# Data Analyst’s Recipe | How to create a scatter plot in MATLAB

Creating a scatter plot in MATLAB is a useful way to visualize the relationship between two continuous variables. In this tutorial, we will walk through the steps to create a scatter plot in MATLAB and explore the UCI dataset as an example.

First, we need to load the data that we want to use for our scatter plot. For this tutorial, we will be using the `iris` dataset which is included in the `datasets` package in MATLAB.

``````% Load the iris dataset

# Creating a scatter plot using scatter function

Next, we will create a scatter plot using the `scatter()` function in MATLAB. We will use the `scatter()` function to create the basic plot object and then add layers to customise the plot.

``````% Create a basic scatter plot
scatter(meas(:,1), meas(:,2))
xlabel('Sepal Length')
ylabel('Sepal Width')
title('Sepal Length vs. Sepal Width')``````

In the above code, we first loaded the `fisheriris` dataset using the `load()` function. Then, we created a basic scatter plot using the `scatter()` function and specified the `meas(:,1)` and `meas(:,2)` as the variables to be plotted on the x and y axes respectively. Finally, we added the x and y axis labels, and a title to the plot using the `xlabel()`, `ylabel()` and `title()` functions.

# Customizing the scatter plot

Now that we have created a basic scatter plot, we can customize it to make it more visually appealing and informative. Here are a few examples:

## Changing the colour of the points based on a third variable

``````% Create a scatter plot with points colored by species
gscatter(meas(:,1), meas(:,2), species)
xlabel('Sepal Length')
ylabel('Sepal Width')
title('Sepal Length vs. Sepal Width')``````

In the above code, we used the `gscatter()` function to create a scatter plot where the points are colored by the `species` variable. This creates a scatter plot where each species is represented by a different color.

``````% Create a scatter plot with a regression line
scatter(meas(:,1), meas(:,2))
xlabel('Sepal Length')
ylabel('Sepal Width')
title('Sepal Length vs. Sepal Width')
hold on
mdl = fitlm(meas(:,1), meas(:,2));
plot(mdl)``````

In the above code, we first created a basic scatter plot. Then, we used the `fitlm()` function to create a linear regression model of `meas(:,1)` vs. `meas(:,2)`. Finally, we added the regression line to the plot using the `plot()` function.

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