| gofplots.qqplot(data[, dist, distargs, a, ...]) | qqplot of the quantiles of x versus the quantiles/ppf of a distribution. |
| gofplots.qqline(ax, line[, x, y, dist, fmt]) | Plot a reference line for a qqplot. |
| boxplots.violinplot(data[, ax, labels, ...]) | Make a violin plot of each dataset in the data sequence. |
| boxplots.beanplot(data[, ax, labels, ...]) | Make a bean plot of each dataset in the data sequence. |
| correlation.plot_corr(dcorr[, xnames, ...]) | Plot correlation of many variables in a tight color grid. |
| correlation.plot_corr_grid(dcorrs[, titles, ...]) | Create a grid of correlation plots. |
| plot_grids.scatter_ellipse(data[, level, ...]) | Create a grid of scatter plots with confidence ellipses. |
| functional.fboxplot(data[, xdata, labels, ...]) | Plot functional boxplot. |
| functional.rainbowplot(data[, xdata, depth, ...]) | Create a rainbow plot for a set of curves. |
| functional.banddepth(data[, method]) | Calculate the band depth for a set of functional curves. |
| regressionplots.plot_fit(res, exog_idx[, ...]) | Plot fit against one regressor. |
| regressionplots.plot_regress_exog(res, exog_idx) | Plot regression results against one regressor. |
| regressionplots.plot_partregress(endog, exog) | Plot partial regression for a set of regressors. |
| regressionplots.plot_ccpr(res[, exog_idx, ...]) | Generate CCPR plots against a set of regressors, plot in a grid. |
| tsaplots.plotacf(corr[, ax, lags, use_vlines]) | Plot the auto or cross correlation. |
| factorplots.interaction_plot(x, trace, response) | Interaction plot for factor level statistics |