Cleaned the RPE data to remove nan and replace with median value.

data_preparation/replaceNanWithMedian.R

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+source("readData.R")
+
+library(tidyverse)
+
+
+# file to replace NA values with the median for thet column
+
+
+trainingData <- readRPEData()
+
+#duration
+trainingData$Duration[is.na(trainingData$Duration)] <- median(trainingData$Duration, na.rm=TRUE)
+
+
+#RPE
+trainingData$RPE[is.na(trainingData$RPE)] <- median(trainingData$RPE, na.rm=TRUE)
+
+# acute load
+trainingData$AcuteLoad[is.na(trainingData$AcuteLoad)] <- median(trainingData$AcuteLoad, na.rm=TRUE)
+
+# chronic load
+trainingData$ChronicLoad[is.na(trainingData$ChronicLoad)] <- median(trainingData$ChronicLoad, na.rm=TRUE)
+
+# ratio
+trainingData$AcuteChronicRatio[is.na(trainingData$AcuteChronicRatio)] <- median(trainingData$AcuteChronicRatio, na.rm=TRUE)
+
+# objective rating
+trainingData$ObjectiveRating[is.na(trainingData$ObjectiveRating)] <- median(trainingData$ObjectiveRating, na.rm=TRUE)
+
+
+# focus rating
+trainingData$FocusRating[is.na(trainingData$FocusRating)] <- median(trainingData$FocusRating, na.rm=TRUE)
+
+
+trainingData$RPE[is.na(trainingData$RPE)] <- median(trainingData$RPE, na.rm=TRUE)
+
+write.csv(as.data.frame(trainingData), "cleaned/time_series_rpw_naReplacedWithMedian.csv")
+
+
+head(as.data.frame(trainingData), 100)
+
+
+
+
+trainingData