Hello I have the following function that I get from scikit-learn site, I try to reduce the function only for one plot, but I cannot do more than this:

[![enter image description here](https://i.stack.imgur.com/2vPVT.png)](https://i.stack.imgur.com/2vPVT.png)

Using the following code:

```
def plot_learning_curve(estimator,X, y, axes=None, cv=None,
                        n_jobs=None, train_sizes=np.linspace(.1, 1.0, 5)):

    _, axes = plt.subplots(2, 1, figsize=(10, 20))

    axes[0].set_title('Curvas de error de aprendizaje')
    axes[0].set_xlabel("Nº Ejemplos de entrenamiento")
    axes[0].set_ylabel("Error: 1 - F1")

    train_sizes, train_scores, test_scores, fit_times, _ = \
        learning_curve(estimator, X, y, cv=cv, n_jobs=n_jobs,
                       train_sizes=train_sizes,
                       return_times=True)
    train_scores_mean = np.mean([1] - train_scores, axis=1)
    train_scores_std = np.std([1] - train_scores, axis=1)
    test_scores_mean = np.mean([1] - test_scores, axis=1)
    test_scores_std = np.std([1] - test_scores, axis=1)

    # Plot learning curve
    axes[0].grid()
    axes[0].fill_between(train_sizes, train_scores_mean - train_scores_std,
                         train_scores_mean + train_scores_std, alpha=0.1,
                         color="r")
    axes[0].fill_between(train_sizes, test_scores_mean - test_scores_std,
                         test_scores_mean + test_scores_std, alpha=0.1,
                         color="g")
    axes[0].plot(train_sizes, train_scores_mean, 'o-', color="r",
                 label="Error de entrenamiento")
    axes[0].plot(train_sizes, test_scores_mean, 'o-', color="g",
                 label="Error de validación medio (cv=10)")
    axes[0].legend(loc="best")

    return plt

```

The question is how can I remove the second subplot.

Thanks