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Figure-level interface for drawing relational plots onto a FacetGrid. |
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Draw a scatter plot with possibility of several semantic groupings. |
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Draw a line plot with possibility of several semantic groupings. |
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Figure-level interface for drawing categorical plots onto a |
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Draw a scatterplot where one variable is categorical. |
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Draw a categorical scatterplot with non-overlapping points. |
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Draw a box plot to show distributions with respect to categories. |
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Draw a combination of boxplot and kernel density estimate. |
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Draw an enhanced box plot for larger datasets. |
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Show point estimates and confidence intervals using scatter plot glyphs. |
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Show point estimates and confidence intervals as rectangular bars. |
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Show the counts of observations in each categorical bin using bars. |
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Flexibly plot a univariate distribution of observations. |
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Fit and plot a univariate or bivariate kernel density estimate. |
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Plot datapoints in an array as sticks on an axis. |
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Plot data and regression model fits across a FacetGrid. |
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Plot data and a linear regression model fit. |
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Plot the residuals of a linear regression. |
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Plot rectangular data as a color-encoded matrix. |
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Plot a matrix dataset as a hierarchically-clustered heatmap. |
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Multi-plot grid for plotting conditional relationships. |
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Apply a plotting function to each facet’s subset of the data. |
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Like |
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Plot pairwise relationships in a dataset. |
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Subplot grid for plotting pairwise relationships in a dataset. |
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Plot with the same function in every subplot. |
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Plot with a univariate function on each diagonal subplot. |
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Plot with a bivariate function on the off-diagonal subplots. |
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Plot with a bivariate function on the lower diagonal subplots. |
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Plot with a bivariate function on the upper diagonal subplots. |
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Draw a plot of two variables with bivariate and univariate graphs. |
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Grid for drawing a bivariate plot with marginal univariate plots. |
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Shortcut to draw the full plot. |
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Draw a bivariate plot of x and y. |
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Draw univariate plots for x and y separately. |
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Set aesthetic parameters in one step. |
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Return a parameter dict for the aesthetic style of the plots. |
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Set the aesthetic style of the plots. |
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Return a parameter dict to scale elements of the figure. |
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Set the plotting context parameters. |
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Change how matplotlib color shorthands are interpreted. |
Restore all RC params to default settings. |
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Restore all RC params to original settings (respects custom rc). |
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Set the matplotlib color cycle using a seaborn palette. |
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Return a list of colors defining a color palette. |
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Get a set of evenly spaced colors in HUSL hue space. |
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Get a set of evenly spaced colors in HLS hue space. |
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Make a sequential palette from the cubehelix system. |
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Make a sequential palette that blends from dark to |
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Make a sequential palette that blends from light to |
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Make a diverging palette between two HUSL colors. |
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Make a palette that blends between a list of colors. |
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Make a palette with color names from the xkcd color survey. |
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Make a palette with color names from Crayola crayons. |
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Return discrete colors from a matplotlib palette. |
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Select a palette from the ColorBrewer set. |
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Launch an interactive widget to create a sequential cubehelix palette. |
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Launch an interactive widget to create a light sequential palette. |
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Launch an interactive widget to create a dark sequential palette. |
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Launch an interactive widget to choose a diverging color palette. |
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Load an example dataset from the online repository (requires internet). |
Report available example datasets, useful for reporting issues. |
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Return a path to the cache directory for example datasets. |
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Remove the top and right spines from plot(s). |
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Decrease the saturation channel of a color by some percent. |
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Return a fully saturated color with the same hue. |
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Independently manipulate the h, l, or s channels of a color. |