Total TRUE and FALSE in Grouped Data

[jrmorse]

I am having trouble calculating the number of TRUE and FALSE values based off specific groups. I think this is pretty basic, but essentially I have data with many IDs and IDs that have a value of either TRUE or FALSE in a column titled one_positive (this was created with mutate() and any() to assign a TRUE value if just one of several tests was listed as positive).

Now, I am trying to calculate the total number of TRUE and FALSE one_positives per unique ID in a given a month.

My end goal is a dataframe that has three columns: Lab Month, # True, # False

chla_gono %>%
  mutate(positive = ifelse(labval %in% c("DETECTED", "POS", "POSITIVE", "REACTIVE", "REACTIVEMINIMAL", "REPEATEDLY REACTIVE", "RESULT:            NEISSERIA GONORRHOEAE"), "TRUE", "FALSE")) %>% 
  group_by(labdate,lab_month, iasid) %>% 
  mutate(one_positive= any(positive== "TRUE")) %>% 
  group_by(lab_month, iasid, one_positive) %>% 
  count(one_positive)

When doing this code, I get a column that lists the total number of tests that each unique ID has associated during a given time frame.

[woodward]

Is this what you want?

chla_gono %>%
  mutate(positive = ifelse(labval %in% c("DETECTED", "POS", "POSITIVE", "REACTIVE", "REACTIVEMINIMAL", "REPEATEDLY REACTIVE", "RESULT:            NEISSERIA GONORRHOEAE"), "TRUE", "FALSE")) %>% 
  group_by(lab_month) %>% 
  summarise(
    n_positive= sum(positive),
    n_negative= sum(!positive)
  )

[jrmorse]

@jrmorse

group_by(labdate,lab_month, iasid) %>% 
  mutate(one_positive= any(positive== "TRUE"))

No that doesn't give me what I'm looking for... I'm trying to count all the TRUE and FALSE values for each month by unique ID. But thanks for your response!

[woodward]

Then include the additional grouping variables in group_by(). But you said:

"My end goal is a dataframe that has three columns: Lab Month, # True, # False"