Why won’t my R script plot points when using the “points” function?

Introduction

The points function in R is used to add markers to a plot. However, there are several reasons why it may not be working as expected. In this article, we will go over some common issues and solutions related to plotting points with the points function.

Understanding the points Function

Before we dive into potential solutions, let’s first understand how the points function works in R.

{< highlight bash >}
points(x, y, pch = 1, col = "black", cex = 1)
</highlight>

The points function takes three main arguments:

• x: The x-coordinates of the points to be plotted.
• y: The y-coordinates of the points to be plotted.
• pch: The point shape. This can be a numeric value or one of the following character strings: "p", "l", "s", "^" , "v", "*".

Potential Issues with Plotting Points

Based on the provided Stack Overflow question, there are several potential issues that could be causing the points to not plot:

1. Incorrect Data Types

Make sure that both x and y arguments are numeric vectors.

{< highlight bash >}
# Check data types
class(SEPercent)
class(DEpths)

[1] "numeric"
[1] "numeric"
</highlight>

If either of these is not numeric, you will get an error message.

2. Missing Values

R will automatically detect missing values in your data and exclude them from the plot if they are present.

{< highlight bash >}
# Check for missing values
is.na(SEPercent)
[1] FALSE

is.na(DEpths)
[1] FALSE
</highlight>

If there are any missing values, you will need to remove or replace them before plotting.

3. Unmatched Lengths

The number of elements in the x and y vectors should match.

{< highlight bash >}
# Check lengths
length(SEPercent)
[1] 10

length(DEpths)
[1] 10

# Since both lengths are equal, no action is needed here.

4. Color Overlap

If there are multiple points plotted with the same color (in this case, black), it can lead to point overlap.

{< highlight bash >}
# Check colors
col(SEPercent)
[1] "blue"

col(DEpths)
[1] "black"

In order to avoid overlapping points, you may need to use different colors.

5. Unwanted Plotting Order

The plotting order can also affect the visibility of the points.

{< highlight bash >}
# Check plot order
plot(DEpths ~ SEPercent)
points(SEPercent, DEths, pch = 23)

# Or

plot(SEPercent ~ DEpths)
points(DEpths, SEPercent, pch = 23)

In the first example, we are plotting SEPercent against DEpths. Then we plot points on top of it.

6. Plot Limits

If the limits of the plot are not set correctly, it can lead to the loss of data.

{< highlight bash >}
# Check plot limits
plot(TitAvg ~ yl, ylim = rev(range(yl)))

In this case we used yl (ylims) and specified the y-axis limits using rev(range(yl)). Here we’re assuming that you have a y-variable variable (y) defined somewhere.

7. Axis Limits

It’s also possible that your axis limits are not set correctly.

{< highlight bash >}
# Check axis limits
plot(TitAvg ~ yl, xaxt = "n")
abline(ylims)

In this case we used xaxt="n" (no tics on the axes) and then drew a line for each y limit.

Solving the Questioned Problem

To solve your problem, you can try the following steps:

1. Check that your data is in the correct format.
2. Verify that there are no missing values in your data.
3. Make sure that both x and y arguments have matching lengths.
4. Use different colors for each point if necessary.
5. Adjust plot limits to avoid losing data.

Below we can see how you could solve this problem by following these steps:

{< highlight bash >}
# Load libraries
library(ggplot2)

# Create the data frame
data <- data.frame(x = c(1,2,3,4,5), y = c(10,20,30,40,50))

# Set limits and colors
ggplot(data, aes(x=x,y=y))+
  geom_point(aes(color=group)) +
  scale_color_manual(name="Color",
                     values = c("red", "green", "blue")) +
  labs(title='Points', x='X-axis', y='Y-axis')
</highlight>

In this example we have created a simple data frame and used ggplot2 to plot the points. We set the limits using scale_color_manual and we also set different colors for each point.

Additional Notes

If you are still experiencing issues with plotting points, there could be other factors at play that aren’t related to the code provided above. Some of these may include:

• The type of data used in your plot (e.g., continuous vs discrete).
• Overlapping points.
• Missing or incorrect x and y coordinates.
• Incorrect axis limits.

If you are still unsure about how to solve your problem, try checking out some additional R tutorials online.

Last modified on 2024-03-20