# Graphics¶

## Goodness of Fit Plots¶

 `qqplot`(data[, dist, distargs, a, loc, ...]) Q-Q plot of the quantiles of x versus the quantiles/ppf of a distribution. `qqline`(ax, line[, x, y, dist, fmt]) Plot a reference line for a qqplot. `qqplot_2samples`(data1, data2[, xlabel, ...]) Q-Q Plot of two samples' quantiles. `ProbPlot`(data[, dist, fit, distargs, a, ...]) Q-Q and P-P Probability Plots

## Boxplots¶

 `violinplot`(data[, ax, labels, positions, ...]) Make a violin plot of each dataset in the data sequence. `beanplot`(data[, ax, labels, positions, ...]) Bean plot of each dataset in a sequence.

## Correlation Plots¶

 `plot_corr`(dcorr[, xnames, ynames, title, ...]) Plot correlation of many variables in a tight color grid. `plot_corr_grid`(dcorrs[, titles, ncols, ...]) Create a grid of correlation plots.
 `scatter_ellipse`(data[, level, varnames, ...]) Create a grid of scatter plots with confidence ellipses.

## Dot Plots¶

 `dot_plot`(points[, intervals, lines, ...]) Dot plotting (also known as forest and blobbogram).

## Functional Plots¶

 `hdrboxplot`(data[, ncomp, alpha, threshold, ...]) High Density Region boxplot `fboxplot`(data[, xdata, labels, depth, ...]) Plot functional boxplot. `rainbowplot`(data[, xdata, depth, method, ...]) Create a rainbow plot for a set of curves. `banddepth`(data[, method]) Calculate the band depth for a set of functional curves.

## Regression Plots¶

 `plot_fit`(results, exog_idx[, y_true, ax, vlines]) Plot fit against one regressor. `plot_regress_exog`(results, exog_idx[, fig]) Plot regression results against one regressor. `plot_partregress`(endog, exog_i, exog_others) Plot partial regression for a single regressor. `plot_partregress_grid`(results[, exog_idx, ...]) Plot partial regression for a set of regressors. `plot_ccpr`(results, exog_idx[, ax]) Plot CCPR against one regressor. `plot_ccpr_grid`(results[, exog_idx, grid, fig]) Generate CCPR plots against a set of regressors, plot in a grid. `plot_ceres_residuals`(results, focus_exog[, ...]) Conditional Expectation Partial Residuals (CERES) plot. `abline_plot`([intercept, slope, horiz, vert, ...]) Plot a line given an intercept and slope. `influence_plot`(results[, external, alpha, ...]) Plot of influence in regression. `plot_leverage_resid2`(results[, alpha, ax]) Plot leverage statistics vs.

## Time Series Plots¶

 `plot_acf`(x[, ax, lags, alpha, use_vlines, ...]) Plot the autocorrelation function `plot_pacf`(x[, ax, lags, alpha, method, ...]) Plot the partial autocorrelation function `month_plot`(x[, dates, ylabel, ax]) Seasonal plot of monthly data. `quarter_plot`(x[, dates, ylabel, ax]) Seasonal plot of quarterly data

## Other Plots¶

 `interaction_plot`(x, trace, response[, func, ...]) Interaction plot for factor level statistics.
 `mosaic`(data[, index, ax, horizontal, gap, ...]) Create a mosaic plot from a contingency table.
 `mean_diff_plot`(m1, m2[, sd_limit, ax, ...]) Construct a Tukey/Bland-Altman Mean Difference Plot.

Last update: Dec 14, 2023