Created
August 9, 2017 12:33
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Filter lab tests for tests that occured for at least K users distinctly, and then filter by the most frequent (non distinct) labs. R
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#LABS | |
#get most frequent lab tests, for distinct patients. | |
#Filter for distinct by user: | |
# data.labs = as.data.frame(data.labs) | |
# data.labs.userDistinct = subset(as.data.table(data.labs),select=c("guid_tz","kod_bdika")) #ORIG | |
# data.labs.userDistinct= unique(data.labs.userDistinct) #ORIG | |
data.labs.userDistinct= unique(data.labs,by="guid_tz") #changed | |
#Filter all Labs data! | |
"Lab tests that occured for at least K unique users:" | |
commonlabNames = sort(table(data.labs.userDistinct$kod_bdika)[table(data.labs.userDistinct$kod_bdika)>25],decreasing=T) # Keeps supermajority of labs | |
data.labs = data.labs[data.labs$kod_bdika %in% commonlabNames, ] # Get data of labs with only the labtests which occured at least K times for unique patients | |
## | |
# Labs which appear at least K times: | |
# sort(table(data.labs$kod_bdika)[table(data.labs$kod_bdika)>250],decreasing=T) ## 336 (note that we're not normalizing by occurences per test vs per user) | |
# FreqlabNames = sort(table(data.labs$kod_bdika)[table(data.labs$kod_bdika)>350],decreasing=T) | |
FreqlabNames = names(sort(table(data.labs.userDistinct$kod_bdika),decreasing=T)[1:250]) #most frequent tests. note long tail | |
data.labs.freq = data.labs[data.labs$kod_bdika %in% FreqlabNames, ] # Get data of labs with only the most frequent labtests |
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