Mutate - NA Handling

Question

I've used the arrange and mutate combination to do additions based on groupings. For example, I've used the following:

master_df <-group_by(master_df,asof_dt)
mutate(master_df,tot_flag=ls_flag)

This groups my data frame master_df by asof_dt, and then creates tot_flag and adds ls_flag by date.

However, my ls_flag column contains NA's.

I would like to do the following: 1) find out how to add the ls_flag, ignoring any NA's 2) find out how to add the total number of NA's per day.

Here is the full example:

asof_dt<-c("2014-10-01","2014-10-01","2014-10-01","2014-10-02","2014-10-02","2014-10-02")
ls_flag<-c(1,1,NA,NA,1,1)
master_df<-data.frame(asof_dt,ls_flag)
master_df <-group_by(master_df,asof_dt)
mutate(master_df,tot_flag=sum(ls_flag))

Thank you very much!

Answer 1

Is this your desired result? You can use the na.rm = TRUE option in sum():

master_df %>%
  group_by(asof_dt) %>%
  mutate(tot_flag = sum(ls_flag, na.rm = TRUE),
         tot_NA = sum(is.na(ls_flag)))

#Source: local data frame [6 x 4]
#Groups: asof_dt
#
#     asof_dt ls_flag tot_flag tot_NA
#1 2014-10-01       1        2      1
#2 2014-10-01       1        2      1
#3 2014-10-01      NA        2      1
#4 2014-10-02      NA        2      1
#5 2014-10-02       1        2      1
#6 2014-10-02       1        2      1

Or perhaps you just want a "summary" (using summarise):

master_df %>%
  group_by(asof_dt) %>%
  summarise(tot_flag = sum(ls_flag, na.rm = TRUE),
            tot_NA = sum(is.na(ls_flag)))
#Source: local data frame [2 x 3]
#
#     asof_dt tot_flag tot_NA
#1 2014-10-01        2      1
#2 2014-10-02        2      1