ls()
## character(0)
rm(list=ls())
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 291743 7.8 592000 15.9 460000 12.3
## Vcells 326434 2.5 786432 6.0 677388 5.2
library(MASS)
data(Boston)
str(Boston)
## 'data.frame': 506 obs. of 14 variables:
## $ crim : num 0.00632 0.02731 0.02729 0.03237 0.06905 ...
## $ zn : num 18 0 0 0 0 0 12.5 12.5 12.5 12.5 ...
## $ indus : num 2.31 7.07 7.07 2.18 2.18 2.18 7.87 7.87 7.87 7.87 ...
## $ chas : int 0 0 0 0 0 0 0 0 0 0 ...
## $ nox : num 0.538 0.469 0.469 0.458 0.458 0.458 0.524 0.524 0.524 0.524 ...
## $ rm : num 6.58 6.42 7.18 7 7.15 ...
## $ age : num 65.2 78.9 61.1 45.8 54.2 58.7 66.6 96.1 100 85.9 ...
## $ dis : num 4.09 4.97 4.97 6.06 6.06 ...
## $ rad : int 1 2 2 3 3 3 5 5 5 5 ...
## $ tax : num 296 242 242 222 222 222 311 311 311 311 ...
## $ ptratio: num 15.3 17.8 17.8 18.7 18.7 18.7 15.2 15.2 15.2 15.2 ...
## $ black : num 397 397 393 395 397 ...
## $ lstat : num 4.98 9.14 4.03 2.94 5.33 ...
## $ medv : num 24 21.6 34.7 33.4 36.2 28.7 22.9 27.1 16.5 18.9 ...
head(Boston)
## crim zn indus chas nox rm age dis rad tax ptratio black
## 1 0.00632 18 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3 396.90
## 2 0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 396.90
## 3 0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 392.83
## 4 0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 394.63
## 5 0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 396.90
## 6 0.02985 0 2.18 0 0.458 6.430 58.7 6.0622 3 222 18.7 394.12
## lstat medv
## 1 4.98 24.0
## 2 9.14 21.6
## 3 4.03 34.7
## 4 2.94 33.4
## 5 5.33 36.2
## 6 5.21 28.7
tail(Boston)
## crim zn indus chas nox rm age dis rad tax ptratio black
## 501 0.22438 0 9.69 0 0.585 6.027 79.7 2.4982 6 391 19.2 396.90
## 502 0.06263 0 11.93 0 0.573 6.593 69.1 2.4786 1 273 21.0 391.99
## 503 0.04527 0 11.93 0 0.573 6.120 76.7 2.2875 1 273 21.0 396.90
## 504 0.06076 0 11.93 0 0.573 6.976 91.0 2.1675 1 273 21.0 396.90
## 505 0.10959 0 11.93 0 0.573 6.794 89.3 2.3889 1 273 21.0 393.45
## 506 0.04741 0 11.93 0 0.573 6.030 80.8 2.5050 1 273 21.0 396.90
## lstat medv
## 501 14.33 16.8
## 502 9.67 22.4
## 503 9.08 20.6
## 504 5.64 23.9
## 505 6.48 22.0
## 506 7.88 11.9
summary(Boston)
## crim zn indus chas
## Min. : 0.00632 Min. : 0.00 Min. : 0.46 Min. :0.00000
## 1st Qu.: 0.08204 1st Qu.: 0.00 1st Qu.: 5.19 1st Qu.:0.00000
## Median : 0.25651 Median : 0.00 Median : 9.69 Median :0.00000
## Mean : 3.61352 Mean : 11.36 Mean :11.14 Mean :0.06917
## 3rd Qu.: 3.67708 3rd Qu.: 12.50 3rd Qu.:18.10 3rd Qu.:0.00000
## Max. :88.97620 Max. :100.00 Max. :27.74 Max. :1.00000
## nox rm age dis
## Min. :0.3850 Min. :3.561 Min. : 2.90 Min. : 1.130
## 1st Qu.:0.4490 1st Qu.:5.886 1st Qu.: 45.02 1st Qu.: 2.100
## Median :0.5380 Median :6.208 Median : 77.50 Median : 3.207
## Mean :0.5547 Mean :6.285 Mean : 68.57 Mean : 3.795
## 3rd Qu.:0.6240 3rd Qu.:6.623 3rd Qu.: 94.08 3rd Qu.: 5.188
## Max. :0.8710 Max. :8.780 Max. :100.00 Max. :12.127
## rad tax ptratio black
## Min. : 1.000 Min. :187.0 Min. :12.60 Min. : 0.32
## 1st Qu.: 4.000 1st Qu.:279.0 1st Qu.:17.40 1st Qu.:375.38
## Median : 5.000 Median :330.0 Median :19.05 Median :391.44
## Mean : 9.549 Mean :408.2 Mean :18.46 Mean :356.67
## 3rd Qu.:24.000 3rd Qu.:666.0 3rd Qu.:20.20 3rd Qu.:396.23
## Max. :24.000 Max. :711.0 Max. :22.00 Max. :396.90
## lstat medv
## Min. : 1.73 Min. : 5.00
## 1st Qu.: 6.95 1st Qu.:17.02
## Median :11.36 Median :21.20
## Mean :12.65 Mean :22.53
## 3rd Qu.:16.95 3rd Qu.:25.00
## Max. :37.97 Max. :50.00
names(Boston)
## [1] "crim" "zn" "indus" "chas" "nox" "rm" "age"
## [8] "dis" "rad" "tax" "ptratio" "black" "lstat" "medv"
#?Boston
library(data.table)
Boston=data.table(Boston)
tables()
## NAME NROW NCOL MB
## [1,] Boston 506 14 1
## COLS
## [1,] crim,zn,indus,chas,nox,rm,age,dis,rad,tax,ptratio,black,lstat,medv
## KEY
## [1,]
## Total: 1MB
#only one variable
summary(Boston$crim)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00632 0.08204 0.25650 3.61400 3.67700 88.98000
length(unique(Boston$crim))
## [1] 504
table(Boston$chas)
##
## 0 1
## 471 35
unique(Boston$chas)
## [1] 0 1
length(unique(Boston$chas))
## [1] 2
summary(Boston$ptratio)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 12.60 17.40 19.05 18.46 20.20 22.00
attach(Boston)
cor(ptratio,medv)
## [1] -0.5077867
cor(black,medv)
## [1] 0.3334608
cor(rm,medv)
## [1] 0.6953599
plot(Boston$medv)
plot(medv)
plot(medv,chas)
#plot(chas,medv,color=red) #color needs to be in ""
colors()
## [1] "white" "aliceblue" "antiquewhite"
## [4] "antiquewhite1" "antiquewhite2" "antiquewhite3"
## [7] "antiquewhite4" "aquamarine" "aquamarine1"
## [10] "aquamarine2" "aquamarine3" "aquamarine4"
## [13] "azure" "azure1" "azure2"
## [16] "azure3" "azure4" "beige"
## [19] "bisque" "bisque1" "bisque2"
## [22] "bisque3" "bisque4" "black"
## [25] "blanchedalmond" "blue" "blue1"
## [28] "blue2" "blue3" "blue4"
## [31] "blueviolet" "brown" "brown1"
## [34] "brown2" "brown3" "brown4"
## [37] "burlywood" "burlywood1" "burlywood2"
## [40] "burlywood3" "burlywood4" "cadetblue"
## [43] "cadetblue1" "cadetblue2" "cadetblue3"
## [46] "cadetblue4" "chartreuse" "chartreuse1"
## [49] "chartreuse2" "chartreuse3" "chartreuse4"
## [52] "chocolate" "chocolate1" "chocolate2"
## [55] "chocolate3" "chocolate4" "coral"
## [58] "coral1" "coral2" "coral3"
## [61] "coral4" "cornflowerblue" "cornsilk"
## [64] "cornsilk1" "cornsilk2" "cornsilk3"
## [67] "cornsilk4" "cyan" "cyan1"
## [70] "cyan2" "cyan3" "cyan4"
## [73] "darkblue" "darkcyan" "darkgoldenrod"
## [76] "darkgoldenrod1" "darkgoldenrod2" "darkgoldenrod3"
## [79] "darkgoldenrod4" "darkgray" "darkgreen"
## [82] "darkgrey" "darkkhaki" "darkmagenta"
## [85] "darkolivegreen" "darkolivegreen1" "darkolivegreen2"
## [88] "darkolivegreen3" "darkolivegreen4" "darkorange"
## [91] "darkorange1" "darkorange2" "darkorange3"
## [94] "darkorange4" "darkorchid" "darkorchid1"
## [97] "darkorchid2" "darkorchid3" "darkorchid4"
## [100] "darkred" "darksalmon" "darkseagreen"
## [103] "darkseagreen1" "darkseagreen2" "darkseagreen3"
## [106] "darkseagreen4" "darkslateblue" "darkslategray"
## [109] "darkslategray1" "darkslategray2" "darkslategray3"
## [112] "darkslategray4" "darkslategrey" "darkturquoise"
## [115] "darkviolet" "deeppink" "deeppink1"
## [118] "deeppink2" "deeppink3" "deeppink4"
## [121] "deepskyblue" "deepskyblue1" "deepskyblue2"
## [124] "deepskyblue3" "deepskyblue4" "dimgray"
## [127] "dimgrey" "dodgerblue" "dodgerblue1"
## [130] "dodgerblue2" "dodgerblue3" "dodgerblue4"
## [133] "firebrick" "firebrick1" "firebrick2"
## [136] "firebrick3" "firebrick4" "floralwhite"
## [139] "forestgreen" "gainsboro" "ghostwhite"
## [142] "gold" "gold1" "gold2"
## [145] "gold3" "gold4" "goldenrod"
## [148] "goldenrod1" "goldenrod2" "goldenrod3"
## [151] "goldenrod4" "gray" "gray0"
## [154] "gray1" "gray2" "gray3"
## [157] "gray4" "gray5" "gray6"
## [160] "gray7" "gray8" "gray9"
## [163] "gray10" "gray11" "gray12"
## [166] "gray13" "gray14" "gray15"
## [169] "gray16" "gray17" "gray18"
## [172] "gray19" "gray20" "gray21"
## [175] "gray22" "gray23" "gray24"
## [178] "gray25" "gray26" "gray27"
## [181] "gray28" "gray29" "gray30"
## [184] "gray31" "gray32" "gray33"
## [187] "gray34" "gray35" "gray36"
## [190] "gray37" "gray38" "gray39"
## [193] "gray40" "gray41" "gray42"
## [196] "gray43" "gray44" "gray45"
## [199] "gray46" "gray47" "gray48"
## [202] "gray49" "gray50" "gray51"
## [205] "gray52" "gray53" "gray54"
## [208] "gray55" "gray56" "gray57"
## [211] "gray58" "gray59" "gray60"
## [214] "gray61" "gray62" "gray63"
## [217] "gray64" "gray65" "gray66"
## [220] "gray67" "gray68" "gray69"
## [223] "gray70" "gray71" "gray72"
## [226] "gray73" "gray74" "gray75"
## [229] "gray76" "gray77" "gray78"
## [232] "gray79" "gray80" "gray81"
## [235] "gray82" "gray83" "gray84"
## [238] "gray85" "gray86" "gray87"
## [241] "gray88" "gray89" "gray90"
## [244] "gray91" "gray92" "gray93"
## [247] "gray94" "gray95" "gray96"
## [250] "gray97" "gray98" "gray99"
## [253] "gray100" "green" "green1"
## [256] "green2" "green3" "green4"
## [259] "greenyellow" "grey" "grey0"
## [262] "grey1" "grey2" "grey3"
## [265] "grey4" "grey5" "grey6"
## [268] "grey7" "grey8" "grey9"
## [271] "grey10" "grey11" "grey12"
## [274] "grey13" "grey14" "grey15"
## [277] "grey16" "grey17" "grey18"
## [280] "grey19" "grey20" "grey21"
## [283] "grey22" "grey23" "grey24"
## [286] "grey25" "grey26" "grey27"
## [289] "grey28" "grey29" "grey30"
## [292] "grey31" "grey32" "grey33"
## [295] "grey34" "grey35" "grey36"
## [298] "grey37" "grey38" "grey39"
## [301] "grey40" "grey41" "grey42"
## [304] "grey43" "grey44" "grey45"
## [307] "grey46" "grey47" "grey48"
## [310] "grey49" "grey50" "grey51"
## [313] "grey52" "grey53" "grey54"
## [316] "grey55" "grey56" "grey57"
## [319] "grey58" "grey59" "grey60"
## [322] "grey61" "grey62" "grey63"
## [325] "grey64" "grey65" "grey66"
## [328] "grey67" "grey68" "grey69"
## [331] "grey70" "grey71" "grey72"
## [334] "grey73" "grey74" "grey75"
## [337] "grey76" "grey77" "grey78"
## [340] "grey79" "grey80" "grey81"
## [343] "grey82" "grey83" "grey84"
## [346] "grey85" "grey86" "grey87"
## [349] "grey88" "grey89" "grey90"
## [352] "grey91" "grey92" "grey93"
## [355] "grey94" "grey95" "grey96"
## [358] "grey97" "grey98" "grey99"
## [361] "grey100" "honeydew" "honeydew1"
## [364] "honeydew2" "honeydew3" "honeydew4"
## [367] "hotpink" "hotpink1" "hotpink2"
## [370] "hotpink3" "hotpink4" "indianred"
## [373] "indianred1" "indianred2" "indianred3"
## [376] "indianred4" "ivory" "ivory1"
## [379] "ivory2" "ivory3" "ivory4"
## [382] "khaki" "khaki1" "khaki2"
## [385] "khaki3" "khaki4" "lavender"
## [388] "lavenderblush" "lavenderblush1" "lavenderblush2"
## [391] "lavenderblush3" "lavenderblush4" "lawngreen"
## [394] "lemonchiffon" "lemonchiffon1" "lemonchiffon2"
## [397] "lemonchiffon3" "lemonchiffon4" "lightblue"
## [400] "lightblue1" "lightblue2" "lightblue3"
## [403] "lightblue4" "lightcoral" "lightcyan"
## [406] "lightcyan1" "lightcyan2" "lightcyan3"
## [409] "lightcyan4" "lightgoldenrod" "lightgoldenrod1"
## [412] "lightgoldenrod2" "lightgoldenrod3" "lightgoldenrod4"
## [415] "lightgoldenrodyellow" "lightgray" "lightgreen"
## [418] "lightgrey" "lightpink" "lightpink1"
## [421] "lightpink2" "lightpink3" "lightpink4"
## [424] "lightsalmon" "lightsalmon1" "lightsalmon2"
## [427] "lightsalmon3" "lightsalmon4" "lightseagreen"
## [430] "lightskyblue" "lightskyblue1" "lightskyblue2"
## [433] "lightskyblue3" "lightskyblue4" "lightslateblue"
## [436] "lightslategray" "lightslategrey" "lightsteelblue"
## [439] "lightsteelblue1" "lightsteelblue2" "lightsteelblue3"
## [442] "lightsteelblue4" "lightyellow" "lightyellow1"
## [445] "lightyellow2" "lightyellow3" "lightyellow4"
## [448] "limegreen" "linen" "magenta"
## [451] "magenta1" "magenta2" "magenta3"
## [454] "magenta4" "maroon" "maroon1"
## [457] "maroon2" "maroon3" "maroon4"
## [460] "mediumaquamarine" "mediumblue" "mediumorchid"
## [463] "mediumorchid1" "mediumorchid2" "mediumorchid3"
## [466] "mediumorchid4" "mediumpurple" "mediumpurple1"
## [469] "mediumpurple2" "mediumpurple3" "mediumpurple4"
## [472] "mediumseagreen" "mediumslateblue" "mediumspringgreen"
## [475] "mediumturquoise" "mediumvioletred" "midnightblue"
## [478] "mintcream" "mistyrose" "mistyrose1"
## [481] "mistyrose2" "mistyrose3" "mistyrose4"
## [484] "moccasin" "navajowhite" "navajowhite1"
## [487] "navajowhite2" "navajowhite3" "navajowhite4"
## [490] "navy" "navyblue" "oldlace"
## [493] "olivedrab" "olivedrab1" "olivedrab2"
## [496] "olivedrab3" "olivedrab4" "orange"
## [499] "orange1" "orange2" "orange3"
## [502] "orange4" "orangered" "orangered1"
## [505] "orangered2" "orangered3" "orangered4"
## [508] "orchid" "orchid1" "orchid2"
## [511] "orchid3" "orchid4" "palegoldenrod"
## [514] "palegreen" "palegreen1" "palegreen2"
## [517] "palegreen3" "palegreen4" "paleturquoise"
## [520] "paleturquoise1" "paleturquoise2" "paleturquoise3"
## [523] "paleturquoise4" "palevioletred" "palevioletred1"
## [526] "palevioletred2" "palevioletred3" "palevioletred4"
## [529] "papayawhip" "peachpuff" "peachpuff1"
## [532] "peachpuff2" "peachpuff3" "peachpuff4"
## [535] "peru" "pink" "pink1"
## [538] "pink2" "pink3" "pink4"
## [541] "plum" "plum1" "plum2"
## [544] "plum3" "plum4" "powderblue"
## [547] "purple" "purple1" "purple2"
## [550] "purple3" "purple4" "red"
## [553] "red1" "red2" "red3"
## [556] "red4" "rosybrown" "rosybrown1"
## [559] "rosybrown2" "rosybrown3" "rosybrown4"
## [562] "royalblue" "royalblue1" "royalblue2"
## [565] "royalblue3" "royalblue4" "saddlebrown"
## [568] "salmon" "salmon1" "salmon2"
## [571] "salmon3" "salmon4" "sandybrown"
## [574] "seagreen" "seagreen1" "seagreen2"
## [577] "seagreen3" "seagreen4" "seashell"
## [580] "seashell1" "seashell2" "seashell3"
## [583] "seashell4" "sienna" "sienna1"
## [586] "sienna2" "sienna3" "sienna4"
## [589] "skyblue" "skyblue1" "skyblue2"
## [592] "skyblue3" "skyblue4" "slateblue"
## [595] "slateblue1" "slateblue2" "slateblue3"
## [598] "slateblue4" "slategray" "slategray1"
## [601] "slategray2" "slategray3" "slategray4"
## [604] "slategrey" "snow" "snow1"
## [607] "snow2" "snow3" "snow4"
## [610] "springgreen" "springgreen1" "springgreen2"
## [613] "springgreen3" "springgreen4" "steelblue"
## [616] "steelblue1" "steelblue2" "steelblue3"
## [619] "steelblue4" "tan" "tan1"
## [622] "tan2" "tan3" "tan4"
## [625] "thistle" "thistle1" "thistle2"
## [628] "thistle3" "thistle4" "tomato"
## [631] "tomato1" "tomato2" "tomato3"
## [634] "tomato4" "turquoise" "turquoise1"
## [637] "turquoise2" "turquoise3" "turquoise4"
## [640] "violet" "violetred" "violetred1"
## [643] "violetred2" "violetred3" "violetred4"
## [646] "wheat" "wheat1" "wheat2"
## [649] "wheat3" "wheat4" "whitesmoke"
## [652] "yellow" "yellow1" "yellow2"
## [655] "yellow3" "yellow4" "yellowgreen"
length(colors())
## [1] 657
boxplot(medv~chas,col="red")
boxplot(medv~chas,
xlab="River Facing",
ylab="Price in 1000s",
main="Housing in Boston",
col="yellowgreen")
par(bg="grey") #BACKGROUND
par(mfrow=c(2,1)) #NUMBER OF GRAPHS
plot(medv,col="yellow2") #COLOR
hist(medv) #HISTOGRAM
barplot(medv) #BARPLOT
hist(medv,col = "blue")
par(mfrow=c(1,1)) #NUMBER OF GRAPHS RECHANGED
table(chas)
## chas
## 0 1
## 471 35
pie(table(chas),labels = c("Not River Facing"," River Facing"),col=rainbow(6))
barplot(table(chas))
plot(table(chas),type="l")
#LINE PLOTS USED FOR TRENDS
plot(table(mtcars$cyl),type="l")
data("AirPassengers")
head(AirPassengers)
## [1] 112 118 132 129 121 135
plot(AirPassengers,type="l")
par(mfrow=c(3,1)) #NUMBER OF GRAPHS
plot(age,type="l",col=rainbow(6))
boxplot(age,col=rainbow(6))
hist(age,col=rainbow(6))
summary(Boston$medv)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 5.00 17.02 21.20 22.53 25.00 50.00
boxplot(Boston$medv)
library(corrplot)
par(mfrow=c(3,1))
hist(Boston$medv,col=heat.colors(7,0.6))
hist(Boston$medv,col=heat.colors(7))
hist(Boston$ptratio,col=heat.colors(7,0.6))
par(mfrow=c(3,2))
hist(Boston$ptratio,col=heat.colors(7,0.6),main=" heat.colors(7,0.6)")
hist(Boston$ptratio,col=cm.colors(7,0.6),main="cm.colors(7,0.6)")
hist(Boston$ptratio,col= topo.colors(7,0.6),main="topo.colors(7,0.6)")
hist(Boston$ptratio,col= rainbow(7,0.6),main=" rainbow(7,0.6)")
hist(Boston$ptratio,col= rainbow(12,0.6),main=" rainbow(12,0.6)")
hist(Boston$ptratio,col= rainbow(12,0.3),main=" rainbow(12,0.3)")
table(Boston$ptratio)
##
## 12.6 13 13.6 14.4 14.7 14.8 14.9 15.1 15.2 15.3 15.5 15.6 15.9 16 16.1
## 3 12 1 1 34 3 4 1 13 3 1 2 2 5 5
## 16.4 16.6 16.8 16.9 17 17.3 17.4 17.6 17.8 17.9 18 18.2 18.3 18.4 18.5
## 6 16 4 5 4 1 18 7 23 11 5 4 4 16 4
## 18.6 18.7 18.8 18.9 19 19.1 19.2 19.6 19.7 20.1 20.2 20.9 21 21.1 21.2
## 17 9 2 3 4 17 19 8 8 5 140 11 27 1 15
## 22
## 2
par(mfrow=c(1,1))
data(list = "Boston", package = "MASS")
crs=NULL
crs$dataset <- Boston
names(crs$dataset) <- gsub("-", ".", names(crs$dataset))
require(corrplot, quietly=TRUE)
crs$cor <- cor(Boston)
# Order the correlations by their strength.
crs$ord <- order(crs$cor[1,])
crs$cor <- crs$cor[crs$ord, crs$ord]
# Display the actual correlations.
print(crs$cor)
## medv black dis rm zn
## medv 1.0000000 0.33346082 0.24992873 0.69535995 0.36044534
## black 0.3334608 1.00000000 0.29151167 0.12806864 0.17552032
## dis 0.2499287 0.29151167 1.00000000 0.20524621 0.66440822
## rm 0.6953599 0.12806864 0.20524621 1.00000000 0.31199059
## zn 0.3604453 0.17552032 0.66440822 0.31199059 1.00000000
## chas 0.1752602 0.04878848 -0.09917578 0.09125123 -0.04269672
## ptratio -0.5077867 -0.17738330 -0.23247054 -0.35550149 -0.39167855
## age -0.3769546 -0.27353398 -0.74788054 -0.24026493 -0.56953734
## indus -0.4837252 -0.35697654 -0.70802699 -0.39167585 -0.53382819
## nox -0.4273208 -0.38005064 -0.76923011 -0.30218819 -0.51660371
## lstat -0.7376627 -0.36608690 -0.49699583 -0.61380827 -0.41299457
## tax -0.4685359 -0.44180801 -0.53443158 -0.29204783 -0.31456332
## rad -0.3816262 -0.44441282 -0.49458793 -0.20984667 -0.31194783
## crim -0.3883046 -0.38506394 -0.37967009 -0.21924670 -0.20046922
## chas ptratio age indus nox
## medv 0.175260177 -0.5077867 -0.37695457 -0.48372516 -0.42732077
## black 0.048788485 -0.1773833 -0.27353398 -0.35697654 -0.38005064
## dis -0.099175780 -0.2324705 -0.74788054 -0.70802699 -0.76923011
## rm 0.091251225 -0.3555015 -0.24026493 -0.39167585 -0.30218819
## zn -0.042696719 -0.3916785 -0.56953734 -0.53382819 -0.51660371
## chas 1.000000000 -0.1215152 0.08651777 0.06293803 0.09120281
## ptratio -0.121515174 1.0000000 0.26151501 0.38324756 0.18893268
## age 0.086517774 0.2615150 1.00000000 0.64477851 0.73147010
## indus 0.062938027 0.3832476 0.64477851 1.00000000 0.76365145
## nox 0.091202807 0.1889327 0.73147010 0.76365145 1.00000000
## lstat -0.053929298 0.3740443 0.60233853 0.60379972 0.59087892
## tax -0.035586518 0.4608530 0.50645559 0.72076018 0.66802320
## rad -0.007368241 0.4647412 0.45602245 0.59512927 0.61144056
## crim -0.055891582 0.2899456 0.35273425 0.40658341 0.42097171
## lstat tax rad crim
## medv -0.7376627 -0.46853593 -0.381626231 -0.38830461
## black -0.3660869 -0.44180801 -0.444412816 -0.38506394
## dis -0.4969958 -0.53443158 -0.494587930 -0.37967009
## rm -0.6138083 -0.29204783 -0.209846668 -0.21924670
## zn -0.4129946 -0.31456332 -0.311947826 -0.20046922
## chas -0.0539293 -0.03558652 -0.007368241 -0.05589158
## ptratio 0.3740443 0.46085304 0.464741179 0.28994558
## age 0.6023385 0.50645559 0.456022452 0.35273425
## indus 0.6037997 0.72076018 0.595129275 0.40658341
## nox 0.5908789 0.66802320 0.611440563 0.42097171
## lstat 1.0000000 0.54399341 0.488676335 0.45562148
## tax 0.5439934 1.00000000 0.910228189 0.58276431
## rad 0.4886763 0.91022819 1.000000000 0.62550515
## crim 0.4556215 0.58276431 0.625505145 1.00000000
# Graphically display the correlations.
corrplot(crs$cor, mar=c(0,0,1,0))
