#pdf("gc-out.pdf", width = 10, height = 8)

CARCR<-c(0.00,5.32,44.71,29.95,11.63,5.97,2.22,0.19)
COLST<-c(0.02,12.69,43.68,24.48,11.16,5.84,2.00,0.13)
MERNU<-c(0.00,5.30,43.76,29.95,12.45,5.93,2.36,0.25)
GAVST<-c(0.00,4.24,43.26,31.92,13.21,5.58,1.68,0.11)
BALRE<-c(0.00,5.42,45.62,29.51,10.92,5.77,2.53,0.23,0.00)
APAVI<-c(0.00,5.32,44.00,30.29,12.25,6.55,1.56,0.03)
PHACA<-c(0.00,4.25,44.75,31.59,11.53,5.57,2.20,0.13,0.00)
PHALE<-c(0.00,5.23,42.84,30.84,12.14,6.01,2.59,0.35,0.00)
PHORU<-c(0.00,2.96,40.48,33.15,13.13,6.81,3.14,0.32)
PODCR<-c(0.00,5.28,43.08,30.55,12.15,6.28,2.47,0.18)
FULGL<-c(0.00,4.95,45.12,30.06,11.15,5.26,2.91,0.54,0.00)
EURHE<-c(0.00,5.12,36.47,32.83,14.47,7.00,3.63,0.48,0.00)
CHLUN<-c(0.00,7.41,45.67,28.12,10.86,5.48,2.25,0.21)
PELCR<-c(0.00,4.08,45.66,31.48,11.26,4.97,2.26,0.29,0.00)
PTEGU<-c(0.00,4.65,45.74,29.69,11.22,5.92,2.54,0.25)
ACACH<-c(0.00,5.36,44.52,29.52,12.20,6.11,2.15,0.13)
BUCRH<-c(0.00,2.15,33.70,30.85,14.85,12.10,5.70,0.65,0.00)
NESNO<-c(0.00,5.97,46.83,29.00,10.48,5.21,2.36,0.16)
HALAL<-c(0.00,4.42,47.24,31.02,10.98,4.76,1.54,0.04)
ANAPL<-c(0.05,14.57,40.28,24.75,11.99,4.74,2.28,1.08,0.27)
APTFO<-c(0.00,5.37,44.47,30.20,11.11,4.56,2.30,1.28,0.70)
CAPCA<-c(0.00,8.43,44.68,28.04,12.47,5.13,1.17,0.07)
MESUN<-c(0.00,5.94,43.33,29.75,12.62,6.04,2.06,0.27,0.00)
CALAN<-c(0.00,7.45,46.11,30.37,9.70,3.76,1.80,0.71,0.09)
CHAPE<-c(0.00,7.68,45.38,27.29,10.95,5.02,2.59,1.01,0.06)
CHAVO<-c(0.00,4.85,43.49,30.66,11.80,5.06,2.66,1.29,0.19)
COLLI<-c(0.02,6.38,44.95,29.03,10.97,4.86,2.31,1.15,0.33)
CORBR<-c(0.00,5.66,43.03,29.68,11.65,5.64,2.82,1.29,0.23)
CATAU<-c(0.00,3.75,45.00,31.50,12.63,4.92,1.82,0.36,0.02)
LEPDI<-c(0.00,4.16,42.47,30.71,11.39,5.97,4.35,0.95,0.01)
CUCCA<-c(0.00,7.72,45.85,26.62,11.18,5.16,2.37,1.01,0.08)
EGRGA<-c(0.00,4.84,40.00,30.89,12.63,6.16,3.45,1.67,0.37)
GALGA<-c(0.01,9.78,40.05,29.23,13.24,5.17,1.98,0.51,0.03)
GEOFO<-c(0.00,7.00,41.12,30.50,12.24,5.48,2.55,1.00,0.11)
MANVI<-c(0.00,7.75,50.29,25.79,9.08,4.21,2.00,0.80,0.07)
MELUN<-c(0.00,8.36,46.06,28.04,11.10,4.26,1.69,0.48,0.02)
NIPNI<-c(0.00,5.65,42.28,31.06,12.17,4.58,2.24,1.25,0.77)
TYTAL<-c(0.00,9.51,46.83,26.61,10.77,5.21,1.05,0.02)
OPHHO<-c(0.00,3.68,41.01,31.56,13.12,5.95,3.19,1.33,0.15)
PICPU<-c(0.00,2.67,32.85,33.66,15.79,7.78,4.52,2.32,0.40)
PYGAD<-c(0.00,5.30,44.07,29.92,10.86,5.51,3.26,0.96,0.13)
STRCA<-c(0.00,4.38,47.57,30.25,10.52,4.32,2.01,0.84,0.11)
TAEGU<-c(0.00,0.16,30.65,44.42,16.45,5.99,1.96,0.37,0.00)
TAUER<-c(0.00,5.50,42.40,29.80,12.01,6.96,2.94,0.38,0.00)
TINMA<-c(0.00,6.18,40.70,33.37,11.82,4.41,2.19,1.09,0.24)

data<-rbind(CARCR,COLST,MERNU,GAVST,BALRE,APAVI,PHACA,PHALE,
PHORU,PODCR,FULGL,EURHE,CHLUN,PELCR,PTEGU,ACACH,
BUCRH,NESNO,HALAL,ANAPL,APTFO,CAPCA,MESUN,CALAN,
CHAPE,CHAVO,COLLI,CORBR,CATAU,LEPDI,CUCCA,EGRGA,
GALGA,GEOFO,MANVI,MELUN,NIPNI,TYTAL,OPHHO,PICPU,
PYGAD,STRCA,TAEGU,TAUER,TINMA
)

heatmap(data,
labCol = c("<30","30-35","35-40","40-45","45-50","50-55","55-60","60-65",">65"),
#col = topo.colors(9),
#col = cm.colors(256), scale="column",
#RowSideColors = 43, #ColSideColors = 9,
margins=c(5,10)

)
#dev.off()

 

a<-10 + rnorm(140,0,1)
b<-15 + rnorm(90,0,1)
c<-14 + rnorm(120,0,1)
d<-12 + rnorm(130,0,1)
e<-13 + rnorm(140,0,1)
f<-14 + rnorm(90,0,1)
g<-12 + rnorm(120,0,1)
h<-15 + rnorm(130,0,1)
i<-11 + rnorm(140,0,1)
j<-13 + rnorm(90,0,1)
k<-14 + rnorm(120,0,1)
l<-12 + rnorm(130,0,1)

boxplot(a,b,c,d,e,f,g,h,i,j,k,l,
outline = FALSE,
plot = TRUE,
range = 1.5,
#pars = list(boxwex = 0.35, staplewex = 0.5, outwex = 0.5),

boxwex=.24,at=1:12 - .2,
col="orange",axes=F
#names=c("a","b","c","d"),
#col = "blue"
#boxwex = 0.25, at = 1:12 - 0.2
#varwidth = TURE
)
box()
axis(2)
axis(1,at=c(1:12 - .2),c("a","b","c","d","e","f","g","h","i","j","k","l"),las = 2)