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.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.hdrboxplot`(data[, ncomp, alpha, …])	High Density Region boxplot
`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`(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_partregress_grid`(results)	Plot partial regression for a set of regressors.
`regressionplots.plot_ccpr`(results, exog_idx)	Plot CCPR against one regressor.
`regressionplots.plot_ccpr_grid`(results[, …])	Generate CCPR plots against a set of regressors, plot in a grid.
`regressionplots.plot_ceres_residuals`(…[, …])	Produces a CERES (Conditional Expectation Partial Residuals) plot for a fitted regression model.
`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.

`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

`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.
`agreement.mean_diff_plot`(m1, m2[, sd_limit, …])	Tukey’s Mean Difference Plot.