install.packages(c("corrplot", "ggplot2", "forcats", "reshape2", "gridExtra", "BioStatR", "FactoMineR", "factoextra", "mclust", "cluster", "ppclust", "circlize", "ggalluvial"))
install.packages(c("lme4", "quantreg"))
install.packages("FactoMineR")
install.packages("FactoMineR")
install.packages("FactoMineR")
install.packages("nloptr")
install.packages("nloptr")
install.packages("FactoMineR")
install.packages(c("corrplot", "ggplot2", "forcats", "reshape2", "gridExtra", "BioStatR", "FactoMineR", "factoextra", "mclust", "cluster", "ppclust", "circlize", "ggalluvial"))
clear
knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
library(gridExtra)
library(reshape2)
library(corrplot)
ggplot(melt(T[1:18]),aes(x=variable,y=value))+
geom_boxplot()+ theme(axis.text.x = element_text(angle=90, vjust = 0.5, hjust = 1))
knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
library(gridExtra)
library(reshape2)
library(corrplot)
T = read.table("DataProjet3MIC-2425.txt",header=TRUE,sep=";")
T$ExpT1 = as.factor(T$ExpT1)
T$ExpT2 = as.factor(T$ExpT2)
T$ExpT3 = as.factor(T$ExpT3)
head(T)
summary(T)
str(T)
levels(T$ExpT1)
g1<-ggplot(T, aes(x=T$ExpT1))+
geom_bar()+
ylab("Effectifs")+ggtitle("Effectifs")
g2<-ggplot(T, aes(x = T$ExpT1)) +
geom_bar(aes(y = (..count..)/sum(..count..)))+ylab("")+ggtitle("Frequences")
df <- data.frame(group = levels(T$ExpT1),
value = as.vector(table(T$ExpT1))/nrow(T))
g3<-ggplot(df, aes(x="", y=value, fill=group))+
geom_bar(width = 1, stat = "identity")+
coord_polar("y", start=0)+
theme(legend.position="bottom")
grid.arrange(g3,g1,g2,ncol=3)
g1<-ggplot(T, aes(x=T$ExpT2))+
geom_bar()+
ylab("Effectifs")+ggtitle("Effectifs")
g2<-ggplot(T, aes(x = T$ExpT2)) +
geom_bar(aes(y = (..count..)/sum(..count..)))+ylab("")+ggtitle("Frequences")
df <- data.frame(group = levels(T$ExpT2),
value = as.vector(table(T$ExpT2))/nrow(T))
g3<-ggplot(df, aes(x="", y=value, fill=group))+
geom_bar(width = 1, stat = "identity")+
coord_polar("y", start=0)+
theme(legend.position="bottom")
grid.arrange(g3,g1,g2,ncol=3)
g1<-ggplot(T, aes(x=T$ExpT3))+
geom_bar()+
ylab("Effectifs")+ggtitle("Effectifs")
g2<-ggplot(T, aes(x = T$ExpT3)) +
geom_bar(aes(y = (..count..)/sum(..count..)))+ylab("")+ggtitle("Frequences")
df <- data.frame(group = levels(T$ExpT3),
value = as.vector(table(T$ExpT3))/nrow(T))
g3<-ggplot(df, aes(x="", y=value, fill=group))+
geom_bar(width = 1, stat = "identity")+
coord_polar("y", start=0)+
theme(legend.position="bottom")
grid.arrange(g3,g1,g2,ncol=3)
#apply(T[-c(37:39)],2,function(col){
# which(T == col)
#hist(col, main = paste("Histogram of", colnames(T)[which(T == col)[2]]),
#    xlab = "Values", col = "lightblue", border = "black")
#})
T_long = melt(T[-c(37:39)])
ggplot(T_long, aes(x = value)) +
geom_histogram(binwidth = 1, fill = "blue", color = "black", alpha = 0.7) +
facet_wrap(~variable,scales = "free",ncol=6) +
labs(title = "Histograms for Each Column", x = "Values", y = "Frequency")
ggplot(melt(T[1:18]),aes(x=variable,y=value))+
geom_boxplot()+ theme(axis.text.x = element_text(angle=90, vjust = 0.5, hjust = 1))
ggplot(melt(T[19:36]),aes(x=variable,y=value))+
geom_boxplot() + theme(axis.text.x = element_text(angle=90, vjust = 0.5, hjust = 1))
cr = cor(T[-c(37:39)])
corrplot(cr,method="ellipse", type="lower", bg = "lightgrey")
cr = cor(T[-c(37:39)])
corrplot(cr,method="ellipse", type="lower", bg = "lightgrey")
library(knitr)
## Global options
options(max.print="75")
opts_chunk$set(echo=TRUE,
cache=FALSE,
prompt=FALSE,
tidy=TRUE,
comment=NA,
message=FALSE,
warning=FALSE,
class.source="badCode")
opts_knit$set(width=75)
library(corrplot)
library(ggplot2)
library(gridExtra)
library(forcats)
library(reshape2)
library(BioStatR)
wine <- read.table("wine.txt",header=TRUE)
head(wine)
# A COMPLETER
dim(wine)
nrow(wine)
ncol(wine)
# A COMPLETER
is.data.frame(wine)
attributes(wine)
# A COMPLETER
str(wine)
wine$Qualite<-as.factor(wine$Qualite)
wine$Type<-factor(wine$Type,labels=c("blanc","rouge"))
head(wine)
summary(wine)
gEx <- ggplot(data=wine)
summary(gEx)
names(gEx)
gEx$layers
ggplot(data=wine,aes(x=Densite,y=Alcool))+
geom_point()
ggplot(data=wine)+
geom_point(aes(x=Densite,y=Alcool,color=Type))
ggplot(data=wine)+
geom_point(aes(x=Densite,y=Alcool),color="blue")
ggplot(data=wine)+
geom_violin(aes(x=Qualite,y=Alcool))+
geom_point(aes(x=Qualite,y=Alcool), col = "blue", alpha = 0.2,position="jitter")
ggplot(data=wine)+
geom_point(aes(x=Alcool,y=Densite,size=AcidVol,color=Type))+
scale_size("Acide vol.", range = c(0,1.5),breaks=seq(0,1.5,0.2)) +
scale_x_continuous("Alcool",limits=c(8,16)) +
scale_y_continuous("Densité",limits=c(0.985,1.01))
# A COMPLETER
t <- table(wine$Type)
summary(wine$Type)
levels(wine$Type)
# A COMPLETER
mean(wine$Alcool)
median(wine$Alcool)
var(wine$Alcool)
sd(wine$Alcool)
e <- range(wine$Alcool)
e
e[2]-e[1]
# A COMPLETER²²
summary(wine$Alcool)
q1 = quantile(wine$Alcool,0.25)
q2 = quantile(wine$Alcool,0.75)
IQR(wine$Alcool)
q2-q1
Lp = q2+1.5*(q2-q1)
Lm = q1-1.5*(q2-q1)
print("valeurs adjacentes :")
Lp
Lm
# A COMPLETER
H <- hist(wine$Alcool)
H
ggplot(wine,aes(y=Alcool))+geom_boxplot()
# A COMPLETER
B<-boxplot(wine$Alcool)
quantile(wine$Alcool)
B
# A COMPLETER
cr = cor(wine[c("Alcool","AcidVol","AcidCitr","SO2lbr","SO2tot","Densite")])
corrplot(cr,method="number", type="lower", bg = "lightgrey",)
# A COMPLETER
ggplot(wine,aes(x=wine$Alcool,y=wine$Densite))+geom_point()+geom_smooth(method="lm")
# A COMPLETER
ggplot(wine,aes(x=wine$Type,y=wine$Alcool))+
geom_boxplot()
ggplot(wine,aes(x=wine$Qualite,y=wine$Alcool))+
geom_boxplot()
# A COMPLETER
ggplot(wine,aes(x=wine$Type,y=wine$Densite))+
geom_boxplot()
ggplot(wine,aes(x=wine$Qualite,y=wine$Densite))+
geom_boxplot()
ggplot(wine,aes(x=wine$Type,y=wine$AcidVol))+
geom_boxplot()
ggplot(wine,aes(x=wine$Qualite,y=wine$AcidVol))+
geom_boxplot()
ggplot(wine,aes(x=wine$Type,y=wine$SO2lbr))+
geom_boxplot()
ggplot(wine,aes(x=wine$Qualite,y=wine$SO2lbr))+
geom_boxplot()
ggplot(wine,aes(x=wine$Type,y=wine$AcidCitr))+
geom_boxplot()
ggplot(wine,aes(x=wine$Qualite,y=wine$AcidCitr))+
geom_boxplot()
ggplot(wine,aes(x=wine$Type,y=wine$SO2tot))+
geom_boxplot()
ggplot(wine,aes(x=wine$Qualite,y=wine$SO2tot))+
geom_boxplot()
# A COMPLETER
eta2(wine$AcidVol,wine$Type)
eta2(wine$AcidCitr,wine$Type)
eta2(wine$SO2lbr,wine$Type)
eta2(wine$SO2tot,wine$Type)
eta2(wine$Densite,wine$Type)
eta2(wine$Alcool,wine$Type)
# A COMPLETER
t= table(wine$Type,wine$Qualite)
addmargins(t)
# A COMPLETER
mosaicplot(prop.table(t))
g1<-ggplot(wine, aes(x=Type))+
geom_bar()+
ylab("Effectifs")+ggtitle("Effectifs")
g2<-ggplot(wine, aes(x = Type)) +
geom_bar(aes(y = (..count..)/sum(..count..)))+ylab("")+ggtitle("Frequences")
df <- data.frame(group = levels(wine$Type),
value = as.vector(table(wine$Type))/nrow(wine))
g3<-ggplot(df, aes(x="", y=value, fill=group))+
geom_bar(width = 1, stat = "identity")+
coord_polar("y", start=0)+
theme(legend.position="bottom")
grid.arrange(g3,g1,g2,ncol=3)
# A COMPLETER
t <- table(wine$Type)
summary(wine$Type)
levels(wine$Type)
ggplot(wine,aes(x=wine$Type,y=wine$Alcool))+
geom_boxplot()
T$T2_6H_R2
T$T3_6H_R1
# traitement 1 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(wine,aes(x=T$T1_6H_R1,y=T$ExpT1))+
geom_boxplot()
T$T2_6H_R2
T$T3_6H_R1
# traitement 1 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(wine,aes(y=T$T1_6H_R1,x=T$ExpT1))+
geom_boxplot()
T$T2_6H_R2
T$T3_6H_R1
# traitement 1 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(wine,aes(y=T$T1_6H_R1,x=levels(T$ExpT1)))+
geom_boxplot()
T$T2_6H_R2
T$T3_6H_R1
# traitement 1 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(y=T$T1_6H_R1,x=T$ExpT1))+
geom_boxplot()
ggplot(wine,aes(x=T$T1_6H_R2,y=T$ExpT1))+
geom_boxplot()
T$T2_6H_R2
T$T3_6H_R1
# traitement 1 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(y=T$T1_6H_R1,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(x=T$T1_6H_R2,y=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(x=T$T1_6H_R1,y=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(x=T$T1_6H_R2,y=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(x=T$T1_6H_R1,y=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(x=T$T1_6H_R2,y=T$ExpT3))+
geom_boxplot()
# traitement 2 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(x=T$T2_6H_R1,y=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(x=T$T2_6H_R2,y=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(x=T$T2_6H_R1,y=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(x=T$T2_6H_R2,y=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(x=T$T2_6H_R1,y=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(x=T$T2_6H_R2,y=T$ExpT3))+
geom_boxplot()
# traitement 2 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(x=T$T3_6H_R1,y=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(x=T$T3_6H_R2,y=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(x=T$T3_6H_R1,y=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(x=T$T3_6H_R2,y=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(x=T$T3_6H_R1,y=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(x=T$T3_6H_R2,y=T$ExpT2))+
geom_boxplot()
T$T2_6H_R2
T$T3_6H_R1
# traitement 1 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(y=T$T1_6H_R1,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(y=T$T1_6H_R2,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(y=T$T1_6H_R1,x=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(y=T$T1_6H_R2,x=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(y=T$T1_6H_R1,x=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(y=T$T1_6H_R2,x=T$ExpT3))+
geom_boxplot()
# traitement 2 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(y=T$T2_6H_R1,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(y=T$T2_6H_R2,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(y=T$T2_6H_R1,x=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(y=T$T2_6H_R2,x=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(y=T$T2_6H_R1,x=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(y=T$T2_6H_R2,x=T$ExpT3))+
geom_boxplot()
# traitement 2 corrélation avec l'expression des genes du T1 T2 et T3
ggplot(T,aes(y=T$T3_6H_R1,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(y=T$T3_6H_R2,x=T$ExpT1))+
geom_boxplot()
ggplot(T,aes(y=T$T3_6H_R1,x=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(y=T$T3_6H_R2,x=T$ExpT2))+
geom_boxplot()
ggplot(T,aes(y=T$T3_6H_R1,x=T$ExpT3))+
geom_boxplot()
ggplot(T,aes(y=T$T3_6H_R2,x=T$ExpT3))+
geom_boxplot()
