library(readr)
library(data.table)
library(stats)
library(tibble)
library(scales)
##
## Attaching package: 'scales'
## The following object is masked from 'package:readr':
##
## col_factor
library(mlbench)
library(plyr)
library(plotfunctions)
##
## Attaching package: 'plotfunctions'
## The following object is masked from 'package:scales':
##
## alpha
getwd()
## [1] "C:/Users/charl/OneDrive/Documents"
june <- read.csv("C://Users/Charl/OneDrive/Documents/Ghemri.csv")
june
## Left Right Up Down
## 1 55 45 24 100
## 2 42 0 26 69
## 3 32 92 32 46
## 4 68 18 41 24
## 5 84 26 80 0
## 6 25 48 76 32
## 7 45 41 92 86
## 8 76 52 39 71
## 9 30 64 46 65
## 10 50 80 50 48
aggregate(Left ~ Up, june, mean)
## Up Left
## 1 24 55
## 2 26 42
## 3 32 32
## 4 39 76
## 5 41 68
## 6 46 30
## 7 50 50
## 8 76 25
## 9 80 84
## 10 92 45
aggregate(Left ~ Up, june, each(mean, median))
## Up Left.mean Left.median
## 1 24 55 55
## 2 26 42 42
## 3 32 32 32
## 4 39 76 76
## 5 41 68 68
## 6 46 30 30
## 7 50 50 50
## 8 76 25 25
## 9 80 84 84
## 10 92 45 45
aggregate(Left ~ Right+Up+Down, june, mean)
## Right Up Down Left
## 1 26 80 0 84
## 2 18 41 24 68
## 3 48 76 32 25
## 4 92 32 46 32
## 5 80 50 48 50
## 6 64 46 65 30
## 7 0 26 69 42
## 8 52 39 71 76
## 9 41 92 86 45
## 10 45 24 100 55
plot(Left ~ Up, june, xlim=c(20, 100), ylim=c(0, 100))
plot(Left ~ Right, june, xlim=c(0, 100), ylim=c(0, 100))
plot(Up ~ Down, june, xlim=c(0,100), ylim=c(0,100))
plot(Left ~ Down, june, xlim=c(0,100), ylim=c(0,100))
