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R - Scatterplots

Scatterplots show many points plotted in the Cartesian plane. Each point represents the values of two variables. One variable is chosen in the horizontal axis and another in the vertical axis.
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

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