To get a better sense of the data in the iris.data matrix, let’s visualize it!
With Matplotlib, we can create a 2D scatter plot of the Iris dataset using two of its features (sepal length vs. petal length). The sepal length measurements are stored in column 0 of the matrix, and the petal length measurements are stored in column 2 of the matrix.
But how do we get these values?
Suppose we only want to retrieve the values that are in column 0 of a matrix, we can use the NumPy/pandas notation [:,0] like so:
[:,0] can be translated to [all_rows , column_0]
Once you have the measurements we need, we can make a scatter plot like this:
To show the plot:
Let’s try this! But this time, plot the sepal length (column 0) vs. sepal width (column 1) instead.
Instructions
Store iris.data in a variable named samples.
Create a list named x that contains the column 0 values of samples.
Create a list named y that contains the column 1 values of samples.
Use the .scatter() function to create a scatter plot of x and y.
Because some of the data samples have the exact same features, let’s add alpha=0.5:
Call the .show() function to display the graph.
If you didn’t know there are three species of the Iris plant, would you have known just by looking at the visualization?