July 2016
Beginner to intermediate
462 pages
9h 14m
English
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Seaborn
The following argument plots a univariate distribution of observations:
seaborn.distplot(a, bins=None, hist=True, kde=True, rug=False, fit=None, hist_kws=None, kde_kws=None, rug_kws=None, fit_kws=None, color=None, vertical=False, norm_hist=False, axlabel=None, label=None, ax=None)
The following argument plots tabular data as a color-encoded matrix:
seaborn.heatmap(data, vmin=None, vmax=None, cmap=None, center=None, robust=False, annot=False, fmt='.2g', annot_kws=None, linewidths=0, linecolor='white', cbar=True, cbar_kws=None, cbar_ax=None, square=False, ax=None, xticklabels=True, yticklabels=True, mask=None, **kwargs)
The following argument plots data and the corresponding linear regression model fit:
seaborn.regplot(x, y, data=None, x_estimator=None, ...