Supprimer INSA/TP anadon/.Rhistory
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setwd("C:/Users/PC/Desktop/INSA/anadonn")
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library(knitr)
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## Global options
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options(max.print="75")
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opts_chunk$set(echo=FALSE,
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eval=FALSE,
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cache=FALSE,
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prompt=FALSE,
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tidy=TRUE,
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comment=NA,
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message=FALSE,
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warning=FALSE,
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class.source="badCode")
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opts_knit$set(width=75)
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donnees <- read.table("DataProjet3MIC-2425.txt",header=TRUE, sep=";")
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str(donnees)
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summary(donnees)
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ggplot(data = donnees)+
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geom_point(aes(x=ExpT1,y=T1_1H_R1))
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library(corrplot)
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library(ggplot2)
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library(gridExtra)
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library(forcats)
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library(reshape2)
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library(BioStatR)
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library(FactoMineR)
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library(factoextra)
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library(knitr)
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## Global options
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options(max.print="75")
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opts_chunk$set(echo=FALSE,
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eval=FALSE,
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cache=FALSE,
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prompt=FALSE,
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tidy=TRUE,
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comment=NA,
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message=FALSE,
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warning=FALSE,
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class.source="badCode")
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opts_knit$set(width=75)
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donnees <- read.table("DataProjet3MIC-2425.txt",header=TRUE, sep=";")
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head(donnees,200)
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str(donnees)
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summary(donnees)
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ggplot(data = donnees)+
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geom_point(aes(x=ExpT1,y=T1_1H_R1))
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apply(donnees[,1:36],2,var)
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apply(donnees[,1:36],2,mean)
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hist(donnees$T1_1H_R1)
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ggplot(donnees,aes(x=T1_1H_R1))+geom_boxplot()
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library(knitr)
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## Global options
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options(max.print="75")
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opts_chunk$set(echo=TRUE,
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cache=FALSE,
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prompt=FALSE,
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tidy=TRUE,
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comment=NA,
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message=FALSE,
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warning=FALSE,
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class.source="badCode")
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opts_knit$set(width=75)
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library(corrplot)
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library(ggplot2)
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library(gridExtra)
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library(forcats)
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library(reshape2)
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library(BioStatR)
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dim(wine)
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nrow(wine)
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ncol(wine)
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head(wine)
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wine <- read.table("wine.txt",header=TRUE)
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head(wine)
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dim(wine)
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nrow(wine)
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ncol(wine)
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is.data.frame(wine)
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names(wine)
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colnames(wine)
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str(wine)
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wine$Qualite<-as.factor(wine$Qualite)
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wine$Type<-factor(wine$Type,labels=c("blanc","rouge"))
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head(wine)
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summary(wine)
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gEx <- ggplot(data=wine)
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summary(gEx)
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names(gEx)
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gEx$layers
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ggplot(data=wine,aes(x=Densite,y=Alcool))+
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geom_point()
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ggplot(data=wine)+
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geom_point(aes(x=Densite,y=Alcool,color=Type))
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ggplot(data=wine)+
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geom_point(aes(x=Densite,y=Alcool),color="blue")
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# A COMPLETER
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summary(wine$Type)
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levels(wine$Type
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)
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table(wine$Type)
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g1<-ggplot(wine, aes(x=Type))+
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geom_bar()+
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ylab("")+ggtitle("Effectifs")
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g2<-ggplot(wine, aes(x = Type)) +
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geom_bar(aes(y = (..count..)/sum(..count..)))+ylab("")+ggtitle("Frequences")
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df <- data.frame(group = levels(wine$Type),
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value = as.vector(table(wine$Type))/nrow(wine))
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g3<-ggplot(df, aes(x="", y=value, fill=group))+
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geom_bar(width = 1, stat = "identity")+
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coord_polar("y", start=0)+
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theme(legend.position="bottom")
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grid.arrange(g3,g1,g2,ncol=3)
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wine$Qualite <- fct_relevel(wine$Qualite,"bad","medium","good")
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EffQual=as.vector(table(wine$Qualite))
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FreqQual= data.frame(Eff = EffQual, Freq = EffQual/length(wine$Qualite), FreqCumul=cumsum(EffQual)/length(wine$Qualite))
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rownames(FreqQual)=levels(wine$Qualite)
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knitr::kable(FreqQual, caption = 'Description de la variable Qualite',booktabs = TRUE,digits=3)
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df <- data.frame(Qualite = levels(wine$Qualite), value = table(wine$Qualite),
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valuecumul = 100 * cumsum(prop.table(table(wine$Qualite))))
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df$Qualite <- fct_relevel(df$Qualite, "bad", "medium", "good")
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df <- data.frame(df, freq = df$value.Freq/nrow(wine))
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g1 <- ggplot(wine) + geom_bar(aes(x = Qualite)) + ggtitle("Effectifs")+xlab("Qualite")
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g2 <- ggplot(wine) + geom_bar(aes(x = Qualite, y = ..prop.., group = 1)) + ggtitle("Frequences")+xlab("Qualite")
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g3 <- ggplot(df, aes(x = Qualite, y = valuecumul)) + geom_bar(stat = "identity") +
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ggtitle("Fréquences cumulées")
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g4 <- ggplot(df, aes(x = "", y = freq, fill = Qualite)) + geom_bar(width = 1, stat = "identity") +
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coord_polar("y", start = 0)
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grid.arrange(g1, g2, g3, g4, ncol = 2)
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mean(wine$Alcool)
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median(wine$Alcool)
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var(wine$Alcool)
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sd(wine$Alcool)
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range(wine$Alcool)
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summary(wine$Alcool)
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quantile(wine$Alcool,0.75,names=FALSE)-quantile(wine$Alcool,0.25,names = FALSE)
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quantile(wine$Alcool)
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H<-hist(wine$Alcool)
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ggplot(wine,aes(y=Alcool))+geom_boxplot()
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wineaux<-melt(wine[,-c(1,2)])
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ggplot(wineaux,aes(x=variable,y=value))+
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geom_boxplot()
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B<-boxplot(wine$Alcool)
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print('Correlation')
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cor(wine[,-c(1,2)])
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print('Covariance')
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cov(wine[,-c(1,2)])
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help(corrplot)
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corrplot(cor(wine[,-c(1,2)]),method = "ellipse")
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ggplot(data=wine)+
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geom_point(aes(x=Alcool,y=Densite))+
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geom_smooth(aes(x=Alcool,y=Densite),method="lm")
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donneesaux<-melt(donnees[,-(37:39)])
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ggplot(donneesaux,aes(x=variable,y=value))+
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geom_boxplot()
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donneesaux<-melt(donnees[,(1:18)])
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ggplot(donneesaux,aes(x=variable,y=value))+
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geom_boxplot()
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don_R1<-melt(donnees[,(1:18)])
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gR1=ggplot(don_R1,aes(x=variable,y=value))+
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geom_boxplot()
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don_R2<-melt(donnees[,(19:36)])
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gR2=ggplot(don_R2,aes(x=variable,y=value))+
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geom_boxplot()
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grid.arrange(gR1, gR2, ncol = 2)
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don_R1<-melt(donnees[,(1:18)])
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gR1=ggplot(don_R1,aes(x=variable,y=value))+
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geom_boxplot()
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don_R2<-melt(donnees[,(19:36)])
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gR2=ggplot(don_R2,aes(x=variable,y=value))+
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geom_boxplot()
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grid.arrange(gR1, gR2, nrow = 2)
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