visualisali

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.5.3

library(data.table)

## Warning: package 'data.table' was built under R version 4.5.3

datairis<- as.data.table(iris)

summary(datairis)

##   Sepal.Length    Sepal.Width     Petal.Length    Petal.Width   
##  Min.   :4.300   Min.   :2.000   Min.   :1.000   Min.   :0.100  
##  1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600   1st Qu.:0.300  
##  Median :5.800   Median :3.000   Median :4.350   Median :1.300  
##  Mean   :5.843   Mean   :3.057   Mean   :3.758   Mean   :1.199  
##  3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100   3rd Qu.:1.800  
##  Max.   :7.900   Max.   :4.400   Max.   :6.900   Max.   :2.500  
##        Species  
##  setosa    :50  
##  versicolor:50  
##  virginica :50  
##                 
##                 
## 

str(datairis)

## Classes 'data.table' and 'data.frame':   150 obs. of  5 variables:
##  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
##  - attr(*, ".internal.selfref")=<externalptr>

ggplot(datairis, aes(x= Sepal.Length)) +
  geom_histogram(fill= "purple") +
  labs(tittle= "Histogram Sepal Length")

## Ignoring unknown labels:
## • tittle : "Histogram Sepal Length"
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.

ggplot(datairis, aes(y = Sepal.Length)) +
  geom_boxplot(fill = "pink") +
  labs(title = "Boxplot Sepal Lenght")

ggplot(datairis, aes(x = Sepal.Length, y = Sepal.Width))+
  geom_point(aes(color = Species)) +
  labs(title ="Scatter Plot")

pairs(iris[,1:4], col = iris$Species, pch = 19)

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width,
                 size = Petal.Length, color = Species)) +
  geom_point(alpha = 0.7) +
  labs(title = "Bubble Plot")

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