Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. For a brief introduction to …

If you’re working in a Jupyter notebook or an IPython terminal with matplotlib mode enabled, you should immediately see the plot. Otherwise, you may need to explicitly call …

Seaborn is a library for making statistical graphics in Python. It builds on top of matplotlib and integrates closely with pandas data structures. Seaborn helps you explore and understand …

Example gallery#. lmplot. scatterplot

The seaborn.objects interface. Specifying a plot and mapping data; Transforming data before plotting; Building and displaying the plot; Customizing the appearance

ax matplotlib.axes.Axes. Pre-existing axes for the plot. Otherwise, call matplotlib.pyplot.gca() internally. kwargs. Other keyword arguments are passed to one of the following matplotlib …

Set aspects of the visual theme for all matplotlib and seaborn plots. This function changes the global defaults for all plots using the matplotlib rcParams system. The themeing is …

Customize the plot using parameters of the underlying matplotlib function: sns . boxplot ( data = titanic , x = "age" , y = "class" , notch = True , showcaps = False , flierprops = { "marker" : "x" }, …

seaborn. pairplot (data, *, hue = None, hue_order = None, palette = None, vars = None, x_vars = None, y_vars = None, kind = 'scatter', diag_kind = 'auto', markers = None, height = 2.5, aspect …

seaborn.clustermap# seaborn. clustermap ( data , * , pivot_kws = None , method = 'average' , metric = 'euclidean' , z_score = None , standard_scale = None , figsize = (10, 10) , cbar_kws = …