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Created graph showing moving average vs daily load.

master
Jeffery Russell 5 years ago
parent
commit
bf9c85f0e4
2 changed files with 11 additions and 0 deletions
  1. +11
    -0
      data_preparation/createWorkSequenceData.R
  2. BIN
      findings/SlidingAverageDailyLoad.png

+ 11
- 0
data_preparation/createWorkSequenceData.R View File

@ -40,6 +40,8 @@ for(day in window:numDays)
slidingAverage <- c(slidingAverage, windowAverage) slidingAverage <- c(slidingAverage, windowAverage)
} }
plot(window:numDays, slidingAverage, main="Sliding Average") plot(window:numDays, slidingAverage, main="Sliding Average")
plot(density(slidingAverage), main="Sliding Average Density") plot(density(slidingAverage), main="Sliding Average Density")
plot(density(workLoad), main="Total Work Load Average") plot(density(workLoad), main="Total Work Load Average")
@ -47,4 +49,13 @@ plot(density(workLoad), main="Total Work Load Average")
dataTibble <- tibble(TimeSinceAugFirst = window:numDays, slidingWorkAverage = slidingAverage) dataTibble <- tibble(TimeSinceAugFirst = window:numDays, slidingWorkAverage = slidingAverage)
ggplot(data = dataTibble) +
theme(plot.title = element_text(hjust = 0.5)) +
ggtitle("Team's Total Daily Load Moving Average") +
geom_point(mapping = aes(x=TimeSinceAugFirst, y=slidingWorkAverage)) +
labs(x = "Days Since August Twenty First 2017", y = "Teams Total Daily Load")+
theme_bw()
write.csv(dataTibble, "cleaned/slidingWorkAverage.csv") write.csv(dataTibble, "cleaned/slidingWorkAverage.csv")

BIN
findings/SlidingAverageDailyLoad.png View File

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