getwd()
## [1] "C:/Users/dell/Desktop/test3"
setwd("C:/Users/dell/Desktop")
dir(,pattern = ".csv")
## [1] "BigDiamonds.csv" "BigDiamonds.csv (2).zip"
memory.limit()
## [1] 1535
memory.size()
## [1] 18.5
rm(list = ls())
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 367092 9.9 750400 20.1 460000 12.3
## Vcells 381970 3.0 1023718 7.9 752284 5.8
plot(iris)
plot(iris[4:5])
plot(mtcars$mpg,mtcars$gear)
plot(mtcars$gear,mtcars$mpg)
plot(AirPassengers)
plot(mtcars$mpg)
plot(mtcars$mpg,type="l")
plot(mtcars$mpg,type="h")
boxplot(mtcars$mpg)
boxplot(mtcars$mpg~mtcars$gear)
barplot(mtcars$mpg)
table(mtcars$mpg,mtcars$gear)
##
## 3 4 5
## 10.4 2 0 0
## 13.3 1 0 0
## 14.3 1 0 0
## 14.7 1 0 0
## 15 0 0 1
## 15.2 2 0 0
## 15.5 1 0 0
## 15.8 0 0 1
## 16.4 1 0 0
## 17.3 1 0 0
## 17.8 0 1 0
## 18.1 1 0 0
## 18.7 1 0 0
## 19.2 1 1 0
## 19.7 0 0 1
## 21 0 2 0
## 21.4 1 1 0
## 21.5 1 0 0
## 22.8 0 2 0
## 24.4 0 1 0
## 26 0 0 1
## 27.3 0 1 0
## 30.4 0 1 1
## 32.4 0 1 0
## 33.9 0 1 0
barplot(table(mtcars$mpg,mtcars$gear))
barplot(table(mtcars$gear,mtcars$mpg))
par(mfrow=c(1,1))
hist(mtcars$mpg)
hist(mtcars$mpg,breaks = 10)
rug(mtcars$mpg)
plot(density(mtcars$mpg))
pie(table(mtcars$cyl))
pie(table(mtcars$gear))
par(mfrow=c(2,4))
pie(table(mtcars$cyl))
barplot(table(mtcars$cyl))
hist(mtcars$cyl)
plot(table(mtcars$cyl),type='l')
pie(table(mtcars$gear))
barplot(table(mtcars$gear))
hist(mtcars$gear)
plot(table(mtcars$gear),type='l')
par(mfrow=c(1,1))
par(bg="grey")
boxplot(iris$Sepal.Length~iris$Species)
par(mfrow=c(1,1))
par(bg="green")
boxplot(iris$Sepal.Length~iris$Species)
par(bg="yellow")
boxplot(iris$Sepal.Length~iris$Species,main="Box Plot of Sepal Length by Species")
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"
par(bg="yellowgreen")
boxplot(iris$Sepal.Length~iris$Species,main="Box Plot of Sepal Length by Species",xlab="Species",ylab="Sepal Length of Iris Flowers in cm")
data("trees")
#box,bar,scatter,line plot in 1 screen
#titles, xlab, ylab, color bg
str(trees)
## 'data.frame': 31 obs. of 3 variables:
## $ Girth : num 8.3 8.6 8.8 10.5 10.7 10.8 11 11 11.1 11.2 ...
## $ Height: num 70 65 63 72 81 83 66 75 80 75 ...
## $ Volume: num 10.3 10.3 10.2 16.4 18.8 19.7 15.6 18.2 22.6 19.9 ...
par(mfrow=c(2,2))
par(bg="wheat1")
attach(trees)
boxplot(Girth~Volume,main="Girth vs Volume",xlab="Girth",ylab="Volume")
barplot(Girth,main="Girth",ylab="Girth")
plot(Girth,Volume,main="Girth vs Volume",xlab="Girth",ylab="Volume")
plot(Girth,type="l",main="Girth ",ylab="Girth")
par(mfrow=c(2,2))
par(bg="skyblue2")
boxplot(trees$Height~trees$Volume, main="box plot of tree height by volume", xlab="Volume", ylab="height of trees")
barplot(trees$Height, main="box plot of tree height by volume", xlab="Volume", ylab="height")
plot(table(trees$Girth),type='l')
plot(table(trees$Girth),type='h')
par(mfrow=c(2,4))
par(bg="yellowgreen")
boxplot(trees$Girth~trees$Height)
barplot(trees$Girth)
scatter.smooth(trees$Girth)
line(trees$Height)
##
## Call:
## line(trees$Height)
##
## Coefficients:
## [1] 72.75 0.25
boxplot(trees$Girth~trees$Height,main="Trees,",xlab="Girth",ylab="Height")
par(mfrow=c(1,4))
#par(bg="redgreen")
attach(trees)
## The following objects are masked from trees (pos = 3):
##
## Girth, Height, Volume
boxplot(Height~Volume,main="Ravi - Height vs Volume",xlab="Girth",ylab="Volume")
barplot(Height,main="Girth",ylab="Girth")
plot(Height,Volume,main="Ravi - Height vs Volume",xlab="Height",ylab="Volume")
plot(Height,type="l",main="Height ",ylab="Height")
par(mfrow=c(1,1))
plot(Height,col="blue",type="l",main="Height ",ylab="Height")
barplot(Height,main="Girth",ylab="Girth",col = "wheat1")
par(mfrow=c(2,3))
hist(iris$Sepal.Length,col=topo.colors(3))
hist(iris$Sepal.Length,col=topo.colors(6))
hist(iris$Sepal.Length,col=topo.colors(9))
hist(iris$Sepal.Length,col=topo.colors(3,0.1))
hist(iris$Sepal.Length,col=topo.colors(3,0.6))
hist(iris$Sepal.Length,col=topo.colors(3,0.9))
par(mfrow=c(3,5))
hist(iris$Sepal.Length,col=topo.colors(6))
hist(iris$Sepal.Length,col=cm.colors(6))
hist(iris$Sepal.Length,col=terrain.colors(6))
hist(iris$Sepal.Length,col=heat.colors(6))
hist(iris$Sepal.Length,col=rainbow(6))
hist(iris$Sepal.Length,col=topo.colors(3))
hist(iris$Sepal.Length,col=cm.colors(3))
hist(iris$Sepal.Length,col=terrain.colors(3))
hist(iris$Sepal.Length,col=heat.colors(3))
hist(iris$Sepal.Length,col=rainbow(3))
hist(iris$Sepal.Length,col=topo.colors(6,0.2))
hist(iris$Sepal.Length,col=cm.colors(6,0.2))
hist(iris$Sepal.Length,col=terrain.colors(6,0.2))
hist(iris$Sepal.Length,col=heat.colors(6,0.2))
hist(iris$Sepal.Length,col=rainbow(6,0.2))
library(RColorBrewer)
par(mfrow=c(1,1))
display.brewer.all()
par(mfrow=c(2,3))
hist(iris$Sepal.Length,col=brewer.pal(6,"Set1"),main="Set1")
hist(iris$Sepal.Length,col=brewer.pal(6,"Set2"),main="Set2")
hist(iris$Sepal.Length,col=brewer.pal(6,"Set3"),main="Set3")
hist(iris$Sepal.Length,col=brewer.pal(6,"Greens"),main="Greens")
hist(iris$Sepal.Length,col=brewer.pal(6,"Blues"),main="Blues")
hist(iris$Sepal.Length,col=brewer.pal(6,"Reds"),main="Reds")
par(mfrow=c(1,1))
library(hexbin)
hexbin(iris$Species,iris$Sepal.Length)
## 'hexbin' object from call: hexbin(x = iris$Species, y = iris$Sepal.Length)
## n = 150 points in nc = 48 hexagon cells in grid dimensions 36 by 31
plot(iris$Sepal.Length)
plot(hexbin(iris$Species,iris$Sepal.Length))
plot(mtcars$mpg,mtcars$cyl)
plot(hexbin(mtcars$mpg,mtcars$cyl))
library(tabplot)
## Loading required package: bit
## Attaching package bit
## package:bit (c) 2008-2012 Jens Oehlschlaegel (GPL-2)
## creators: bit bitwhich
## coercion: as.logical as.integer as.bit as.bitwhich which
## operator: ! & | xor != ==
## querying: print length any all min max range sum summary
## bit access: length<- [ [<- [[ [[<-
## for more help type ?bit
##
## Attaching package: 'bit'
## The following object is masked from 'package:base':
##
## xor
## Loading required package: ff
## Attaching package ff
## - getOption("fftempdir")=="C:/Users/dell/AppData/Local/Temp/RtmpYVadJe"
## - getOption("ffextension")=="ff"
## - getOption("ffdrop")==TRUE
## - getOption("fffinonexit")==TRUE
## - getOption("ffpagesize")==65536
## - getOption("ffcaching")=="mmnoflush" -- consider "ffeachflush" if your system stalls on large writes
## - getOption("ffbatchbytes")==16095641.6 -- consider a different value for tuning your system
## - getOption("ffmaxbytes")==804782080 -- consider a different value for tuning your system
##
## Attaching package: 'ff'
## The following objects are masked from 'package:bit':
##
## clone, clone.default, clone.list
## The following objects are masked from 'package:utils':
##
## write.csv, write.csv2
## The following objects are masked from 'package:base':
##
## is.factor, is.ordered
## Loading required package: ffbase
##
## Attaching package: 'ffbase'
## The following objects are masked from 'package:ff':
##
## [.ff, [.ffdf, [<-.ff, [<-.ffdf
## The following objects are masked from 'package:base':
##
## %in%, table
## Standard deviations are plot by default. See argument numMode of plot.tabplot.
tableplot(iris)
tableplot(mtcars)
## Warning in tableplot_checkBins(nBins, max(N, 2)): Setting nBins (100) to
## number of rows (32)
library(ggplot2)
tableplot(diamonds)
library(vcd)
## Loading required package: grid
data("Titanic")
Titanic
## , , Age = Child, Survived = No
##
## Sex
## Class Male Female
## 1st 0 0
## 2nd 0 0
## 3rd 35 17
## Crew 0 0
##
## , , Age = Adult, Survived = No
##
## Sex
## Class Male Female
## 1st 118 4
## 2nd 154 13
## 3rd 387 89
## Crew 670 3
##
## , , Age = Child, Survived = Yes
##
## Sex
## Class Male Female
## 1st 5 1
## 2nd 11 13
## 3rd 13 14
## Crew 0 0
##
## , , Age = Adult, Survived = Yes
##
## Sex
## Class Male Female
## 1st 57 140
## 2nd 14 80
## 3rd 75 76
## Crew 192 20
mosaic(Titanic)
HairEyeColor
## , , Sex = Male
##
## Eye
## Hair Brown Blue Hazel Green
## Black 32 11 10 3
## Brown 53 50 25 15
## Red 10 10 7 7
## Blond 3 30 5 8
##
## , , Sex = Female
##
## Eye
## Hair Brown Blue Hazel Green
## Black 36 9 5 2
## Brown 66 34 29 14
## Red 16 7 7 7
## Blond 4 64 5 8
mosaic(HairEyeColor)
cor(mtcars)
## mpg cyl disp hp drat wt
## mpg 1.0000000 -0.8521620 -0.8475514 -0.7761684 0.68117191 -0.8676594
## cyl -0.8521620 1.0000000 0.9020329 0.8324475 -0.69993811 0.7824958
## disp -0.8475514 0.9020329 1.0000000 0.7909486 -0.71021393 0.8879799
## hp -0.7761684 0.8324475 0.7909486 1.0000000 -0.44875912 0.6587479
## drat 0.6811719 -0.6999381 -0.7102139 -0.4487591 1.00000000 -0.7124406
## wt -0.8676594 0.7824958 0.8879799 0.6587479 -0.71244065 1.0000000
## qsec 0.4186840 -0.5912421 -0.4336979 -0.7082234 0.09120476 -0.1747159
## vs 0.6640389 -0.8108118 -0.7104159 -0.7230967 0.44027846 -0.5549157
## am 0.5998324 -0.5226070 -0.5912270 -0.2432043 0.71271113 -0.6924953
## gear 0.4802848 -0.4926866 -0.5555692 -0.1257043 0.69961013 -0.5832870
## carb -0.5509251 0.5269883 0.3949769 0.7498125 -0.09078980 0.4276059
## qsec vs am gear carb
## mpg 0.41868403 0.6640389 0.59983243 0.4802848 -0.55092507
## cyl -0.59124207 -0.8108118 -0.52260705 -0.4926866 0.52698829
## disp -0.43369788 -0.7104159 -0.59122704 -0.5555692 0.39497686
## hp -0.70822339 -0.7230967 -0.24320426 -0.1257043 0.74981247
## drat 0.09120476 0.4402785 0.71271113 0.6996101 -0.09078980
## wt -0.17471588 -0.5549157 -0.69249526 -0.5832870 0.42760594
## qsec 1.00000000 0.7445354 -0.22986086 -0.2126822 -0.65624923
## vs 0.74453544 1.0000000 0.16834512 0.2060233 -0.56960714
## am -0.22986086 0.1683451 1.00000000 0.7940588 0.05753435
## gear -0.21268223 0.2060233 0.79405876 1.0000000 0.27407284
## carb -0.65624923 -0.5696071 0.05753435 0.2740728 1.00000000
#install.packages("corrgram")
library(corrgram)
corrgram(mtcars)
heatmap(as.matrix(mtcars))
library(ggplot2)
qplot(mpg,data=mtcars,geom = "density")
qplot(mpg,data=mtcars,geom = "density",fill=as.factor(gear))
qplot(mpg,data=mtcars,geom = "density",fill=as.factor(gear),alpha=I(0.5))
qplot(mpg,data=mtcars,geom = "density")+facet_grid(~gear)
#library(Rcmdr)
#install.packages("ggmap")
library(ggmap)
geocode("Connaught Place")
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Connaught%20Place&sensor=false
## lon lat
## 1 77.21667 28.63145
#qmap("gateway of india",zoom=15)