Matplotlib 3.0 Cookbook

How to do it...

Here are the steps to implement the logic:

1. Load and prepare the data for the 3D plot:

iris = pd.read_csv('iris_dataset.csv', delimiter=',')iris['species'] = iris['species'].map({"setosa" : 0, "versicolor" : 1, "virginica" : 2})x, y, z = iris['petal_length'], iris['petal_width'], iris['species']

2. Define and instantiate the figure and axes for 3D plotting:

fig = plt.figure(figsize=(8,6))ax = fig.add_subplot(111, projection='3d')

3. Draw the scatter plot using a for loop to plot each of the clusters with a different color and marker:

for name, c, marker in zip((0, 1, 2), ('r', 'b', 'g'), ('o', '^', '*')):    index = iris['species'] == name    ax.scatter(x[index], y[index], z[index], s=25*x[index]*y[index],                c=c, marker=marker)