install.packages ("circlize")
library ("circlize") #how to load a package click runset.seed(123)
mat = matrix(sample(1:100, 18, replace = TRUE), 3, 6)
rownames(mat) = letters[1:3]
colnames(mat) = LETTERS[1:6]
### basic settings
par(mfrow = c(3, 2))
par(mar = c(1, 1, 1, 1))
chordDiagram(mat)
circos.clear()
circos.par(gap.degree = c(rep(2, nrow(mat)-1), 10, rep(2, ncol(mat)-1), 10))
chordDiagram(mat)
circos.clear()
circos.par(start.degree = 90)
chordDiagram(mat)
circos.clear()
chordDiagram(mat, order = c("A", "B", "a", "C", "D", "b", "E", "F", "c"))
chordDiagram(mat, directional = TRUE)
chordDiagram(mat, directional = TRUE, diffHeight = 0.06)
circos.clear()
################ example 2 ###############################
set.seed(123)
mat = matrix(sample(1:100, 18, replace = TRUE), 3, 6)
rownames(mat) = letters[1:3]
colnames(mat) = LETTERS[1:6]
### colors settings
rand_color = function(n, alpha = 1) {
return(rgb(runif(n), runif(n), runif(n), alpha = alpha))
}
par(mfrow = c(3, 3))
par(mar = c(1, 1, 1, 1))
grid.col = NULL
grid.col[letters[1:3]] = c("red", "green", "blue")
grid.col[LETTERS[1:6]] = "grey"
chordDiagram(mat, grid.col = grid.col)
chordDiagram(mat, grid.col = grid.col, transparency = 0.5)
col_mat = rand_color(length(mat), alpha = 0.5)
dim(col_mat) = dim(mat)
chordDiagram(mat, grid.col = grid.col, col = col_mat)
chordDiagram(mat, grid.col = grid.col,
col = colorRamp2(quantile(mat, seq(0, 1, by = 0.1)),
rev(heat.colors(11))), transparency = 0.5)
chordDiagram(mat, grid.col = grid.col, row.col = 1:3, transparency = 0.5)
chordDiagram(mat, grid.col = grid.col, column.col = 1:6, transparency = 0.5)
chordDiagram(mat, grid.col = grid.col, row.col = c("#FF000080", "#00FF0010", "#0000FF10"))
circos.clear()
#we deleted the ", the minus and the spaces between my datamydata <- rnorm(100, mean = 0, sd = 1)
data.mean <- mean(mydata)
data.mean # Print the value of data.mean## [1] -0.003076955Creating vectors:
batman<-20
superman<-10
mixed<-c(batman, superman)
mixed## [1] 20 10#question 4celsius <- c(17 ,21 ,18 ,21 ,14)
fahrenheit <- celsius *9/5 + 32
fahrenheit## [1] 62.6 69.8 64.4 69.8 57.2a <- seq(from = 10, to = 50, by = 10)
b <- seq(from = 12, to = 14, by = 1)
c <- seq(from = 97, to = 137, by = 10)
final <- c (a, b, c)
final## [1] 10 20 30 40 50 12 13 14 97 107 117 127 137question 7
rep(1:5, each = 2, times = 2)## [1] 1 1 2 2 3 3 4 4 5 5 1 1 2 2 3 3 4 4 5 5question 8
a <- seq(from = 1, to = 10, by = 1)
squares <- a^2
squares## [1] 1 4 9 16 25 36 49 64 81 100mean(squares)## [1] 38.5median(squares)## [1] 30.5Sampling Data and Descriptive Statistics
Question 9
normal.samp <- rnorm(50, mean = 30, sd = 5)
normal.samp## [1] 24.31977 35.57763 33.76261 26.53766 34.24919 22.03331 37.70412
## [8] 46.39708 27.94941 32.33834 33.25904 36.43765 24.80625 33.98182
## [15] 38.08659 27.19818 25.73394 31.14077 24.81628 37.33287 32.23367
## [22] 27.79545 30.01957 35.57907 37.78089 15.86740 33.57190 26.59613
## [29] 29.94045 20.63804 26.59845 39.67853 28.60232 30.05890 34.78857
## [36] 21.84354 35.49354 32.80471 23.88351 29.68100 32.98873 26.72659
## [43] 29.44618 30.31089 19.68987 36.74066 34.96306 33.28746 26.97975
## [50] 32.29443Question 10
min(normal.samp)## [1] 15.8674max(normal.samp)## [1] 46.39708runif (25, min=21.99232 , max = 46.2052)## [1] 29.04144 43.78135 40.33146 42.53120 35.28358 22.89214 45.88126
## [8] 40.51062 35.61529 45.54123 32.92130 24.75699 30.32487 39.24129
## [15] 44.25922 29.55289 27.88515 45.56325 44.02244 23.20671 23.19473
## [22] 35.09514 41.48117 33.87327 29.43773Question 11
rnorm(100 , mean = 0, sd = 1) ## [1] -0.999615004 -1.277685754 -0.163228657 -0.191343649 0.896999987
## [6] 0.293626303 -0.484837432 0.224091817 0.949161938 -1.342107961
## [11] -0.968359083 1.569695435 0.457174846 0.315691637 -1.080574150
## [16] -0.755305233 0.311391380 -1.765024020 -1.309146535 1.257647431
## [21] -0.102743856 0.624925646 -0.701628902 0.596967998 -0.453295031
## [26] -1.194989073 0.845945113 0.236280398 2.295097798 -0.592311428
## [31] -0.734855363 0.863774257 -1.752011812 0.001937284 1.026726646
## [36] 0.002540859 -0.651659169 1.318964806 0.568338219 -0.433261810
## [41] 0.622596888 -0.289984636 0.080143680 -0.705812796 1.517507354
## [46] -0.887102110 -0.321107103 -0.303857158 0.714523438 0.831179966
## [51] 0.529109170 0.123574343 -0.263523299 0.910987026 -1.081614034
## [56] -0.808219502 -1.246222371 -0.229229667 -0.862184784 0.470131519
## [61] -0.123683490 0.238162268 0.542103542 -1.586157285 -1.113199398
## [66] 1.979237152 1.762246692 0.904215168 3.063960514 0.043477024
## [71] 0.603745477 -0.175998885 1.468588922 0.796650352 0.713663577
## [76] -1.015426932 -0.780391986 -0.753437209 -1.509541731 -0.218258044
## [81] -0.018815972 -0.490493599 1.182334864 -0.746644986 -0.724955883
## [86] 2.333990177 0.103059977 0.809380685 -1.094289274 0.163778696
## [91] 0.423488363 0.238339676 0.579699101 0.447000014 0.626917869
## [96] -0.718147810 0.105565672 -0.590916746 -0.533211053 0.207992924runif (100, min=0 , max = 10) ## [1] 1.1857555 9.9817238 2.1886438 5.0901349 3.1316186 6.7383486 2.5761745
## [8] 8.0827708 9.7946126 7.2058402 7.7093975 3.8990060 3.3688837 8.0867962
## [15] 0.4131971 9.7460928 1.0108710 3.1767600 2.5268789 0.2606342 7.7888228
## [22] 2.9197604 4.5422577 5.1648255 7.9825465 9.2964519 8.7340526 3.2100372
## [29] 3.6431532 3.8108274 6.7450981 0.4952194 1.1940367 4.1360692 9.4074537
## [36] 7.3301123 3.8482014 1.1479443 5.7765550 0.4115933 5.0747782 2.9650570
## [43] 7.4922331 7.9067735 2.9978377 7.7308038 0.3322522 9.4896776 8.9932425
## [50] 5.3220006 9.1737650 4.2441538 5.4952031 4.2597134 4.8553964 3.9572889
## [57] 4.4668361 8.0123140 3.6279371 5.4900376 0.4492202 6.9829933 5.1716438
## [64] 1.8007728 3.6034071 9.0994303 9.2611042 2.1486510 3.0168720 1.1498917
## [71] 3.2500667 2.0809384 3.7871727 7.7777162 0.1784647 4.4695390 6.1533691
## [78] 4.9334481 7.7344524 9.7154400 7.6213012 4.3889280 4.3317986 2.6912915
## [85] 8.8841516 7.6362898 9.0319227 3.8811807 4.2945279 4.7064648 8.5768505
## [92] 1.9771573 6.1502612 3.8811282 0.9015941 5.8771150 3.4415108 2.0978225
## [99] 0.3880289 1.3799295