plot

myX <- rnorm(100, mean = 0, sd = 1)
myY <- rnorm(100, mean = 10, sd = 1)
plot(x = myX, y = myY)

plot

plot(x = myX, y = myY, 
  xlab = "XXXXXXXXXX", ylab = "YYYYYYYYYY")

plot

plot(x = myX, y = myY, 
  xlim = c(-10, 10), ylim = c(5, 15))

plot

plot(x = rep(1:5, 5), y = rep(1:5, each = 5),
  pch = 1:25, xlab = "", ylab = "", cex = 2)

plot

plot(x = rep(1:5, 5), y = rep(1:5, each = 5),
  pch = 1:25, xlab = "", ylab = "", cex = 2)
text(x = rep(seq(1:5), 5), y = rep(seq(1:5), each = 5),
  labels = 1:25, pos = 4)

plot

plot(x = myX, y = myY, 
  pch = c("a", "@", "#", "1", "=", "-", "_", "o", "O", "0", 
    letters[1:15]), cex = 2)

plot

plot(x = myX, y = myY, 
  cex = seq(from = 0.5, to = 5, length.out = 100))

plot

plot(x = myX, y = myY, 
  cex = seq(from = 0.5, to = 5, length.out = 100),
  pch = 16,
  col = sample(colors(), 100))

plot

myX <- rnorm(100)
myY <- rnorm(100)
dfGraph <- data.frame(myX, myY)

plot

head(dfGraph, n = 20)

##            myX         myY
## 1   1.54652775  0.98203127
## 2   1.92331768  0.60806081
## 3   0.08341063  0.02792164
## 4   0.58529863  0.47730264
## 5   1.68783551 -0.13917972
## 6   1.17642085 -0.19342129
## 7   0.06981720 -1.26890972
## 8   2.38322205 -0.31977800
## 9   0.26150711 -0.05256700
## 10 -0.37503628 -1.31416568
## 11  0.85857806  1.75393012
## 12 -0.81217396  0.23898354
## 13  0.74970325  0.25122926
## 14  0.10556934  1.34485148
## 15  0.16730426 -1.43159322
## 16  0.76798213 -2.01158330
## 17  1.87526397 -1.35214636
## 18 -0.57788954 -0.06158261
## 19 -1.24514382  0.85183678
## 20 -2.09958731  0.45206061

plot

dfGraph <- dfGraph[order(dfGraph$myX),]
dfGraph$myCol <- colorRampPalette(c("blue", "yellow", "red"))(100)

plot

head(dfGraph, n = 20)

##           myX        myY   myCol
## 20 -2.0995873  0.4520606 #0000FF
## 21 -2.0194602  0.4392399 #0505F9
## 92 -1.8269490  1.6016332 #0A0AF4
## 52 -1.6992173 -0.4633641 #0F0FEF
## 98 -1.6970580 -0.4777775 #1414EA
## 64 -1.6641388 -0.4515215 #1919E5
## 68 -1.6381789 -0.4403694 #1E1EE0
## 54 -1.6153006 -0.0384538 #2424DA
## 34 -1.4227258  1.2343830 #2929D5
## 43 -1.3993424  0.1400011 #2E2ED0
## 84 -1.3755416 -0.9518039 #3333CB
## 63 -1.3416515 -0.6004861 #3838C6
## 19 -1.2451438  0.8518368 #3D3DC1
## 87 -1.1346758 -0.5575879 #4242BC
## 90 -1.0717999  0.2259167 #4848B6
## 89 -1.0340338  0.4557486 #4D4DB1
## 51 -0.9702982 -0.8304358 #5252AC
## 26 -0.9616053 -1.3683735 #5757A7
## 71 -0.9427434  0.8052766 #5C5CA2
## 12 -0.8121740  0.2389835 #61619D

plot

dfGraph <- dfGraph[order(dfGraph$myY),]
dfGraph$myCex <- seq(from = 0.5, to = 5, length.out = 100)

plot

head(dfGraph, n = 20)

##            myX        myY   myCol     myCex
## 83  1.06637947 -2.5356713 #FF7100 0.5000000
## 16  0.76798213 -2.0115833 #FF9F00 0.5454545
## 57 -0.12255446 -1.9494928 #D3D32B 0.5909091
## 82 -0.17940086 -1.9118695 #C3C33B 0.6363636
## 15  0.16730426 -1.4315932 #FFE700 0.6818182
## 37  0.10491443 -1.4188780 #FFF200 0.7272727
## 26 -0.96160525 -1.3683735 #5757A7 0.7727273
## 17  1.87526397 -1.3521464 #FF1400 0.8181818
## 10 -0.37503628 -1.3141657 #9A9A64 0.8636364
## 7   0.06981720 -1.2689097 #F7F707 0.9090909
## 96  0.08490146 -1.0868609 #FFFC00 0.9545455
## 31  1.77603144 -1.0242393 #FF1900 1.0000000
## 84 -1.37554156 -0.9518039 #3333CB 1.0454545
## 51 -0.97029818 -0.8304358 #5252AC 1.0909091
## 88 -0.26626962 -0.7749495 #AFAF4F 1.1363636
## 77  0.73395525 -0.7674954 #FFA900 1.1818182
## 35  0.84970336 -0.7146479 #FF8000 1.2272727
## 65 -0.23558603 -0.6868824 #B4B44A 1.2727273
## 59 -0.76198487 -0.6856236 #676797 1.3181818
## 60  0.31187308 -0.6089887 #FFD300 1.3636364

plot

plot(x = dfGraph$myX, y = dfGraph$myY, 
  cex = dfGraph$myCex, pch = 16, col = dfGraph$myCol, 
  xlab = "", ylab = "")

plot

dfGraph$grupo <- factor(
  sample(letters[1:5], size = 100, replace = TRUE))

plot

head(dfGraph, n = 20)

##            myX        myY   myCol     myCex grupo
## 83  1.06637947 -2.5356713 #FF7100 0.5000000     e
## 16  0.76798213 -2.0115833 #FF9F00 0.5454545     b
## 57 -0.12255446 -1.9494928 #D3D32B 0.5909091     b
## 82 -0.17940086 -1.9118695 #C3C33B 0.6363636     c
## 15  0.16730426 -1.4315932 #FFE700 0.6818182     b
## 37  0.10491443 -1.4188780 #FFF200 0.7272727     e
## 26 -0.96160525 -1.3683735 #5757A7 0.7727273     a
## 17  1.87526397 -1.3521464 #FF1400 0.8181818     a
## 10 -0.37503628 -1.3141657 #9A9A64 0.8636364     e
## 7   0.06981720 -1.2689097 #F7F707 0.9090909     c
## 96  0.08490146 -1.0868609 #FFFC00 0.9545455     b
## 31  1.77603144 -1.0242393 #FF1900 1.0000000     a
## 84 -1.37554156 -0.9518039 #3333CB 1.0454545     b
## 51 -0.97029818 -0.8304358 #5252AC 1.0909091     b
## 88 -0.26626962 -0.7749495 #AFAF4F 1.1363636     e
## 77  0.73395525 -0.7674954 #FFA900 1.1818182     e
## 35  0.84970336 -0.7146479 #FF8000 1.2272727     a
## 65 -0.23558603 -0.6868824 #B4B44A 1.2727273     d
## 59 -0.76198487 -0.6856236 #676797 1.3181818     b
## 60  0.31187308 -0.6089887 #FFD300 1.3636364     e

plot

str(dfGraph)

## 'data.frame':    100 obs. of  5 variables:
##  $ myX  : num  1.066 0.768 -0.123 -0.179 0.167 ...
##  $ myY  : num  -2.54 -2.01 -1.95 -1.91 -1.43 ...
##  $ myCol: chr  "#FF7100" "#FF9F00" "#D3D32B" "#C3C33B" ...
##  $ myCex: num  0.5 0.545 0.591 0.636 0.682 ...
##  $ grupo: Factor w/ 5 levels "a","b","c","d",..: 5 2 2 3 2 5 1 1 5 3 ...

plot

plot(x = dfGraph$myX, y = dfGraph$myY, 
  pch = 16, xlab = "", ylab = "",
  col = as.numeric(dfGraph$grupo))

plot

plot(x = dfGraph$myX, y = dfGraph$myY, pch = 16, xlab = "", 
  ylab = "", cex = 2, col = as.numeric(dfGraph$grupo))
legend("topleft", fill = seq_along(levels(dfGraph$grupo)), 
  legend = levels(dfGraph$grupo))

plot

plot(x = dfGraph$myX, y = dfGraph$myY, 
  pch = as.numeric(dfGraph$grupo), xlab = "", ylab = "", 
  cex = 2, col = as.numeric(dfGraph$grupo))
legend("topleft", pch = seq_along(levels(dfGraph$grupo)), 
  legend = levels(dfGraph$grupo), 
  col = seq_along(levels(dfGraph$grupo)))

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'b')

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'p') 

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'l') 

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'c') 

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'o') 

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'h') 

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 's') 

plot

myX <- 1:20
myY <- rnorm(20, mean = 10, sd = 1)
plot(x = myX, y = myY, type = 'n') 

plot

plot(x = myX, y = myY, type = 'n') 
grid(lwd = 3, lty = 1)
points(x = myX, y = myY, type = "l", lwd = 2)

plot

plot(x = myX, y = myY, type = 'l', lwd = 2) 
grid(lwd = 3, lty = 1)

plot

plot(x = myX, y = myY, type = 'l', lwd = 2, 
  panel.first = grid(lwd = 3, lty = 1)) 

plot

op <- par(no.readonly = TRUE)
par(mfrow = c(1, 2))
plot(x = myX, y = myY, type = 'l', lwd = 2) 
grid(lwd = 3, lty = 1)
plot(x = myX, y = myY, type = 'l', lwd = 2, 
  panel.first = grid(lwd = 3, lty = 1))

plot

par(op)

plot

par(mfrow = c(1, 2), mar = c(2, 2, 1, 1))
plot(x = myX, y = myY, type = 'l', lwd = 2) 
grid(lwd = 3, lty = 1)
plot(x = myX, y = myY, type = 'l', lwd = 2, 
  panel.first = grid(lwd = 3, lty = 1))

plot

par(op)

plot

par(mfrow = c(2, 2), mar = c(2, 2, 1, 1))
graph4 <- lapply(1:4, function(i){
  plot(x = rnorm(100), 
    y = rnorm(100), 
    col = i, pch = 16)
})

plot

par(op)

plot

plot(x = myX, y = myY, type = 'l', lwd = 2)
abline(h = mean(myY), lwd = 1, lty = 2)
abline(v = myX[myY == min(myY)], col = 4, lty = 2)
abline(v = myX[myY == max(myY)], col = 2, lty = 2)

hist

myX <- list(
  rnorm(1000),
  rgamma(1000, shape = 1),
  sample(1:100, size = 1000, replace = TRUE),
  rbeta(1000, shape1 = 1, shape2 = 2)
)
myTitle <- c("Normal", "Gamma", "Uniform", "Beta")

hist

par(mfrow = c(2, 2), mar = c(2, 2, 1, 1))
tr <- lapply(1:4, function(i){
  hist(myX[[i]], col = heat.colors(15), 
    main = myTitle[i]
  )
})

hist

par(op)

hist

myX <- rnorm(1000)
par(mfrow = c(1, 2), mar = c(1, 1, 1, 1))
hist(myX, axes = FALSE, col = rainbow(100))
hist(myX, axes = FALSE, nclass = 100, col = rainbow(100))

hist

par(op)

barplot

barplot

pkgCheck <- function(x){ 
    if (!require(x, character.only = TRUE)){
        install.packages(x, dependencies = TRUE)
        if(!require(x, character.only = TRUE)) {
            stop()
        }
    }
}
pkgCheck("palettesForR")

barplot

# pkgCheck("palettesForR")
myX <- rnorm(3, mean = 10)
barplot(myX, names.arg = c("A", "B", "C"), col = Cool_gpl)

barplot

par(mar = c(1, 1, 1, 1))
myX <- matrix(c(4, 5, 8, 4, 6, 2, 3, 4, 5), nrow = 3)
barplot(myX, axes = FALSE, col = Pastels_gpl[1:3])

barplot

par(mar = c(1, 1, 1, 1))
barplot(myX, axes = FALSE, col = Pastels_gpl[1:3], 
  beside = TRUE, legend.text = c("A", "B", "C"))

plot + barplot

plot + barplot

n <- 50
myX <- rnorm(n)
myY <- rnorm(n)
myCol <- c(2, sample(c(4, 2), size = (n - 1), replace = TRUE))
myColors <- colorRampPalette(c("blue", "red"))(100)
head(data.frame(myX, myY, myCol))

##          myX         myY myCol
## 1 -0.7761458 -1.24459376     2
## 2  0.1938932  0.04129434     4
## 3 -0.9152905 -1.07962279     4
## 4 -0.9595136  2.58892371     2
## 5  1.7527446 -0.32798150     2
## 6  1.8579302 -0.05269327     2

plot + barplot

myYCut <- cut(myY, breaks = -4:4)
myXCut <- cut(myX, breaks = -4:4)
print(myXCut)

##  [1] (-1,0]  (0,1]   (-1,0]  (-1,0]  (1,2]   (1,2]   (0,1]   (0,1]  
##  [9] (-2,-1] (0,1]   (0,1]   (0,1]   (-1,0]  (-2,-1] (0,1]   (0,1]  
## [17] (0,1]   (0,1]   (0,1]   (-3,-2] (0,1]   (0,1]   (0,1]   (0,1]  
## [25] (-1,0]  (-1,0]  (1,2]   (-1,0]  (-1,0]  (0,1]   (-1,0]  (-1,0] 
## [33] (-2,-1] (0,1]   (-1,0]  (0,1]   (-2,-1] (0,1]   (0,1]   (0,1]  
## [41] (0,1]   (0,1]   (0,1]   (0,1]   (0,1]   (-2,-1] (-2,-1] (0,1]  
## [49] (-1,0]  (1,2]  
## Levels: (-4,-3] (-3,-2] (-2,-1] (-1,0] (0,1] (1,2] (2,3] (3,4]

plot + barplot

myYCutCol <- table(myCol, myYCut)
myXCutCol <- table(myCol, myXCut)
print(myXCutCol)

##      myXCut
## myCol (-4,-3] (-3,-2] (-2,-1] (-1,0] (0,1] (1,2] (2,3] (3,4]
##     2       0       0       5      5     9     4     0     0
##     4       0       1       1      7    18     0     0     0

plot + barplot

xCol <- round(
  myXCutCol[1,] / (myXCutCol[1,] + myXCutCol[2,]) * 100
)
xCol[is.na(xCol) | xCol == 0] <- 1
yCol <- round(
  myYCutCol[1,] / (myYCutCol[1,] + myYCutCol[2,]) * 100
)
yCol[is.na(yCol) | yCol == 0] <- 1
print(xCol)

## (-4,-3] (-3,-2] (-2,-1]  (-1,0]   (0,1]   (1,2]   (2,3]   (3,4] 
##       1       1      83      42      33     100       1       1

plot + barplot

par(mar = c(2, 3, 1, 1))
layout(matrix(c(1, 1, 0, 
                2, 2, 3, 
                2, 2, 3), ncol = 3, byrow = TRUE))
barplot(table(myXCut), las = 1, col = myColors[xCol])
plot(x = myX, y = myY, col = myCol, pch = 16, 
  xlim = c(-4, 4), ylim = c(-4, 4), cex = 1.5, 
  panel.first = grid())
barplot(table(myYCut), las = 1, horiz = TRUE, 
  col = myColors[yCol])

plot + barplot

plot + barplot

graphBarplotCol <- function(n){
  myX <- rnorm(n)
  myY <- rnorm(n)
  myCol <- c(2, sample(c(4, 2), size = (n - 1), replace = TRUE))
  myColors <- colorRampPalette(c("blue", "red"))(100)
  myYCut <- cut(myY, breaks = -4:4)
  myXCut <- cut(myX, breaks = -4:4)
  myYCutCol <- table(myCol, myYCut)
  myXCutCol <- table(myCol, myXCut)
  xCol <- round(
    myXCutCol[1,] / (myXCutCol[1,] + myXCutCol[2,]) * 100
  )
  xCol[is.na(xCol) | xCol == 0] <- 1
  yCol <- round(
    myYCutCol[1,] / (myYCutCol[1,] + myYCutCol[2,]) * 100
  )
  yCol[is.na(yCol) | yCol == 0] <- 1
  op <- par(no.readonly = TRUE)
  par(mar = c(2, 3, 1, 1))
  layout(matrix(c(1, 1, 0, 
                  2, 2, 3, 
                  2, 2, 3), ncol = 3, byrow = TRUE))
  barplot(table(myXCut), las = 1, col = myColors[xCol])
  plot(x = myX, y = myY, col = myCol, pch = 16, 
    xlim = c(-4, 4), ylim = c(-4, 4), cex = 1.5, 
    panel.first = grid())
  barplot(table(myYCut), las = 1, horiz = TRUE, 
    col = myColors[yCol])
  par(op)
}

plot + barplot

graphBarplotCol(n = 10)

plot + barplot

plot + barplot

graphBarplotCol(n = 1000)

plot + barplot

boxplot

df <- data.frame(
  box1 = rnorm(1000), 
  box2 = rgamma(1000, shape = 1), 
  box3 = sample(-3:3, size = 1000, replace = TRUE),
  box4 = rbeta(1000, shape1 = 1, shape2 = 2)
)

boxplot

boxplot(df, col = c(
  rgb(0, 94, 255, maxColorValue = 255),  
  rgb(255, 0, 174, maxColorValue = 255),  
  rgb(255, 136, 0, maxColorValue = 255),  
  rgb(119, 255, 0, maxColorValue = 255)))

boxplot

boxplot

df$cat <- sample(
  c("w", "x", "y", "z"), 
  size = 1000, 
  replace = TRUE)

boxplot

boxplot(df$box3 ~ df$cat, col = c(
  rgb(0, 94, 255, maxColorValue = 255),  
  rgb(255, 0, 174, maxColorValue = 255),  
  rgb(255, 136, 0, maxColorValue = 255),  
  rgb(119, 255, 0, maxColorValue = 255)), ylab = "Box3")

boxplot

boxplot

df$cat2 <- sample(
  1:3, 
  size = 1000, 
  replace = TRUE)

boxplot

boxplot(df$box4 ~ df$cat*df$cat2, col = c(
  rgb(0, 94, 255, maxColorValue = 255),  
  rgb(255, 0, 174, maxColorValue = 255),  
  rgb(255, 136, 0, maxColorValue = 255),  
  rgb(119, 255, 0, maxColorValue = 255)), ylab = "Box4")

boxplot

boxplot

boxplot(df$box4 ~ df$cat2*df$cat, col = c(
  rgb(0, 94, 255, maxColorValue = 255),  
  rgb(255, 0, 174, maxColorValue = 255),  
  rgb(255, 136, 0, maxColorValue = 255)), ylab = "Box4")

boxplot