1 Create a Simple Scatter Plot in R

Enter the data by hand:

Xdata = c(162, 150, 142, 126, 149, 195, 82, 194, 111, 122)
Ydata = c(183, 149, 154, 100, 139, 106, 150, 190, 170, 198)
plot(Xdata, Ydata, main = "Simple Scatter Plot")

Example 1: Simple Scatter Plot in R

Using a Data Object:

Using the attitude data from the "datasets" package with some sub-setting and filtering.

Sample rows from attitude:

attitude

   rating complaints privileges learning raises critical advance
1      43         51         30       39     61       92      45
6      43         55         49       44     54       49      34
10     67         61         45       47     62       80      41
13     69         62         57       42     55       63      25
16     81         90         50       72     60       54      36
17     74         85         64       69     79       79      63
23     53         66         52       50     63       80      37
27     78         75         58       74     80       78      49
29     85         85         71       71     77       74      55
30     82         82         39       59     64       78      39

x = attitude$rating
y = attitude$complaints
plot(x, y, pch = 15, main = "Simple Scatter Plot")

Or:

x = attitude[, "rating"]
y = attitude[, "complaints"]
plot(x, y, pch = 15, main = "Simple Scatter Plot")

Example 2: Simple Scatter Plot in R

2 Create Scatter Plot with Regression Line and Lowess Fit in R

To make a scatter plot with regression line and lowess fit, use the abline() and lines() functions respectively. For the "f" argument in lowess() function, the higher the value, the smoother the line. See line types & widths and adding lines to plots.

x = attitude$privileges
y = attitude$learning
plot(x, y)
abline(lm(y ~ x), col = "blue")
lines(lowess(x, y, f = 0.5), col = "red", lty = "dashed")
lines(lowess(x, y, f = 2), col = "green", lty = "dashed")

Scatter Plot with Regression Line and Lowess Fit in R

3 Set Title, Labels, Limits, Colors, Dot Type, Fonts of a Scatter Plot in R

Here we set details such as title (main), x-axis and y-axis labels (xlab, ylab), limits (xlim, ylim), colors (col), dot type (pch), font types (font), and font sizes (cex). See also setting colors and fonts for more details.

x = attitude$raises
y = attitude$rating
plot(x, y,
     main = "Ratings vs Raises",
     xlab = "Raises", ylab = "Ratings",
     xlim = c(min(x), max(x)),
     ylim = c(min(y), max(y)),
     col = "purple",
     col.main="blue", col.lab="green", col.axis="gold",
     pch = 3,
     font=3, font.lab=2, font.main=4,
     cex.main=2, cex.lab=1.25, cex.axis=1.25)

# Add lines

abline(lm(y ~ x), col = "blue")
lines(lowess(x, y, f = 0.5), col = "green", lty = "dashed", lwd =2)
lines(lowess(x, y, f = 2), col = "red", lty = "dotted", lwd = 4)

Scatter Plot with Title, Labels, Limits, Colors, Dot Type, Fonts Set in R

4 Multiple Scatter Plots Overlay with Different Colors by Variables in R

To have multiple scatter plots overlaid in one plot, use the points() function. You can add details to the scatter plot and the points as in the example above. You should also adjust the axes limits if necessary to include the extra points added to the plot.

Rtg = attitude$rating
Cmp = attitude$complaints
Rai = attitude$raises
Crt = attitude$critical

plot(Cmp, Rtg, col = "green")
points(Rai, Rtg, col = "blue", cex = 1.5)
points(Crt, Rtg, col = "red", cex = 2.5)

Multiple Scatter Plots Overlay with Different Colors by Variables in R

Adjust the axes limits to accommodate for the limits of the new points added.

plot(Cmp, Rtg,
     xlim = range(c(Rtg, Cmp, Rai, Crt)),
     ylim = range(c(Rtg, Cmp, Rai, Crt)),
     col = "green")
points(Rai, Rtg, col = "blue", cex = 1.5)
points(Crt, Rtg, col = "red", cex = 2.5)

Multiple Scatter Plots Overlay in One Plot (Limits Adjusted) in R

5 Multiple Variables Scatter Plot Side-by-side in One Plot in R

To have multiple variables scatter plots side-by-side in one plot, use the par() function. The first argument is the number of rows, while the second is the number of columns. Then make your scatter plots, and they will be added one after the other. You can add details to each scatter plot as in the examples above. See also multiple plots on the same graph for more details.

For example, for 2 rows and 3 columns use:

par(mfrow=c(2,3))
plot(attitude$rating, attitude$complaints)
plot(attitude$rating, attitude$privileges)
plot(attitude$rating, attitude$learning)
plot(attitude$rating, attitude$raises)
plot(attitude$rating, attitude$critical)
plot(attitude$rating, attitude$advance)

Multiple Variables Scatter Plots Side-by-side in One Plot in R

For scatter plot of each column vs the others:

plot(attitude)

Multiple Variables Scatter Plots in One Plot (Each vs Others) in R

For a subset of the dataframe selecting some of the columns and excluding the others:

plot(attitude[, c("rating", "complaints", "learning", "critical")])

Multiple Variables Scatter Plots Side-by-side in One Plot (Select Columns) in R