = as.numeric(stringr::str_replace_all(Socket_ID,
                                   "XXXXXX", "0"))) %>%
                group_by(ChargePoint_skey) %>%
                summarise(socketsinuse = max(Socket_ID, na.rm = TRUE))