How to Create a Scatterplot in R with Multiple Variables?
In this article, we will be looking at the way to create a scatter plot with multiple variables in the R programming language.
Using Plot() And Points() Function In Base R:
In this approach to create a scatter plot with multiple variables, the user needs to call the plot() function
- Plot() function: This is a generic function for the plotting of R objects.
Syntax:
plot(x, y, …)
Parameters:
- x: the x coordinates of points in the plot.
- y: the y coordinates of points in the plot
Points() function: It is a generic function to draw a sequence of points at the specified coordinates
Syntax:
points(x,y = NULL, type = “p”, …)
Parameters:
- x, y: coordinate vectors of points to plot.
- type: character indicating the type of plotting; actually any of the types as in plot.default.
- …: Further graphical parameters may also be supplied as arguments.
Example 1:
In this example, we will be creating a scatter plot of 2 different variables using the plot() and the point() function in the R programming language.
R
# Creating First variable gfg_x1 = c (9,1,8,7,7,3,2,4,5,6) gfg_y1 = c (7,4,1,5,9,6,3,3,6,9) # Creating Second variable gfg_x2 = c (4,1,5,9,7,4,5,2,8,4) gfg_y2 = c (9,1,5,7,4,1,3,6,5,2) # creating scatterplot of gfg_x1 vs. gfg_y1 plot (gfg_x1,gfg_y1, col= 'darkgreen' , pch=19) # Adding scatterplot of gfg_x2 vs gfg_y2 points (gfg_x2, gfg_y2, col= 'red' , pch=19) legend (1,9,legend= c ( 'Variable 1' , 'Variable 2' ), pch= c (19, 19), col= c ( 'darkgreen' , 'red' )) |
Output:
Example 2:
Here, we will be creating a scatter plot of 4 different variables.
R
# Creating First variable gfg_x1 = c (9,1,8,7,7,3,2,4,5,6) gfg_y1 = c (7,4,1,5,9,6,3,3,6,9) # Creating Second variable gfg_x2 = c (4,1,5,9,7,4,5,2,8,4) gfg_y2 = c (9,1,5,7,4,1,3,6,5,2) # Creating Third variable gfg_x3 = c (6,8,5,7,4,1,6,3,2,9) gfg_y3 = c (7,4,6,1,5,6,3,5,4,1) # Creating Fourth variable gfg_x4 = c (1,8,7,5,6,3,2,4,5,6) gfg_y4 = c (2,5,8,6,5,8,6,9,2,1) # creating scatterplot of gfg_x1 vs. gfg_y1 plot (gfg_x1,gfg_y1, col= 'darkgreen' , pch=19) # Adding scatterplot of gfg_x2 vs gfg_y2 points (gfg_x2, gfg_y2, col= 'red' , pch=19) # Adding scatterplot of gfg_x3 vs gfg_y3 points (gfg_x3, gfg_y3, col= 'blue' , pch=19) # Adding scatterplot of gfg_x4 vs gfg_y4 points (gfg_x4, gfg_y4, col= 'orange' , pch=19) legend ( 'topleft' ,legend= c ( 'Variable 1' , 'Variable 2' , 'Variable 3' , 'Variable 4' ), pch= c (19, 19), col= c ( 'darkgreen' , 'red' , 'blue' , 'orange' )) |
Output:
Example 3:
Here, we will be creating a scatter plot of 6 different variables.
R
# Creating First variable gfg_x1 = c (9,1,8,7,7,3,2,4,5,6) gfg_y1 = c (7,4,1,5,9,6,3,3,6,9) # Creating Second variable gfg_x2 = c (4,1,5,9,7,4,5,2,8,4) gfg_y2 = c (9,1,5,7,4,1,3,6,5,2) # Creating Third variable gfg_x3 = c (6,8,5,7,4,1,6,3,2,9) gfg_y3 = c (7,4,6,1,5,6,3,5,4,1) # Creating Fourth variable gfg_x4 = c (1,8,7,5,6,3,2,4,5,6) gfg_y4 = c (2,5,8,6,5,8,6,9,2,1) # Creating Fifth variable gfg_x5 = c (8,9,5,6,2,4,4,6,4,1) gfg_y5 = c (3,5,7,4,5,6,4,6,5,7) # Creating Sixth variable gfg_x6 = c (4,5,6,3,2,2,5,5,9,6) gfg_y6 = c (7,8,5,6,3,5,9,4,5,7) # creating scatterplot of gfg_x1 vs. gfg_y1 plot (gfg_x1,gfg_y1, col= 'darkgreen' , pch=19) # Adding scatterplot of gfg_x2 vs gfg_y2 points (gfg_x2, gfg_y2, col= 'red' , pch=19) # Adding scatterplot of gfg_x3 vs gfg_y3 points (gfg_x3, gfg_y3, col= 'blue' , pch=19) # Adding scatterplot of gfg_x4 vs gfg_y4 points (gfg_x4, gfg_y4, col= 'orange' , pch=19) # Adding scatterplot of gfg_x5 vs gfg_y5 points (gfg_x5, gfg_y5, col= 'purple' , pch=19) # Adding scatterplot of gfg_x6 vs gfg_y6 points (gfg_x6, gfg_y6, col= 'black' , pch=19) legend ( 'topleft' ,legend= c ( 'Variable 1' , 'Variable 2' , 'Variable 3' , 'Variable 4' , 'Variable 5' , 'Variable 6' ), pch= c (19, 19), col= c ( 'darkgreen' , 'red' , 'blue' , 'orange' , 'purple' , 'black' )) |
Output: