datafest competition 2019
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# Look at data
library(tidyverse)
library(DBI)
library(RSQLite)
gpsData <- read.csv("data/gps.csv")
gpsDataTibble <- as_tibble(gpsData)
#workingTibble <- head(gpsDataTibble, 500000)
workingTibble <- gpsDataTibble
playerIds <-unique(workingTibble$PlayerID)
cat("Number of Players: ", length(playerIds), sep="")
gameIds <- unique(workingTibble$GameID)
cat("Number of Games: ", length(gameIds), sep="")
playerIDMetrics <- c()
gameIDMetrics <- c()
averageSpeed <- c()
accelDistance <- c()
for(playerID in playerIds)
{
for(gameID in gameIds)
{
cat(playerID, gameID , '\n', sep=" ")
speedTibble <- subset(workingTibble, GameID == gameID & PlayerID == playerID)
# crunch average speed
averageSpeed <- c(averageSpeed, mean(speedTibble$Speed, na.rm = 0))
# average for accel value
accelDistance <- c(accelDistance, mean(sqrt(speedTibble$AccelX^2 + speedTibble$AccelY^2 + speedTibble$AccelZ^ 2), na.rm = 0))
# game and player id to vector
playerIDMetrics <- c(playerIDMetrics, playerID)
gameIDMetrics <- c(gameIDMetrics, gameID)
}
}
plot(accelDistance, averageSpeed)
compressedMetrics <- tibble(gameID = gameIDMetrics, playerID = playerIDMetrics, averageSpeed = averageSpeed, accelerationVector = accelDistance)
length(compressedMetrics$averageSpeed)
length(compressedMetrics$accelerationVector)
write.csv(compressedMetrics, "data/speedData.csv")
#putSQLiteHere <- "gpsData.sqlite" # could also be ":memory:"
#mySQLiteDB <- dbConnect(RSQLite::SQLite(),putSQLiteHere)
#dbWriteTable(mySQLiteDB, "gpsData", compressedMetrics, overwrite=TRUE)
#dbDisconnect(mySQLiteDB)
rpeData <- read.csv("./data/rpe.csv")
rpeDataTibble <- as_tibble(rpeData)
gameData <- read.csv("./data/game.csv")
gameDataTibble <- as_tibble(gameData)
wellnessData <- read.csv("./data/wellness.csv")
wellnessDataTibble <- as_tibble(wellnessData)
head(gpsData)