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nvim_config/typings/seaborn/categorical.pyi

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"""
This type stub file was generated by pyright.
"""
from ._decorators import _deprecate_positional_args
__all__ = ["catplot", "factorplot", "stripplot", "swarmplot", "boxplot", "violinplot", "boxenplot", "pointplot", "barplot", "countplot"]
class _CategoricalPlotter:
width = ...
default_palette = ...
require_numeric = ...
def establish_variables(self, x=..., y=..., hue=..., data=..., orient=..., order=..., hue_order=..., units=...):
"""Convert input specification into a common representation."""
...
def establish_colors(self, color, palette, saturation): # -> None:
"""Get a list of colors for the main component of the plots."""
...
@property
def hue_offsets(self): # -> Any | NDArray[float64]:
"""A list of center positions for plots when hue nesting is used."""
...
@property
def nested_width(self): # -> float:
"""A float with the width of plot elements when hue nesting is used."""
...
def annotate_axes(self, ax): # -> None:
"""Add descriptive labels to an Axes object."""
...
def add_legend_data(self, ax, color, label): # -> None:
"""Add a dummy patch object so we can get legend data."""
...
class _BoxPlotter(_CategoricalPlotter):
def __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth) -> None:
...
def draw_boxplot(self, ax, kws): # -> None:
"""Use matplotlib to draw a boxplot on an Axes."""
...
def restyle_boxplot(self, artist_dict, color, props): # -> None:
"""Take a drawn matplotlib boxplot and make it look nice."""
...
def plot(self, ax, boxplot_kws): # -> None:
"""Make the plot."""
...
class _ViolinPlotter(_CategoricalPlotter):
def __init__(self, x, y, hue, data, order, hue_order, bw, cut, scale, scale_hue, gridsize, width, inner, split, dodge, orient, linewidth, color, palette, saturation) -> None:
...
def estimate_densities(self, bw, cut, scale, scale_hue, gridsize): # -> None:
"""Find the support and density for all of the data."""
...
def fit_kde(self, x, bw): # -> tuple[gaussian_kde, Unknown]:
"""Estimate a KDE for a vector of data with flexible bandwidth."""
...
def kde_support(self, x, bw, cut, gridsize):
"""Define a grid of support for the violin."""
...
def scale_area(self, density, max_density, scale_hue): # -> None:
"""Scale the relative area under the KDE curve.
This essentially preserves the "standard" KDE scaling, but the
resulting maximum density will be 1 so that the curve can be
properly multiplied by the violin width.
"""
...
def scale_width(self, density): # -> None:
"""Scale each density curve to the same height."""
...
def scale_count(self, density, counts, scale_hue): # -> None:
"""Scale each density curve by the number of observations."""
...
@property
def dwidth(self):
...
def draw_violins(self, ax): # -> None:
"""Draw the violins onto `ax`."""
...
def draw_single_observation(self, ax, at_group, at_quant, density): # -> None:
"""Draw a line to mark a single observation."""
...
def draw_box_lines(self, ax, data, support, density, center): # -> None:
"""Draw boxplot information at center of the density."""
...
def draw_quartiles(self, ax, data, support, density, center, split=...): # -> None:
"""Draw the quartiles as lines at width of density."""
...
def draw_points(self, ax, data, center): # -> None:
"""Draw individual observations as points at middle of the violin."""
...
def draw_stick_lines(self, ax, data, support, density, center, split=...): # -> None:
"""Draw individual observations as sticks at width of density."""
...
def draw_to_density(self, ax, center, val, support, density, split, **kws): # -> None:
"""Draw a line orthogonal to the value axis at width of density."""
...
def plot(self, ax): # -> None:
"""Make the violin plot."""
...
class _CategoricalScatterPlotter(_CategoricalPlotter):
default_palette = ...
require_numeric = ...
@property
def point_colors(self): # -> list[Unknown]:
"""Return an index into the palette for each scatter point."""
...
def add_legend_data(self, ax): # -> None:
"""Add empty scatterplot artists with labels for the legend."""
...
class _StripPlotter(_CategoricalScatterPlotter):
"""1-d scatterplot with categorical organization."""
def __init__(self, x, y, hue, data, order, hue_order, jitter, dodge, orient, color, palette) -> None:
"""Initialize the plotter."""
...
def draw_stripplot(self, ax, kws): # -> None:
"""Draw the points onto `ax`."""
...
def plot(self, ax, kws): # -> None:
"""Make the plot."""
...
class _SwarmPlotter(_CategoricalScatterPlotter):
def __init__(self, x, y, hue, data, order, hue_order, dodge, orient, color, palette) -> None:
"""Initialize the plotter."""
...
def could_overlap(self, xy_i, swarm, d): # -> NDArray[Unknown]:
"""Return a list of all swarm points that could overlap with target.
Assumes that swarm is a sorted list of all points below xy_i.
"""
...
def position_candidates(self, xy_i, neighbors, d): # -> NDArray[Unknown]:
"""Return a list of (x, y) coordinates that might be valid."""
...
def first_non_overlapping_candidate(self, candidates, neighbors, d):
"""Remove candidates from the list if they overlap with the swarm."""
...
def beeswarm(self, orig_xy, d): # -> NDArray[Unknown]:
"""Adjust x position of points to avoid overlaps."""
...
def add_gutters(self, points, center, width):
"""Stop points from extending beyond their territory."""
...
def swarm_points(self, ax, points, center, width, s, **kws): # -> None:
"""Find new positions on the categorical axis for each point."""
...
def draw_swarmplot(self, ax, kws): # -> None:
"""Plot the data."""
...
def plot(self, ax, kws): # -> None:
"""Make the full plot."""
...
class _CategoricalStatPlotter(_CategoricalPlotter):
require_numeric = ...
@property
def nested_width(self): # -> float:
"""A float with the width of plot elements when hue nesting is used."""
...
def estimate_statistic(self, estimator, ci, n_boot, seed): # -> None:
...
def draw_confints(self, ax, at_group, confint, colors, errwidth=..., capsize=..., **kws): # -> None:
...
class _BarPlotter(_CategoricalStatPlotter):
"""Show point estimates and confidence intervals with bars."""
def __init__(self, x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, seed, orient, color, palette, saturation, errcolor, errwidth, capsize, dodge) -> None:
"""Initialize the plotter."""
...
def draw_bars(self, ax, kws): # -> None:
"""Draw the bars onto `ax`."""
...
def plot(self, ax, bar_kws): # -> None:
"""Make the plot."""
...
class _PointPlotter(_CategoricalStatPlotter):
default_palette = ...
def __init__(self, x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, seed, markers, linestyles, dodge, join, scale, orient, color, palette, errwidth=..., capsize=...) -> None:
"""Initialize the plotter."""
...
@property
def hue_offsets(self): # -> NDArray[float64]:
"""Offsets relative to the center position for each hue level."""
...
def draw_points(self, ax): # -> None:
"""Draw the main data components of the plot."""
...
def plot(self, ax): # -> None:
"""Make the plot."""
...
class _CountPlotter(_BarPlotter):
require_numeric = ...
class _LVPlotter(_CategoricalPlotter):
def __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, k_depth, linewidth, scale, outlier_prop, trust_alpha, showfliers=...) -> None:
...
def draw_letter_value_plot(self, ax, kws): # -> None:
"""Use matplotlib to draw a letter value plot on an Axes."""
...
def plot(self, ax, boxplot_kws): # -> None:
"""Make the plot."""
...
_categorical_docs = ...
@_deprecate_positional_args
def boxplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., orient=..., color=..., palette=..., saturation=..., width=..., dodge=..., fliersize=..., linewidth=..., whis=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def violinplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., bw=..., cut=..., scale=..., scale_hue=..., gridsize=..., width=..., inner=..., split=..., dodge=..., orient=..., linewidth=..., color=..., palette=..., saturation=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def boxenplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., orient=..., color=..., palette=..., saturation=..., width=..., dodge=..., k_depth=..., linewidth=..., scale=..., outlier_prop=..., trust_alpha=..., showfliers=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def stripplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., jitter=..., dodge=..., orient=..., color=..., palette=..., size=..., edgecolor=..., linewidth=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def swarmplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., dodge=..., orient=..., color=..., palette=..., size=..., edgecolor=..., linewidth=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def barplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., estimator=..., ci=..., n_boot=..., units=..., seed=..., orient=..., color=..., palette=..., saturation=..., errcolor=..., errwidth=..., capsize=..., dodge=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def pointplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., estimator=..., ci=..., n_boot=..., units=..., seed=..., markers=..., linestyles=..., dodge=..., join=..., scale=..., orient=..., color=..., palette=..., errwidth=..., capsize=..., ax=..., **kwargs): # -> Axes:
...
@_deprecate_positional_args
def countplot(*, x=..., y=..., hue=..., data=..., order=..., hue_order=..., orient=..., color=..., palette=..., saturation=..., dodge=..., ax=..., **kwargs): # -> Axes:
...
def factorplot(*args, **kwargs):
"""Deprecated; please use `catplot` instead."""
...
@_deprecate_positional_args
def catplot(*, x=..., y=..., hue=..., data=..., row=..., col=..., col_wrap=..., estimator=..., ci=..., n_boot=..., units=..., seed=..., order=..., hue_order=..., row_order=..., col_order=..., kind=..., height=..., aspect=..., orient=..., color=..., palette=..., legend=..., legend_out=..., sharex=..., sharey=..., margin_titles=..., facet_kws=..., **kwargs):
...