R Notebook

#ggplot2

##scatter plot

library(ggplot2)
#aes=exis
#geom_point for scatter plot
ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2)

Color change according to type

library(ggplot2)
#aes=exis
#geom_point for scatter plot
ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2) +
  #Naming should be according to the dataset
  scale_colour_manual(values = c("Setosa" = "blue", "Versicolor" = "red", "Virginica" = "green"))

Lebels

library(ggplot2)
#aes=exis
#geom_point for scatter plot
ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2) +
  #Naming should be according to the dataset
  scale_colour_manual(values = c("Setosa" = "blue", "Versicolor" = "red", "Virginica" = "green")) +
  labs(title = "Scatterplot using ggplot2",
       x = "Length",
       y = "Width",
       caption = "Source: Iris Dataset"
       )

Theme

library(ggplot2)
#aes=exis
#geom_point for scatter plot
ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2) +
  #Naming should be according to the dataset
  scale_colour_manual(values = c("Setosa" = "blue", "Versicolor" = "red", "Virginica" = "green")) +
  labs(title = "Scatterplot using ggplot2",
       x = "Length",
       y = "Width",
       caption = "Source: Iris Dataset") +
  theme_minimal() #transparent/white background

Legend position

library(ggplot2)
#aes=exis
#geom_point for scatter plot
ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2) +
  #Naming should be according to the dataset
  scale_colour_manual(values = c("Setosa" = "blue", "Versicolor" = "red", "Virginica" = "green")) +
  labs(title = "Scatterplot using ggplot2",
       x = "Length",
       y = "Width",
       caption = "Source: Iris Dataset") +
  theme(legend.position = "bottom")

Text change

library(ggplot2)
#aes=exis
#geom_point for scatter plot
ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2) +
  #Naming should be according to the dataset
  scale_colour_manual(values = c("Setosa" = "blue", "Versicolor" = "red", "Virginica" = "green")) +
  labs(title = "Scatterplot using ggplot2",
       x = "Length",
       y = "Width",
       caption = "Source: Iris Dataset") +
  
  theme(legend.position = "bottom",
        text = element_text(color = "black", size = 10),
        axis.text.x = element_text(color = "blue", size = 9),
        axis.text.y = element_text(color = "red", size = 9)
        )

Image quality modification

library(ggplot2)
#aes=exis
#geom_point for scatter plot
scatter_plot = ggplot(iris, aes(x = sepal.length, y = sepal.width, color = variety)) +
  geom_point(size = 2) +
  #Naming should be according to the dataset
  scale_colour_manual(values = c("Setosa" = "blue", "Versicolor" = "red", "Virginica" = "green")) +
  labs(title = "Scatterplot using ggplot2",
       x = "Length",
       y = "Width",
       caption = "Source: Iris Dataset") +
  
  theme(legend.position = "bottom",
        text = element_text(color = "black", size = 10),
        axis.text.x = element_text(color = "blue", size = 9),
        axis.text.y = element_text(color = "red", size = 9)
        )
scatter_plot
#save as a variable
ggsave("scatter_plot_500dpi.png", dpi = 500)

Saving 4.17 x 2.57 in image

Plot as a Variable

scatter_plot

Boxplot

box_plot = ggplot(iris, aes(x = variety, y = sepal.length, fill = variety)) +
  #fill for default color 
  #aes foe axis
geom_boxplot() +
  labs(title = "Boxplot using ggplot2",
       x = "Class",
       y = "Length") +
  
  theme(legend.position = "right",
        text = element_text(color = "black", size = 10),
        axis.text.x = element_text(color = "blue", size = 9),
        axis.text.y = element_text(color = "red", size = 8))
  box_plot
#save as a variable
ggsave("box_plot_500dpi.png", dpi = 500)

Saving 7.29 x 4.5 in image

#here the dot sign is a outlier

As a variable

box_plot