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77 lines
1.4 KiB
77 lines
1.4 KiB
# Look at data
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library(tidyverse)
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gpsData <- read.csv("data/gps.csv")
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gpsDataTibble <- as_tibble(gpsData)
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workingTibble <- head(gpsDataTibble, 100000)
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playerIds <-unique(workingTibble$PlayerID)
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gameIds <- unique(workingTibble$GameID)
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playerIDMetrics <- c()
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gameIDMetrics <- c()
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averageSpeed <- c()
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accelDistance <- c()
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for(playerID in playerIds)
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{
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for(gameID in gameIds)
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{
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cat(playerID, gameID , '\n', sep=" ")
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speedTibble <- subset(workingTibble, GameID == gameID & PlayerID == playerID)
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# crunch average speed
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averageSpeed <- c(averageSpeed, mean(speedTibble$Speed))
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# average for accel value
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accelDistance <- c(accelDistance, mean(sqrt(speedTibble$AccelX^2 + speedTibble$AccelY^2 + speedTibble$AccelZ^ 2)))
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#xAccel <- c(xAccel, mean(speedTibble$AccelX))
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#yAccel <- c(yAccel, mean(speedTibble$AccelY))
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#zAccel <- c(zAccel, mean(speedTibble$AccelZ))
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# game and player id to vector
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playerIDMetrics <- c(playerIDMetrics, playerID)
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gameIDMetrics <- c(gameIDMetrics, gameID)
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}
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}
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plot(accelDistance, averageSpeed)
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rpeData <- read.csv("./data/rpe.csv")
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rpeDataTibble <- as_tibble(rpeData)
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gameData <- read.csv("./data/game.csv")
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gameDataTibble <- as_tibble(gameData)
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wellnessData <- read.csv("./data/wellness.csv")
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wellnessDataTibble <- as_tibble(wellnessData)
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head(gpsData)
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