drippy.onefactor
================

.. py:module:: drippy.onefactor

.. autoapi-nested-parse::

   Plotting functions for 1-factor models (y = f(x) + e, x categorical).



Attributes
----------

.. autoapisummary::

   drippy.onefactor._FACTOR_LEVEL


Functions
---------

.. autoapisummary::

   drippy.onefactor.scatter_plot
   drippy.onefactor.box_plot
   drippy.onefactor.bihistogram
   drippy.onefactor.qq_plot
   drippy.onefactor.mean_plot
   drippy.onefactor.sd_plot


Module Contents
---------------

.. py:data:: _FACTOR_LEVEL
   :value: 'Factor Level'


.. py:function:: scatter_plot(data: drippy.data.EDAData, fig: matplotlib.figure.Figure | None = None, ax: matplotlib.axes.Axes | None = None) -> tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

   Creates a scatter plot of y vs x.

   Also used in regression context (see drippy.regression).

   :param data: EDAData container. Requires x.
   :param fig: Matplotlib figure. If None, creates new figure.
   :param ax: Matplotlib axes. If None, creates new axes.

   :returns: The figure and axes containing the plot.


.. py:function:: box_plot(data: drippy.data.EDAData, fig: matplotlib.figure.Figure | None = None, ax: matplotlib.axes.Axes | None = None) -> tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

   Creates a box plot of y grouped by factor levels in x.

   :param data: EDAData container. Requires x (categorical).
   :param fig: Matplotlib figure. If None, creates new figure.
   :param ax: Matplotlib axes. If None, creates new axes.

   :returns: The figure and axes containing the plot.


.. py:function:: bihistogram(data: drippy.data.EDAData, fig: matplotlib.figure.Figure | None = None, axes: numpy.ndarray | None = None, bins: int | str = 'auto') -> tuple[matplotlib.figure.Figure, numpy.ndarray]

   Creates side-by-side histograms for exactly 2 factor levels.

   :param data: EDAData container. Requires x with exactly 2 unique levels.
   :param fig: Matplotlib figure. If None, creates new figure.
   :param axes: Array of 2 Axes. If None, creates new axes.
   :param bins: Number of bins or bin strategy.

   :returns: (fig, axes) where axes is a 1-D array of 2 Axes.


.. py:function:: qq_plot(data: drippy.data.EDAData, fig: matplotlib.figure.Figure | None = None, ax: matplotlib.axes.Axes | None = None) -> tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

   Creates a quantile-quantile plot comparing 2 factor level distributions.

   :param data: EDAData container. Requires x with exactly 2 unique levels.
   :param fig: Matplotlib figure. If None, creates new figure.
   :param ax: Matplotlib axes. If None, creates new axes.

   :returns: The figure and axes containing the plot.


.. py:function:: mean_plot(data: drippy.data.EDAData, fig: matplotlib.figure.Figure | None = None, ax: matplotlib.axes.Axes | None = None) -> tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

   Creates a mean plot of y grouped by factor levels in x.

   Shows group means connected by a line, with a horizontal grand mean.

   :param data: EDAData container. Requires x.
   :param fig: Matplotlib figure. If None, creates new figure.
   :param ax: Matplotlib axes. If None, creates new axes.

   :returns: The figure and axes containing the plot.


.. py:function:: sd_plot(data: drippy.data.EDAData, fig: matplotlib.figure.Figure | None = None, ax: matplotlib.axes.Axes | None = None) -> tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

   Creates a standard deviation plot of y grouped by factor levels in x.

   Shows group standard deviations connected by a line, with a horizontal
   overall standard deviation reference line.

   :param data: EDAData container. Requires x.
   :param fig: Matplotlib figure. If None, creates new figure.
   :param ax: Matplotlib axes. If None, creates new axes.

   :returns: The figure and axes containing the plot.