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API Manual
Seaborn API Manual
Class(3)
Method(13)
Function(52)
Sample(160)
Guide(144)
Class
seaborn.FacetGrid
seaborn.JointGrid
seaborn.PairGrid
Method
seaborn.FacetGrid.__init__
seaborn.FacetGrid.map
seaborn.FacetGrid.map_dataframe
seaborn.JointGrid.__init__
seaborn.JointGrid.plot
seaborn.JointGrid.plot_joint
seaborn.JointGrid.plot_marginals
seaborn.PairGrid.__init__
seaborn.PairGrid.map
seaborn.PairGrid.map_diag
seaborn.PairGrid.map_lower
seaborn.PairGrid.map_offdiag
seaborn.PairGrid.map_upper
Function
seaborn.axes_style
seaborn.barplot
seaborn.blend_palette
seaborn.boxenplot
seaborn.boxplot
seaborn.catplot
seaborn.choose_colorbrewer_palette
seaborn.choose_cubehelix_palette
seaborn.choose_dark_palette
seaborn.choose_diverging_palette
seaborn.choose_light_palette
seaborn.clustermap
seaborn.color_palette
seaborn.countplot
seaborn.crayon_palette
seaborn.cubehelix_palette
seaborn.dark_palette
seaborn.desaturate
seaborn.despine
seaborn.distplot
seaborn.diverging_palette
seaborn.heatmap
seaborn.hls_palette
seaborn.husl_palette
seaborn.jointplot
seaborn.kdeplot
seaborn.light_palette
seaborn.lineplot
seaborn.lmplot
seaborn.load_dataset
seaborn.mpl_palette
seaborn.pairplot
seaborn.plotting_context
seaborn.pointplot
seaborn.regplot
seaborn.relplot
seaborn.reset_defaults
seaborn.reset_orig
seaborn.residplot
seaborn.rugplot
seaborn.saturate
seaborn.scatterplot
seaborn.set
seaborn.set_color_codes
seaborn.set_context
seaborn.set_hls_values
seaborn.set_palette
seaborn.set_style
seaborn.stripplot
seaborn.swarmplot
seaborn.violinplot
seaborn.xkcd_palette
Sample
clustermap - Discovering structure in heatmap data
kdeplot - Different cubehelix palettes
PairGrid - Paired categorical plots
FacetGrid - Overlapping densities (��ridge plot')
scatterplot - Scatterplot with continuous hues and sizes
FacetGrid - Plotting on a large number of facets
stripplot - Conditional means with observations
residplot - Plotting model residuals
jointplot - Joint kernel density estimate
barplot - Horizontal bar plots
swarmplot - Scatterplot with categorical variables
JointGrid - Scatterplot with marginal ticks
violinplot - Violinplot from a wide-form dataset
violinplot - Grouped violinplots with split violins
scatterplot - Scatterplot with categorical and numerical semantics
heatmap - Plotting a diagonal correlation matrix
jointplot - Hexbin plot with marginal distributions
boxplot - Grouped boxplots
FacetGrid - Facetting histograms by subsets of data
PairGrid - Dot plot with several variables
catplot - Grouped barplots
jointplot - Linear regression with marginal distributions
lmplot - Faceted logistic regression
lineplot - Timeseries plot with error bands
catplot - Plotting a three-way ANOVA
PairGrid - Paired density and scatterplot matrix
kdeplot - Multiple bivariate KDE plots
heatmap - Annotated heatmaps
pairplot - Scatterplot Matrix
lineplot - Lineplot from a wide-form dataset
lmplot - Anscombe's quartet
FacetGrid - FacetGrid with custom projection
distplot - Distribution plot options
violinplot - Violinplots with observations
barplot - Color palette choices
boxplot - Horizontal boxplot with observations
lmplot - Multiple linear regression
relplot - Scatterplot with varying point sizes and hues
boxenplot - Plotting large distributions
relplot - Line plots on multiple facets
clustermap - Discovering structure in heatmap data
kdeplot - Different cubehelix palettes
PairGrid - Paired categorical plots
FacetGrid - Overlapping densities (��ridge plot')
scatterplot - Scatterplot with continuous hues and sizes
FacetGrid - Plotting on a large number of facets
stripplot - Conditional means with observations
residplot - Plotting model residuals
jointplot - Joint kernel density estimate
barplot - Horizontal bar plots
swarmplot - Scatterplot with categorical variables
JointGrid - Scatterplot with marginal ticks
violinplot - Violinplot from a wide-form dataset
violinplot - Grouped violinplots with split violins
scatterplot - Scatterplot with categorical and numerical semantics
heatmap - Plotting a diagonal correlation matrix
jointplot - Hexbin plot with marginal distributions
boxplot - Grouped boxplots
FacetGrid - Facetting histograms by subsets of data
PairGrid - Dot plot with several variables
catplot - Grouped barplots
jointplot - Linear regression with marginal distributions
lmplot - Faceted logistic regression
lineplot - Timeseries plot with error bands
catplot - Plotting a three-way ANOVA
PairGrid - Paired density and scatterplot matrix
kdeplot - Multiple bivariate KDE plots
heatmap - Annotated heatmaps
pairplot - Scatterplot Matrix
lineplot - Lineplot from a wide-form dataset
lmplot - Anscombe's quartet
FacetGrid - FacetGrid with custom projection
distplot - Distribution plot options
violinplot - Violinplots with observations
barplot - Color palette choices
boxplot - Horizontal boxplot with observations
lmplot - Multiple linear regression
relplot - Scatterplot with varying point sizes and hues
boxenplot - Plotting large distributions
relplot - Line plots on multiple facets
clustermap - Discovering structure in heatmap data
kdeplot - Different cubehelix palettes
PairGrid - Paired categorical plots
FacetGrid - Overlapping densities (��ridge plot')
scatterplot - Scatterplot with continuous hues and sizes
FacetGrid - Plotting on a large number of facets
stripplot - Conditional means with observations
residplot - Plotting model residuals
jointplot - Joint kernel density estimate
barplot - Horizontal bar plots
swarmplot - Scatterplot with categorical variables
JointGrid - Scatterplot with marginal ticks
violinplot - Violinplot from a wide-form dataset
violinplot - Grouped violinplots with split violins
scatterplot - Scatterplot with categorical and numerical semantics
heatmap - Plotting a diagonal correlation matrix
jointplot - Hexbin plot with marginal distributions
boxplot - Grouped boxplots
FacetGrid - Facetting histograms by subsets of data
PairGrid - Dot plot with several variables
catplot - Grouped barplots
jointplot - Linear regression with marginal distributions
lmplot - Faceted logistic regression
lineplot - Timeseries plot with error bands
catplot - Plotting a three-way ANOVA
PairGrid - Paired density and scatterplot matrix
kdeplot - Multiple bivariate KDE plots
heatmap - Annotated heatmaps
pairplot - Scatterplot Matrix
lineplot - Lineplot from a wide-form dataset
lmplot - Anscombe's quartet
FacetGrid - FacetGrid with custom projection
distplot - Distribution plot options
violinplot - Violinplots with observations
barplot - Color palette choices
boxplot - Horizontal boxplot with observations
lmplot - Multiple linear regression
relplot - Scatterplot with varying point sizes and hues
boxenplot - Plotting large distributions
relplot - Line plots on multiple facets
clustermap - Discovering structure in heatmap data
kdeplot - Different cubehelix palettes
PairGrid - Paired categorical plots
FacetGrid - Overlapping densities (��ridge plot')
scatterplot - Scatterplot with continuous hues and sizes
FacetGrid - Plotting on a large number of facets
stripplot - Conditional means with observations
residplot - Plotting model residuals
jointplot - Joint kernel density estimate
barplot - Horizontal bar plots
swarmplot - Scatterplot with categorical variables
JointGrid - Scatterplot with marginal ticks
violinplot - Violinplot from a wide-form dataset
violinplot - Grouped violinplots with split violins
scatterplot - Scatterplot with categorical and numerical semantics
heatmap - Plotting a diagonal correlation matrix
jointplot - Hexbin plot with marginal distributions
boxplot - Grouped boxplots
FacetGrid - Facetting histograms by subsets of data
PairGrid - Dot plot with several variables
catplot - Grouped barplots
jointplot - Linear regression with marginal distributions
lmplot - Faceted logistic regression
lineplot - Timeseries plot with error bands
catplot - Plotting a three-way ANOVA
PairGrid - Paired density and scatterplot matrix
kdeplot - Multiple bivariate KDE plots
heatmap - Annotated heatmaps
pairplot - Scatterplot Matrix
lineplot - Lineplot from a wide-form dataset
lmplot - Anscombe's quartet
FacetGrid - FacetGrid with custom projection
distplot - Distribution plot options
violinplot - Violinplots with observations
barplot - Color palette choices
boxplot - Horizontal boxplot with observations
lmplot - Multiple linear regression
relplot - Scatterplot with varying point sizes and hues
boxenplot - Plotting large distributions
relplot - Line plots on multiple facets
Guide
Visualizing statistical relationships
Relating variables with scatter plots
Emphasizing continuity with line plots
Showing multiple relationships with facets
Plotting with categorical data
Categorical scatterplots
Distributions of observations within categories
Statistical estimation within categories
Plotting ��wide-form�� data
Showing multiple relationships with facets
Visualizing the distribution of a dataset
Plotting univariate distributions
Plotting bivariate distributions
Visualizing pairwise relationships in a dataset
Visualizing linear relationships
Functions to draw linear regression models
Fitting different kinds of models
Conditioning on other variables
Controlling the size and shape of the plot
Plotting a regression in other contexts
Building structured multi-plot grids
Conditional small multiples
Using custom functions
Plotting pairwise data relationships
Controlling figure aesthetics
Seaborn figure styles
Removing axes spines
Temporarily setting figure style
Overriding elements of the seaborn styles
Scaling plot elements
Choosing color palettes
Building color palettes
Qualitative color palettes
Sequential color palettes
Diverging color palettes
Setting the default color palette
Visualizing statistical relationships
Relating variables with scatter plots
Emphasizing continuity with line plots
Showing multiple relationships with facets
Plotting with categorical data
Categorical scatterplots
Distributions of observations within categories
Statistical estimation within categories
Plotting ��wide-form�� data
Showing multiple relationships with facets
Visualizing the distribution of a dataset
Plotting univariate distributions
Plotting bivariate distributions
Visualizing pairwise relationships in a dataset
Visualizing linear relationships
Functions to draw linear regression models
Fitting different kinds of models
Conditioning on other variables
Controlling the size and shape of the plot
Plotting a regression in other contexts
Building structured multi-plot grids
Conditional small multiples
Using custom functions
Plotting pairwise data relationships
Controlling figure aesthetics
Seaborn figure styles
Removing axes spines
Temporarily setting figure style
Overriding elements of the seaborn styles
Scaling plot elements
Choosing color palettes
Building color palettes
Qualitative color palettes
Sequential color palettes
Diverging color palettes
Setting the default color palette
Visualizing statistical relationships
Relating variables with scatter plots
Emphasizing continuity with line plots
Showing multiple relationships with facets
Plotting with categorical data
Categorical scatterplots
Distributions of observations within categories
Statistical estimation within categories
Plotting ��wide-form�� data
Showing multiple relationships with facets
Visualizing the distribution of a dataset
Plotting univariate distributions
Plotting bivariate distributions
Visualizing pairwise relationships in a dataset
Visualizing linear relationships
Functions to draw linear regression models
Fitting different kinds of models
Conditioning on other variables
Controlling the size and shape of the plot
Plotting a regression in other contexts
Building structured multi-plot grids
Conditional small multiples
Using custom functions
Plotting pairwise data relationships
Controlling figure aesthetics
Seaborn figure styles
Removing axes spines
Temporarily setting figure style
Overriding elements of the seaborn styles
Scaling plot elements
Choosing color palettes
Building color palettes
Qualitative color palettes
Sequential color palettes
Diverging color palettes
Setting the default color palette
Visualizing statistical relationships
Relating variables with scatter plots
Emphasizing continuity with line plots
Showing multiple relationships with facets
Plotting with categorical data
Categorical scatterplots
Distributions of observations within categories
Statistical estimation within categories
Plotting ��wide-form�� data
Showing multiple relationships with facets
Visualizing the distribution of a dataset
Plotting univariate distributions
Plotting bivariate distributions
Visualizing pairwise relationships in a dataset
Visualizing linear relationships
Functions to draw linear regression models
Fitting different kinds of models
Conditioning on other variables
Controlling the size and shape of the plot
Plotting a regression in other contexts
Building structured multi-plot grids
Conditional small multiples
Using custom functions
Plotting pairwise data relationships
Controlling figure aesthetics
Seaborn figure styles
Removing axes spines
Temporarily setting figure style
Overriding elements of the seaborn styles
Scaling plot elements
Choosing color palettes
Building color palettes
Qualitative color palettes
Sequential color palettes
Diverging color palettes
Setting the default color palette
Method
Function
Sample
Guide
Class(3)
Method(13)
Function(52)
Sample(160)
Guide(144)
Class