Matplotlib 3.0 Cookbook

How to do it...

Here are the steps involved in plotting a word embeddings graph:

1. Load the required data using pickle:

threed_embeddings = pickle.load(open('threed_embeddings','rb'))reverse_dictionary = pickle.load(open('word_reverse_dictionary',                                       'rb'))

2. Create the figure and axes for 3D plotting:

fig = plt.figure(figsize=(20,20))ax = fig.gca(projection='3d')

3. Draw the scatter plot with text annotation for each of the top 400 words:

num_points = 400words = [reverse_dictionary[i] for i in range(1, num_points+1)]for i, label in enumerate(words):    x, y, z = threed_embeddings[i,:]    ax.scatter(x, y, z)    ax.text(x, y, z, label, ha='right', va='bottom')

4. Set the limits and labels for the x, y, and z axes:

ax.set_xlim(-800,400)ax.set_ylim(-200,800) ...