drippy.onefactor

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

Attributes

_FACTOR_LEVEL

Functions

`scatter_plot`(→ tuple[matplotlib.figure.Figure, ...)	Creates a scatter plot of y vs x.
`box_plot`(→ tuple[matplotlib.figure.Figure, ...)	Creates a box plot of y grouped by factor levels in x.
`bihistogram`(→ tuple[matplotlib.figure.Figure, ...)	Creates side-by-side histograms for exactly 2 factor levels.
`qq_plot`(→ tuple[matplotlib.figure.Figure, ...)	Creates a quantile-quantile plot comparing 2 factor level distributions.
`mean_plot`(→ tuple[matplotlib.figure.Figure, ...)	Creates a mean plot of y grouped by factor levels in x.
`sd_plot`(→ tuple[matplotlib.figure.Figure, ...)	Creates a standard deviation plot of y grouped by factor levels in x.

Module Contents

drippy.onefactor._FACTOR_LEVEL = 'Factor Level'[source]

drippy.onefactor.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][source]

Creates a scatter plot of y vs x.

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

Parameters:

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

Returns:

The figure and axes containing the plot.

drippy.onefactor.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][source]

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

Parameters:

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

Returns:

The figure and axes containing the plot.

drippy.onefactor.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][source]

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

Parameters:

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

Returns:

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

drippy.onefactor.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][source]

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

Parameters:

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

Returns:

The figure and axes containing the plot.

drippy.onefactor.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][source]

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

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

Parameters:

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

Returns:

The figure and axes containing the plot.

drippy.onefactor.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][source]

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.

Parameters:

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

Returns:

The figure and axes containing the plot.