R Notebook3
Description of attributes:
1 - fixed acidity: most acids involved with wine or fixed or nonvolatile (do not evaporate readily)
2 - volatile acidity: the amount of acetic acid in wine, which at too high of levels can lead to an unpleasant, vinegar taste
3 - citric acid: found in small quantities, citric acid can add ‘freshness’ and flavor to wines
4 - residual sugar: the amount of sugar remaining after fermentation stops, it’s rare to find wines with less than 1 gram/liter and wines with greater than 45 grams/liter are considered sweet
5 - chlorides: the amount of salt in the wine
6 - free sulfur dioxide: the free form of SO2 exists in equilibrium between molecular SO2 (as a dissolved gas) and bisulfite ion; it prevents microbial growth and the oxidation of wine
7 - total sulfur dioxide: amount of free and bound forms of S02; in low concentrations, SO2 is mostly undetectable in wine, but at free SO2 concentrations over 50 ppm, SO2 becomes evident in the nose and taste of wine
8 - density: the density of water is close to that of water depending on the percent alcohol and sugar content
9 - pH: describes how acidic or basic a wine is on a scale from 0 (very acidic) to 14 (very basic); most wines are between 3-4 on the pH scale
10 - sulphates: a wine additive which can contribute to sulfur dioxide gas (S02) levels, wich acts as an antimicrobial and antioxidant
11 - alcohol: the percent alcohol content of the wine
12 - quality (score between 0 and 10)
##Loading the dataset
getwd()## [1] "C:/Users/Hariharan/Desktop/books/R"setwd("C:/Users/Hariharan/Documents")
Wine.Dataset<-read.csv('winequality-red.csv')##dimensions of wine dataset
dim(Wine.Dataset)## [1] 1599 12##summary
summary(Wine.Dataset)## fixed.acidity volatile.acidity citric.acid residual.sugar
## Min. : 4.60 Min. :0.1200 Min. :0.000 Min. : 0.900
## 1st Qu.: 7.10 1st Qu.:0.3900 1st Qu.:0.090 1st Qu.: 1.900
## Median : 7.90 Median :0.5200 Median :0.260 Median : 2.200
## Mean : 8.32 Mean :0.5278 Mean :0.271 Mean : 2.539
## 3rd Qu.: 9.20 3rd Qu.:0.6400 3rd Qu.:0.420 3rd Qu.: 2.600
## Max. :15.90 Max. :1.5800 Max. :1.000 Max. :15.500
## chlorides free.sulfur.dioxide total.sulfur.dioxide density
## Min. :0.01200 Min. : 1.00 Min. : 6.00 Min. :0.9901
## 1st Qu.:0.07000 1st Qu.: 7.00 1st Qu.: 22.00 1st Qu.:0.9956
## Median :0.07900 Median :14.00 Median : 38.00 Median :0.9968
## Mean :0.08747 Mean :15.87 Mean : 46.47 Mean :0.9967
## 3rd Qu.:0.09000 3rd Qu.:21.00 3rd Qu.: 62.00 3rd Qu.:0.9978
## Max. :0.61100 Max. :72.00 Max. :289.00 Max. :1.0037
## pH sulphates alcohol quality
## Min. :2.740 Min. :0.3300 Min. : 8.40 Min. :3.000
## 1st Qu.:3.210 1st Qu.:0.5500 1st Qu.: 9.50 1st Qu.:5.000
## Median :3.310 Median :0.6200 Median :10.20 Median :6.000
## Mean :3.311 Mean :0.6581 Mean :10.42 Mean :5.636
## 3rd Qu.:3.400 3rd Qu.:0.7300 3rd Qu.:11.10 3rd Qu.:6.000
## Max. :4.010 Max. :2.0000 Max. :14.90 Max. :8.000##datatypes
class(Wine.Dataset$fixed.acidity)## [1] "numeric"class(Wine.Dataset$volatile.acidity)## [1] "numeric"class(Wine.Dataset$citric.acid)## [1] "numeric"class(Wine.Dataset$residual.sugar)## [1] "numeric"class(Wine.Dataset$chlorides)## [1] "numeric"class(Wine.Dataset$free.sulfur.dioxide)## [1] "numeric"class(Wine.Dataset$total.sulfur.dioxide)## [1] "numeric"class(Wine.Dataset$density)## [1] "numeric"class(Wine.Dataset$pH)## [1] "numeric"class(Wine.Dataset$sulphates)## [1] "numeric"class(Wine.Dataset$alcohol)## [1] "numeric"class(Wine.Dataset$quality)## [1] "integer"##scatterplot
plot(Wine.Dataset$fixed.acidity,Wine.Dataset$volatile.acidity)
##bar plot
barplot(table(Wine.Dataset$quality),xlab = "Quality",ylab = "count" )
# bar chart using ggplot
library(ggplot2)
ggplot(Wine.Dataset, aes(quality)) + geom_bar(fill = "red")+ scale_x_continuous("Quality", breaks = seq(3,8)) + scale_y_continuous("count", breaks = seq(0,700,100)) +coord_flip()+ labs(title = "Bar Chart") + theme_gray()+theme_bw()
##scatterplot using ggplot
ggplot(Wine.Dataset, aes(chlorides,sulphates)) + geom_point() + scale_x_continuous("Chlorides", breaks = seq(0,0.70,0.05))+ scale_y_continuous("Sulphates", breaks = seq(0,3,0.5))+ theme_bw()+labs(title = "Scatter plot using ggplot")
ggplot(Wine.Dataset, aes(chlorides,sulphates)) + geom_point() + scale_x_continuous("Chlorides", breaks = seq(0,0.70,0.05))+ scale_y_continuous("Sulphates", breaks = seq(0,3,0.5))+ theme_bw()+labs(title = "Scatter plot using ggplot")+geom_smooth()## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
ggplot(Wine.Dataset, aes(density, pH)) + geom_point(aes(color = quality)) +
scale_x_continuous("Density")+
scale_y_continuous("pH", breaks = seq(2.5,4.3,0.1))+
theme_bw() + labs(title="Scatterplot")
##scatter plot with facet wrap
ggplot(Wine.Dataset, aes(density, pH)) + geom_point(aes(color = quality)) +
scale_x_continuous("Density")+
scale_y_continuous("pH", breaks = seq(2.5,4.3,0.1))+
theme_bw() + labs(title="Scatterplot")+ facet_wrap( ~ quality)
##Histogram
hist(Wine.Dataset$citric.acid)
##densityplot
plot(density(Wine.Dataset$citric.acid))
##histogram and density plot
plot(density(Wine.Dataset$citric.acid),col = "red")
hist(Wine.Dataset$citric.acid,freq = F,add=T)
##Histogram by ggplot
ggplot(Wine.Dataset, aes(fixed.acidity)) + geom_histogram(colour="darkblue",fill="lightblue",binwidth = 1,linetype="dashed")+
scale_x_continuous("Fixed Acidity", breaks = seq(0,16,by = 1))+
scale_y_continuous("Count", breaks = seq(0,500,by = 100))+
labs(title = "Histogram")
##density plot with ggplot
ggplot(Wine.Dataset,aes(fixed.acidity))+geom_density()
##histogram and density plot with ggplot
ggplot(Wine.Dataset, aes(fixed.acidity)) + geom_histogram(aes(y =stat(density)),colour="darkblue",fill="lightblue",binwidth = 1,linetype="dashed")+geom_density(col ="red")
# violin plot
ggplot(Wine.Dataset,aes(fixed.acidity,volatile.acidity))+geom_violin(trim = FALSE)
library(corrgram)
corrgram(Wine.Dataset)
##2.corrlogram
corrgram(Wine.Dataset,lower.panel = panel.cor,upper.panel = panel.pie) 
##3.corrlogram
corrgram(Wine.Dataset,lower.panel = panel.ellipse,upper.panel = panel.conf) 
##lineplot
plot(Wine.Dataset$pH,type = "o",col ="red",xlab = "",ylab = "",ylim = c(2,5),main = "line plot of PH")
legend(0,5,legend = "PH")
##comparison of line plot
plot(Wine.Dataset$alcohol,type = "o",col ="red",xlab = "",ylab = "",ylim = c(0,20),main = "comparison among alcohol,fixed acidity and residual sugar")
lines(Wine.Dataset$fixed.acidity,type = "o",col ="blue")
lines(Wine.Dataset$residual.sugar,col ="black")
legend(1,20,legend = c("alcohol","fixed acidity","residual sugar"),col = c("red","blue","black"),lty = 1:1,cex = 0.7)
##boxplot
boxplot(Wine.Dataset$alcohol,xlab ="Alcohol",ylab ="Alcohol concentration")
##boxplot by ggplot
ggplot(aes(x=factor(quality), y=alcohol), data=Wine.Dataset)+ geom_boxplot(fill='grey', color='blue', outlier.color = 'red')+ scale_y_continuous()+ scale_x_discrete()+ ggtitle('Wine Quality vs Alcohol Concentration')+ xlab('Wine Quality')
Adding rating as redwine quality to group the redwine quality in the following: Poor = less than 5 ,Good = between 5 and 8, Excellent = greater than 8
##some graphs are used when there is a categorical data. so we add an column full of categorical data
Wine.Dataset$rating[5>=Wine.Dataset$quality] = 'Poor'
Wine.Dataset$rating[5<Wine.Dataset$quality | Wine.Dataset$quality ==7] ='Good'
Wine.Dataset$rating[7<Wine.Dataset$quality ] ='Excellent'
print(Wine.Dataset$rating)## [1] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [7] "Poor" "Good" "Good" "Poor" "Poor" "Poor"
## [13] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [19] "Poor" "Good" "Good" "Poor" "Poor" "Poor"
## [25] "Good" "Poor" "Poor" "Poor" "Poor" "Good"
## [31] "Poor" "Good" "Poor" "Good" "Poor" "Good"
## [37] "Good" "Good" "Poor" "Poor" "Poor" "Poor"
## [43] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [49] "Poor" "Poor" "Poor" "Good" "Good" "Poor"
## [55] "Good" "Poor" "Poor" "Poor" "Poor" "Good"
## [61] "Poor" "Poor" "Good" "Poor" "Poor" "Poor"
## [67] "Poor" "Poor" "Poor" "Good" "Good" "Poor"
## [73] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [79] "Poor" "Poor" "Poor" "Poor" "Poor" "Poor"
## [85] "Good" "Poor" "Good" "Poor" "Poor" "Poor"
## [91] "Poor" "Good" "Poor" "Poor" "Poor" "Good"
## [97] "Poor" "Poor" "Poor" "Good" "Good" "Good"
## [103] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [109] "Good" "Poor" "Poor" "Poor" "Poor" "Good"
## [115] "Poor" "Good" "Good" "Good" "Good" "Good"
## [121] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [127] "Poor" "Poor" "Good" "Poor" "Poor" "Poor"
## [133] "Poor" "Good" "Good" "Poor" "Poor" "Poor"
## [139] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [145] "Good" "Poor" "Poor" "Poor" "Good" "Good"
## [151] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [157] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [163] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [169] "Good" "Poor" "Poor" "Good" "Good" "Good"
## [175] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [181] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [187] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [193] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [199] "Good" "Poor" "Good" "Poor" "Poor" "Poor"
## [205] "Good" "Good" "Good" "Poor" "Poor" "Good"
## [211] "Good" "Good" "Good" "Poor" "Good" "Poor"
## [217] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [223] "Poor" "Good" "Poor" "Good" "Good" "Poor"
## [229] "Good" "Poor" "Good" "Good" "Good" "Poor"
## [235] "Good" "Good" "Good" "Good" "Good" "Good"
## [241] "Poor" "Good" "Good" "Good" "Good" "Good"
## [247] "Poor" "Poor" "Good" "Good" "Good" "Good"
## [253] "Poor" "Poor" "Good" "Poor" "Poor" "Poor"
## [259] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [265] "Poor" "Good" "Poor" "Excellent" "Good" "Good"
## [271] "Good" "Good" "Poor" "Poor" "Poor" "Good"
## [277] "Good" "Good" "Excellent" "Good" "Good" "Good"
## [283] "Poor" "Good" "Poor" "Poor" "Good" "Good"
## [289] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [295] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [301] "Good" "Good" "Poor" "Poor" "Poor" "Good"
## [307] "Poor" "Good" "Good" "Good" "Good" "Good"
## [313] "Good" "Poor" "Poor" "Good" "Poor" "Good"
## [319] "Good" "Good" "Good" "Poor" "Poor" "Good"
## [325] "Good" "Good" "Good" "Poor" "Good" "Poor"
## [331] "Good" "Good" "Good" "Poor" "Good" "Good"
## [337] "Good" "Poor" "Good" "Good" "Good" "Good"
## [343] "Good" "Good" "Good" "Poor" "Good" "Good"
## [349] "Good" "Good" "Good" "Good" "Poor" "Poor"
## [355] "Good" "Good" "Poor" "Good" "Good" "Good"
## [361] "Poor" "Good" "Poor" "Poor" "Good" "Good"
## [367] "Good" "Poor" "Poor" "Good" "Poor" "Good"
## [373] "Good" "Poor" "Good" "Good" "Good" "Good"
## [379] "Good" "Good" "Good" "Good" "Good" "Good"
## [385] "Poor" "Good" "Good" "Good" "Good" "Good"
## [391] "Excellent" "Good" "Poor" "Poor" "Poor" "Good"
## [397] "Poor" "Good" "Good" "Poor" "Poor" "Good"
## [403] "Good" "Good" "Poor" "Good" "Good" "Good"
## [409] "Good" "Poor" "Good" "Poor" "Poor" "Good"
## [415] "Poor" "Poor" "Good" "Poor" "Good" "Poor"
## [421] "Good" "Good" "Poor" "Good" "Poor" "Good"
## [427] "Good" "Good" "Poor" "Good" "Good" "Poor"
## [433] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [439] "Good" "Poor" "Excellent" "Good" "Good" "Good"
## [445] "Good" "Good" "Poor" "Poor" "Good" "Good"
## [451] "Good" "Good" "Good" "Good" "Poor" "Excellent"
## [457] "Poor" "Poor" "Good" "Poor" "Good" "Poor"
## [463] "Poor" "Poor" "Good" "Poor" "Good" "Good"
## [469] "Good" "Poor" "Poor" "Good" "Good" "Poor"
## [475] "Good" "Poor" "Poor" "Good" "Poor" "Good"
## [481] "Poor" "Excellent" "Poor" "Poor" "Good" "Poor"
## [487] "Poor" "Good" "Good" "Good" "Good" "Good"
## [493] "Good" "Good" "Good" "Excellent" "Good" "Poor"
## [499] "Excellent" "Good" "Good" "Good" "Good" "Good"
## [505] "Good" "Good" "Good" "Good" "Good" "Good"
## [511] "Poor" "Good" "Good" "Good" "Good" "Poor"
## [517] "Good" "Poor" "Good" "Poor" "Good" "Poor"
## [523] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [529] "Good" "Poor" "Good" "Poor" "Poor" "Good"
## [535] "Good" "Good" "Poor" "Good" "Good" "Poor"
## [541] "Poor" "Good" "Poor" "Good" "Good" "Poor"
## [547] "Good" "Good" "Good" "Good" "Good" "Good"
## [553] "Good" "Poor" "Poor" "Poor" "Good" "Poor"
## [559] "Good" "Good" "Poor" "Poor" "Poor" "Good"
## [565] "Good" "Poor" "Good" "Good" "Good" "Good"
## [571] "Good" "Good" "Poor" "Poor" "Good" "Good"
## [577] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [583] "Poor" "Good" "Good" "Good" "Good" "Poor"
## [589] "Excellent" "Good" "Poor" "Good" "Poor" "Poor"
## [595] "Poor" "Poor" "Good" "Good" "Good" "Good"
## [601] "Poor" "Good" "Poor" "Good" "Good" "Good"
## [607] "Good" "Good" "Good" "Good" "Poor" "Poor"
## [613] "Good" "Poor" "Good" "Poor" "Poor" "Good"
## [619] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [625] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [631] "Good" "Poor" "Good" "Poor" "Poor" "Poor"
## [637] "Poor" "Poor" "Good" "Good" "Poor" "Poor"
## [643] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [649] "Good" "Good" "Poor" "Poor" "Poor" "Good"
## [655] "Poor" "Poor" "Poor" "Good" "Good" "Poor"
## [661] "Good" "Poor" "Good" "Good" "Poor" "Poor"
## [667] "Good" "Good" "Poor" "Good" "Poor" "Poor"
## [673] "Poor" "Poor" "Good" "Poor" "Good" "Poor"
## [679] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [685] "Poor" "Poor" "Poor" "Poor" "Poor" "Poor"
## [691] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [697] "Good" "Good" "Poor" "Good" "Good" "Good"
## [703] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [709] "Good" "Good" "Poor" "Poor" "Poor" "Poor"
## [715] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [721] "Poor" "Poor" "Poor" "Poor" "Poor" "Poor"
## [727] "Good" "Poor" "Poor" "Good" "Poor" "Poor"
## [733] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [739] "Poor" "Poor" "Good" "Poor" "Poor" "Poor"
## [745] "Poor" "Good" "Good" "Poor" "Good" "Good"
## [751] "Poor" "Poor" "Poor" "Poor" "Good" "Good"
## [757] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [763] "Good" "Poor" "Good" "Good" "Poor" "Poor"
## [769] "Good" "Poor" "Good" "Poor" "Poor" "Good"
## [775] "Good" "Poor" "Good" "Good" "Poor" "Poor"
## [781] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [787] "Poor" "Good" "Good" "Poor" "Good" "Poor"
## [793] "Good" "Poor" "Good" "Poor" "Poor" "Good"
## [799] "Good" "Good" "Poor" "Poor" "Good" "Good"
## [805] "Good" "Good" "Good" "Good" "Poor" "Good"
## [811] "Poor" "Good" "Poor" "Poor" "Good" "Poor"
## [817] "Good" "Good" "Poor" "Poor" "Poor" "Good"
## [823] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [829] "Excellent" "Good" "Poor" "Good" "Poor" "Poor"
## [835] "Poor" "Poor" "Good" "Good" "Good" "Poor"
## [841] "Good" "Poor" "Good" "Poor" "Good" "Poor"
## [847] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [853] "Poor" "Good" "Good" "Good" "Good" "Good"
## [859] "Good" "Good" "Poor" "Good" "Poor" "Poor"
## [865] "Poor" "Poor" "Good" "Good" "Good" "Good"
## [871] "Good" "Poor" "Poor" "Good" "Good" "Good"
## [877] "Poor" "Good" "Good" "Poor" "Poor" "Good"
## [883] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [889] "Good" "Poor" "Poor" "Poor" "Good" "Poor"
## [895] "Good" "Good" "Good" "Good" "Good" "Poor"
## [901] "Poor" "Good" "Good" "Good" "Good" "Poor"
## [907] "Poor" "Good" "Good" "Good" "Good" "Good"
## [913] "Good" "Good" "Good" "Good" "Poor" "Good"
## [919] "Good" "Good" "Poor" "Good" "Good" "Good"
## [925] "Poor" "Good" "Good" "Poor" "Poor" "Good"
## [931] "Poor" "Poor" "Good" "Poor" "Poor" "Good"
## [937] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [943] "Good" "Good" "Good" "Good" "Good" "Good"
## [949] "Good" "Good" "Good" "Good" "Good" "Good"
## [955] "Good" "Poor" "Good" "Good" "Good" "Poor"
## [961] "Good" "Poor" "Poor" "Good" "Good" "Good"
## [967] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [973] "Good" "Poor" "Good" "Poor" "Poor" "Poor"
## [979] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [985] "Poor" "Good" "Good" "Poor" "Poor" "Good"
## [991] "Poor" "Poor" "Good" "Poor" "Poor" "Good"
## [997] "Good" "Good" "Good" "Good" "Good" "Good"
## [1003] "Good" "Good" "Poor" "Good" "Good" "Good"
## [1009] "Good" "Poor" "Good" "Good" "Poor" "Good"
## [1015] "Good" "Good" "Good" "Good" "Good" "Poor"
## [1021] "Good" "Good" "Poor" "Good" "Good" "Good"
## [1027] "Good" "Poor" "Good" "Good" "Good" "Good"
## [1033] "Poor" "Good" "Good" "Good" "Good" "Poor"
## [1039] "Good" "Good" "Poor" "Good" "Good" "Good"
## [1045] "Good" "Good" "Good" "Poor" "Good" "Good"
## [1051] "Poor" "Poor" "Poor" "Good" "Good" "Good"
## [1057] "Good" "Poor" "Good" "Good" "Good" "Excellent"
## [1063] "Good" "Good" "Good" "Good" "Good" "Good"
## [1069] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [1075] "Poor" "Good" "Good" "Poor" "Poor" "Good"
## [1081] "Good" "Good" "Good" "Good" "Good" "Poor"
## [1087] "Good" "Good" "Good" "Good" "Excellent" "Good"
## [1093] "Good" "Good" "Good" "Poor" "Good" "Poor"
## [1099] "Good" "Poor" "Good" "Good" "Good" "Good"
## [1105] "Good" "Poor" "Good" "Good" "Poor" "Good"
## [1111] "Good" "Good" "Good" "Good" "Good" "Good"
## [1117] "Good" "Good" "Good" "Poor" "Excellent" "Good"
## [1123] "Good" "Good" "Poor" "Good" "Good" "Good"
## [1129] "Poor" "Good" "Good" "Poor" "Good" "Good"
## [1135] "Good" "Good" "Good" "Good" "Poor" "Good"
## [1141] "Good" "Good" "Good" "Good" "Poor" "Good"
## [1147] "Good" "Good" "Good" "Good" "Good" "Good"
## [1153] "Poor" "Good" "Good" "Poor" "Good" "Good"
## [1159] "Good" "Poor" "Good" "Good" "Good" "Poor"
## [1165] "Poor" "Poor" "Poor" "Good" "Good" "Good"
## [1171] "Good" "Good" "Good" "Good" "Good" "Good"
## [1177] "Poor" "Good" "Poor" "Good" "Good" "Poor"
## [1183] "Good" "Poor" "Poor" "Good" "Poor" "Good"
## [1189] "Poor" "Poor" "Good" "Poor" "Good" "Poor"
## [1195] "Good" "Good" "Good" "Good" "Good" "Good"
## [1201] "Good" "Good" "Excellent" "Poor" "Good" "Good"
## [1207] "Good" "Poor" "Good" "Good" "Good" "Poor"
## [1213] "Good" "Good" "Good" "Good" "Good" "Good"
## [1219] "Good" "Good" "Good" "Good" "Good" "Good"
## [1225] "Good" "Poor" "Poor" "Poor" "Good" "Poor"
## [1231] "Good" "Poor" "Poor" "Poor" "Good" "Poor"
## [1237] "Good" "Good" "Poor" "Poor" "Poor" "Poor"
## [1243] "Good" "Poor" "Good" "Poor" "Poor" "Poor"
## [1249] "Good" "Good" "Good" "Poor" "Poor" "Poor"
## [1255] "Poor" "Poor" "Poor" "Good" "Good" "Good"
## [1261] "Poor" "Poor" "Poor" "Poor" "Good" "Good"
## [1267] "Good" "Good" "Good" "Excellent" "Good" "Good"
## [1273] "Poor" "Poor" "Good" "Good" "Poor" "Good"
## [1279] "Good" "Good" "Good" "Good" "Good" "Good"
## [1285] "Poor" "Poor" "Good" "Poor" "Poor" "Poor"
## [1291] "Poor" "Good" "Good" "Poor" "Good" "Poor"
## [1297] "Poor" "Good" "Good" "Poor" "Good" "Good"
## [1303] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [1309] "Poor" "Poor" "Poor" "Good" "Poor" "Good"
## [1315] "Good" "Good" "Good" "Good" "Good" "Good"
## [1321] "Poor" "Good" "Poor" "Good" "Good" "Good"
## [1327] "Good" "Good" "Poor" "Good" "Good" "Poor"
## [1333] "Good" "Poor" "Poor" "Good" "Poor" "Poor"
## [1339] "Poor" "Good" "Good" "Good" "Good" "Good"
## [1345] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [1351] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [1357] "Poor" "Good" "Poor" "Good" "Poor" "Poor"
## [1363] "Good" "Poor" "Good" "Poor" "Poor" "Good"
## [1369] "Good" "Poor" "Poor" "Good" "Poor" "Poor"
## [1375] "Poor" "Poor" "Poor" "Good" "Good" "Good"
## [1381] "Good" "Poor" "Poor" "Poor" "Poor" "Poor"
## [1387] "Poor" "Poor" "Poor" "Poor" "Good" "Poor"
## [1393] "Poor" "Poor" "Poor" "Good" "Poor" "Poor"
## [1399] "Good" "Good" "Poor" "Poor" "Good" "Excellent"
## [1405] "Good" "Good" "Good" "Good" "Good" "Good"
## [1411] "Good" "Good" "Good" "Poor" "Poor" "Poor"
## [1417] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [1423] "Good" "Poor" "Good" "Good" "Good" "Poor"
## [1429] "Poor" "Poor" "Poor" "Good" "Good" "Good"
## [1435] "Good" "Good" "Poor" "Poor" "Poor" "Good"
## [1441] "Good" "Good" "Poor" "Poor" "Good" "Good"
## [1447] "Poor" "Poor" "Poor" "Excellent" "Good" "Good"
## [1453] "Good" "Poor" "Good" "Good" "Good" "Poor"
## [1459] "Poor" "Good" "Good" "Poor" "Good" "Good"
## [1465] "Poor" "Poor" "Good" "Poor" "Good" "Poor"
## [1471] "Poor" "Poor" "Good" "Poor" "Poor" "Good"
## [1477] "Poor" "Good" "Poor" "Poor" "Poor" "Poor"
## [1483] "Poor" "Poor" "Poor" "Poor" "Poor" "Poor"
## [1489] "Poor" "Good" "Good" "Poor" "Poor" "Poor"
## [1495] "Good" "Good" "Poor" "Good" "Good" "Good"
## [1501] "Poor" "Poor" "Poor" "Good" "Good" "Poor"
## [1507] "Good" "Good" "Good" "Poor" "Good" "Poor"
## [1513] "Good" "Good" "Good" "Good" "Poor" "Good"
## [1519] "Poor" "Poor" "Good" "Poor" "Poor" "Poor"
## [1525] "Good" "Poor" "Good" "Good" "Good" "Good"
## [1531] "Good" "Poor" "Good" "Poor" "Good" "Good"
## [1537] "Good" "Good" "Poor" "Poor" "Good" "Good"
## [1543] "Good" "Good" "Good" "Good" "Poor" "Poor"
## [1549] "Poor" "Excellent" "Poor" "Poor" "Good" "Poor"
## [1555] "Good" "Good" "Poor" "Good" "Poor" "Poor"
## [1561] "Poor" "Poor" "Poor" "Poor" "Poor" "Good"
## [1567] "Good" "Poor" "Poor" "Good" "Good" "Good"
## [1573] "Poor" "Good" "Good" "Good" "Good" "Good"
## [1579] "Good" "Poor" "Good" "Poor" "Poor" "Poor"
## [1585] "Good" "Good" "Good" "Good" "Good" "Poor"
## [1591] "Good" "Good" "Good" "Good" "Poor" "Good"
## [1597] "Good" "Poor" "Good"table(Wine.Dataset$rating)##
## Excellent Good Poor
## 18 837 744##bar chart
barplot(table(Wine.Dataset$rating),xlab = "Ratings",ylab = "count" )
ggplot(Wine.Dataset, aes(density, chlorides)) + geom_point(aes(color = rating)) +
scale_x_continuous("Wine Density")+
scale_y_continuous("chloride conent", breaks = seq(0,0.70,0.05))+
theme_bw() + labs(title="Scatterplot")
ggplot(Wine.Dataset, aes(density, chlorides)) + geom_point(aes(color = rating)) +
scale_x_continuous("Wine Density")+
scale_y_continuous("chloride conent", breaks = seq(0,0.70,0.05))+
theme_bw() + labs(title="Scatterplot")+ facet_wrap( ~ rating)
##piechart
pie(table(Wine.Dataset$rating),col=c("red","lightblue","lightgreen"),main="Wine-rating split up")
##violin plot
ggplot(Wine.Dataset,aes(rating,alcohol))+geom_violin()
##boxplot
ggplot(Wine.Dataset,aes(rating,alcohol))+geom_boxplot()
##boxplot in violin plot
ggplot(Wine.Dataset,aes(rating,alcohol))+geom_violin(col ="darkblue",fill="lightblue",trim = FALSE)+geom_boxplot(fill="red",width=0.2)
##jitter
ggplot(Wine.Dataset,aes(rating,alcohol))+geom_jitter(col ="blue")
#Heat Map
ggplot(data = Wine.Dataset,aes(x=rating,y=citric.acid,fill=alcohol))+geom_tile()+xlab(label = "Rating")
ggplot(data = Wine.Dataset,aes(x=rating,y=citric.acid,fill=alcohol))+geom_tile()+xlab(label = "Rating")+facet_wrap(~ rating)
##beeswarm plot
library(beeswarm)
beeswarm(Wine.Dataset$fixed.acidity,main ="Beeswarm graph for fixed acidity")