# R - Scatterplots

The simple scatterplot is created using the

**plot()**function.

## Syntax

The basic syntax for creating scatterplot in R is −plot(x, y, main, xlab, ylab, xlim, ylim, axes)Following is the description of the parameters used −

**x**is the data set whose values are the horizontal coordinates.**y**is the data set whose values are the vertical coordinates.**main**is the tile of the graph.**xlab**is the label in the horizontal axis.**ylab**is the label in the vertical axis.**xlim**is the limits of the values of x used for plotting.**ylim**is the limits of the values of y used for plotting.**axes**indicates whether both axes should be drawn on the plot.

## Example

We use the data set**"mtcars"**available in the R environment to create a basic scatterplot. Let's use the columns "wt" and "mpg" in mtcars.

input <- mtcars[,c('wt','mpg')] print(head(input))When we execute the above code, it produces the following result −

wt mpg Mazda RX4 2.620 21.0 Mazda RX4 Wag 2.875 21.0 Datsun 710 2.320 22.8 Hornet 4 Drive 3.215 21.4 Hornet Sportabout 3.440 18.7 Valiant 3.460 18.1

## Creating the Scatterplot

The below script will create a scatterplot graph for the relation between wt(weight) and mpg(miles per gallon).# Get the input values. input <- mtcars[,c('wt','mpg')] # Give the chart file a name. png(file = "scatterplot.png") # Plot the chart for cars with weight between 2.5 to 5 and mileage between 15 and 30. plot(x = input$wt,y = input$mpg, xlab = "Weight", ylab = "Milage", xlim = c(2.5,5), ylim = c(15,30), main = "Weight vs Milage" ) # Save the file. dev.off()When we execute the above code, it produces the following result −

## Scatterplot Matrices

When we have more than two variables and we want to find the correlation between one variable versus the remaining ones we use scatterplot matrix. We use**pairs()**function to create matrices of scatterplots.

### Syntax

The basic syntax for creating scatterplot matrices in R is −pairs(formula, data)Following is the description of the parameters used −

**formula**represents the series of variables used in pairs.**data**represents the data set from which the variables will be taken.

### Example

Each variable is paired up with each of the remaining variable. A scatterplot is plotted for each pair.# Give the chart file a name. png(file = "scatterplot_matrices.png") # Plot the matrices between 4 variables giving 12 plots. # One variable with 3 others and total 4 variables. pairs(~wt+mpg+disp+cyl,data = mtcars, main = "Scatterplot Matrix") # Save the file. dev.off()When the above code is executed we get the following output.

*Table of contents:*1. R - Overview

2. R - Environment Setup

3. R - Basic Syntax

4. R - Data Types

5. R - Variables

6. R - Operators

7. R - Decision Making

8. R - Loops

9. R - Functions

10. R - Strings

11. R - Vectors

12. R - Matrices

13. R - Arrays

14. R - Factors

15. R - Data Frames

16. R - Packages

17. R - Data Reshaping

18. R - CSV Files

19. R - Excel Files

20. R - Binary Files

21. R - XML Files

22. R - JSON Files

23. R - Web Data

24. R - Database

25. R - Pie Charts

26. R - Bar Charts

27. R - Boxplots

28. R - Histograms

29. R - Line Graphs

30. R - Scatterplots

31. R - Mean, Median and Mode

32. R - Linear Regression

33. R - Multiple Regression

34. R - Logistic Regression

35. R - Normal Distribution

36. R - Binomial Distribution

37. R - Poisson Regression

38. R - Analysis of Covariance

39. R - Time Series Analysis

40. R - Nonlinear Least Square

41. R - Decision Tree

42. R - Random Forest

43. R - Survival Analysis

44. R - Chi Square Tests

## No comments:

## Post a Comment