39813c572463211d05f35a0dcac56ba7bd07c725,examples/plot_investigating_dirty_categories.py,,,#,17

Before Change

one_hot_encoded = categorical_encoder.fit_transform(
    sorted_values[:n_obs].reshape(-1, 1))
f3, ax3 = plt.subplots(figsize=(6, 6))
cax3 = ax3.matshow(one_hot_encoded[:n_obs, :n_categories])
f3.colorbar(cax3)
f3.suptitle("Employee Position Title values, one-hot encoded")
ax3.xaxis.tick_bottom()

After Change

// similarities:

f4, ax4 = plt.subplots(figsize=(6, 6))
similarity_encoded = similarity_encoder.fit_transform(employee_position_titles)
cax4 = ax4.matshow(similarity_encoded)
f4.colorbar(cax4)
f4.suptitle("Employee Position Title values, similarity encoded")
ax4.xaxis.tick_bottom()

Instances