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Now let’s have a look at some 2-Dimensional plots:
As mentioned earlier, these plots are made with the help of R software.
1. BARPLOT
A bar plot is also known as a bar chart that shows bars of different values hence of different heights to depict the relationship between numerical and some sort of categorical data.
Syntax of Bar plot in R:
barplot(titanic$fare)
2. BOXPLOT
A simple way of representing statistical data on a plot during which a rectangle is drawn to represent the second and third quartiles, usually with a vertical line inside to point to the median. The lower and upper quartiles are shown as horizontal lines on either side of the rectangle.
Syntax of Boxplot in R:
boxplot(titanic$age,titanic$fare)
3. SCATTERPLOT
This plot is used to visualize the relationship between the continuous variables. Since the data points seem to be scattered in the graph hence, it is called a scatter plot. It uses cartesian coordinates to display the values.
Syntax of Scatterplot in R:
ggplot(titanic,aes(x = age, y = fare))+ geom_point()
4. 2D PIE CHART
It is used to represent values in the form of slices of a circle in different colours. We label the slices and represent those numbers in the chart.
Syntax of 2D Pie chart in R:
library(plotly) fig <- plot_ly(titanic, labels = ~names, values = ~fare, type = 'pie') fig
5. 2D DENSITY PLOT
A related visualization to the histogram is a density plot. A density plot is a smoothed version of the histogram. It uses a kernel density estimate to point out the probability density function of the variable.
Syntax of Density Plot in R:
ggplot(data, aes(x=x, y=y))+ stat_density_2d(aes(fill = ..level..),geom=”polygon”)