Plot a scatterplot of two features against one another,
    and calculate Pearson correlation coefficient.

    Examples:
        `plot_pair(X, 'emb_mean_euclidean', 'emb_mean_cosine')`

    Args:
        df:
        feature_name_1: The name of the first feature.
        feature_name_2: The name of the second feature.
        kind: One of the values { 'scatter' | 'reg' | 'resid' | 'kde' | 'hex' }.
        alpha: Alpha channel value.
        **kwargs: Additional argument to 'sns.jointplot'.

def plot_pair(df, feature_name_1, feature_name_2, kind='scatter', alpha=0.01, **kwargs):
    """
    Plot a scatterplot of two features against one another,
    and calculate Pearson correlation coefficient.

    Examples:
        `plot_pair(X, 'emb_mean_euclidean', 'emb_mean_cosine')`

    Args:
        df:
        feature_name_1: The name of the first feature.
        feature_name_2: The name of the second feature.
        kind: One of the values { 'scatter' | 'reg' | 'resid' | 'kde' | 'hex' }.
        alpha: Alpha channel value.
        **kwargs: Additional argument to 'sns.jointplot'.
    """

    plt.figure()
    sns.jointplot(
        feature_name_1,
        feature_name_2,
        df,
        alpha=alpha,
        kind=kind,
        **kwargs
    )
    plt.show()