The plot() function in R is a versatile function for creating a variety of plots.

**Syntax**
plot(x, y, ...)

Above example is based on two vector points.

We can also use 1 point in a plot() function.

and we can use numeric values instead of a vectors.

If we need to plot from a sequence of numbers you can keep the values from start to end in this format x:y

There are various attributes in a plot() function to describe and apply the values given.

**Attribute**

**Description**

**Example**

Main Title (main)

Main title of the plot.

plot(x, y, main = "Scatter Plot")

Axis Labels (xlab and ylab)

**xlab**- Label for the x-axis.**ylab**- Label for the y-axis.

plot(x, y, xlab = "X-axis", ylab = "Y-axis")

Plot Type (type)

Type of plot (e.g., "p" for points, "l" for lines).

plot(x, y, type = "p")

Point Characteristics (col, pch, cex, lty)

**col**- Point color.**pch**- Point shape.**cex**- Point size.**lty**- Line type.

plot(x, y, col = "blue", pch = 16, cex = 1.5, lty = 2)

Plotting Multiple Sets of Data

Use additional arguments like points() or lines() to overlay multiple sets of data

plot(x1, y1, col = "red"); points(x2, y2, col = "blue", pch = 2)

Axes (xlim and ylim)

**xlim**- Limits for the x-axis.**ylim**- Limits for the y-axis.

plot(x, y, xlim = c(0, 10), ylim = c(-2, 2))

Grid (grid)

Adds a grid to the plot.

plot(x, y, grid = TRUE)

Adding Lines (abline)

Adds lines to the plot.

plot(x, y); abline(h = 0, v = 0, col = "red", lty = 2)

Example

```
# Sample data
set.seed(123)
x <- rnorm(50)
y <- 2 * x + rnorm(50)
# Create a scatter plot with customization
plot(
x, y,
main = "Scatter Plot with Customization",
xlab = "X-axis",
ylab = "Y-axis",
col = "blue",
pch = 16,
cex = 1.5,
xlim = c(-2, 2),
ylim = c(-4, 4),
grid = TRUE
)
# Add a regression line
abline(lm(y ~ x), col = "red", lty = 2)
# Add points with different color and shape
points(x[25:30], y[25:30], col = "green", pch = 3)
# Add a legend
legend("topright", # Specify the position of the legend
legend = c("Data", "Regression Line", "Additional Points"), # Legend text
col = c("blue", "red", "green"), # Line colors corresponding to each distribution
pch = c(16, NA, 3), # Line colors corresponding to each distribution
lty = c(NA, 2, NA), # Line type
cex = 0.8 # Point size)
```

The legend function is used to add a legend to the plot.

Inside legend function we have

The position of the legend, legend text and col specifies the line colors.

There are different types of plot. Here are the list

**Type Argument**

**Description**

**Example**

p

Scatter Plot

plot(x, y, type = "p")

l

Line Plot

plot(x, y, type = "l")

b

Both Points and Lines

plot(x, y, type = "b")

s

Step Plot

plot(x, y, type = "s")

h

Histogram

plot(x, y, type = "h")

S

Staircase Plot

plot(x, y, type = "S")

e

Error Bars

plot(x, y, type = "e")

box

Box Plot

plot(x, type = "box")

contour

Contour Plot

plot(x, y, type = "contour")

heatmap

Heatmap (with matrix data)

plot(matrix_data, type = "h")

Learn more about them in detail in the tutorial.

R Plot

Attributes in a plot

Types of Plot

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Example 1

Example 1
Example 2
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