datafest competition 2019
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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$Duration, na.rm=TRUE)
print(trainingData$Duration)
#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)
# session load
trainingData$SessionLoad[is.na(trainingData$SessionLoad)] <- median(trainingData$SessionLoad, na.rm=TRUE)
# daily load
trainingData$DailyLoad[is.na(trainingData$DailyLoad)] <- median(trainingData$DailyLoad, na.rm=TRUE)
trainingData$RPE[is.na(trainingData$RPE)] <- median(trainingData$RPE, na.rm=TRUE)
write.csv(as.data.frame(trainingData), "cleaned/time_series_rpe_NA_ReplacedWithMedian.csv")
head(as.data.frame(trainingData), 100)
trainingData