Data commit

Task/Merge-and-aggregate-datasets/R/merge-and-aggregate-datasets.r

@@ -0,0 +1,42 @@
+# load data from csv files
+# setwd("C:\Temp\csv\")
+# df_patient <- read.csv(file="patients.csv", header = TRUE, sep = ",")
+# df_visits <- read.csv(file="visits.csv", header = TRUE, sep = ",", dec = ".", colClasses=c("character","character","numeric"))
+
+# load data hard coded, create data frames
+df_patient <- read.table(text = "
+PATIENT_ID,LASTNAME
+1001,Hopper
+4004,Wirth
+3003,Kemeny
+2002,Gosling
+5005,Kurtz
+", header = TRUE, sep = ",") #  character fields so no need for extra parameters colClasses etc.
+
+df_visits <- read.table(text = "
+PATIENT_ID,VISIT_DATE,SCORE
+2002,2020-09-10,6.8
+1001,2020-09-17,5.5
+4004,2020-09-24,8.4
+2002,2020-10-08,
+1001,,6.6
+3003,2020-11-12,
+4004,2020-11-05,7.0
+1001,2020-11-19,5.3
+", header = TRUE, dec = ".", sep = ",", colClasses=c("character","character","numeric"))
+
+# aggregate visit date and scores
+df_agg <- data.frame(
+  cbind(
+    PATIENT_ID = names(tapply(df_visits$VISIT_DATE, list(df_visits$PATIENT_ID), max, na.rm=TRUE)),
+    last_visit = tapply(df_visits$VISIT_DATE, list(df_visits$PATIENT_ID), max, na.rm=TRUE),
+    score_sum = tapply(df_visits$SCORE, list(df_visits$PATIENT_ID), sum, na.rm=TRUE),
+    score_avg = tapply(df_visits$SCORE, list(df_visits$PATIENT_ID), mean, na.rm=TRUE)
+  )
+)
+
+# merge patients and aggregate dataset
+# all.x = all the non matching cases of df_patient are appended to the result as well (i.e. 'left join')
+df_result <- merge(df_patient, df_agg, by = 'PATIENT_ID', all.x = TRUE)
+
+print(df_result)