Seaborn

Seaborn-05-Pairplot多变量图

seaborn.pairplot

 

fit_reg
If True, estimate and plot a regression model relating the x and y variables.

import seaborn as sns
# sns.set(style="darkgrid")
g = sns.lmplot(
    data=code_origin,
    x="true", y="predict", fit_reg=False
)
ax = plt.gca()
def annotate(data, **kws):
    # ax.text(.05, .9, 'R2={:.2f}'.format(score_pipe["R2"]),
    #         transform=ax.transAxes)
    ax.text(.05, .9, r'$R^2={:.2f}$'.format(score_pipe["R2"]),
            transform=ax.transAxes)
g.map_dataframe(annotate)
g.set_axis_labels("Real value", "Predicted value")
axes = g.fig.axes
for ax in axes:
    ax.plot(code_origin['true'], code_origin['true'], C='k', linewidth=1, linestyle='--')