| @ -0,0 +1,77 @@ | |||||
| # Look at data | |||||
| library(tidyverse) | |||||
| gpsData <- read.csv("data/gps.csv") | |||||
| gpsDataTibble <- as_tibble(gpsData) | |||||
| workingTibble <- head(gpsDataTibble, 100000) | |||||
| playerIds <-unique(workingTibble$PlayerID) | |||||
| gameIds <- unique(workingTibble$GameID) | |||||
| 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$Speed)) | |||||
| # average for accel value | |||||
| accelDistance <- c(accelDistance, mean(sqrt(speedTibble$AccelX^2 + speedTibble$AccelY^2 + speedTibble$AccelZ^ 2))) | |||||
| #xAccel <- c(xAccel, mean(speedTibble$AccelX)) | |||||
| #yAccel <- c(yAccel, mean(speedTibble$AccelY)) | |||||
| #zAccel <- c(zAccel, mean(speedTibble$AccelZ)) | |||||
| # game and player id to vector | |||||
| playerIDMetrics <- c(playerIDMetrics, playerID) | |||||
| gameIDMetrics <- c(gameIDMetrics, gameID) | |||||
| } | |||||
| } | |||||
| plot(accelDistance, averageSpeed) | |||||
| 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) | |||||