/Statsmodels

# Graphics

## Goodness of Fit Plots

 gofplots.qqplot(data[, dist, distargs, a, ...]) Q-Q plot 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. gofplots.qqplot_2samples(data1, data2[, ...]) Q-Q Plot of two samples’ quantiles. gofplots.ProbPlot(data[, dist, fit, ...]) Class for convenient construction of Q-Q, P-P, and probability plots.

## Boxplots

 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 Plots

 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 Plots

 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.

## Regression Plots

 regressionplots.plot_fit(results, exog_idx) Plot fit against one regressor. regressionplots.plot_regress_exog(results, ...) Plot regression results against one regressor. regressionplots.plot_partregress(endog, ...) Plot partial regression for a single regressor. regressionplots.plot_ccpr(results, exog_idx) Plot CCPR against one regressor. regressionplots.abline_plot([intercept, ...]) Plots a line given an intercept and slope. regressionplots.influence_plot(results[, ...]) Plot of influence in regression. regressionplots.plot_leverage_resid2(results) Plots leverage statistics vs.

## Time Series Plots

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

## Other Plots

 factorplots.interaction_plot(x, trace, response) Interaction plot for factor level statistics. mosaicplot.mosaic(data[, index, ax, ...]) Create a mosaic plot from a contingency table.