ehrapy.plot.love_plot

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ehrapy.plot.love_plot#

ehrapy.plot.love_plot(balance, *, threshold=0.1, title=None, width=520, height=None)[source]#

Plot a “love plot” of standardised mean differences before and after weighting.

Covariates are drawn on the y-axis sorted by their unweighted absolute SMD, with vertical guide lines at ±threshold (commonly 0.1).

Parameters:

  • balance (DataFrame) – Output of covariate_balance(), a DataFrame indexed by covariate name with smd_unweighted and smd_weighted columns.

  • threshold (float, default: 0.1) – SMD magnitude used for the dashed guide lines.

  • title (str | None, default: None) – Plot title. If None, defaults to "Covariate balance".

  • width (int, default: 520) – Plot width in pixels.

  • height (int | None, default: None) – Plot height in pixels. If None, height is set to 28 * n_covariates + 80.

Return type:

Overlay

Returns:

A holoviews.Overlay containing the scatter points, connecting lines, and guide lines.

Examples

>>> import ehrapy as ep
>>> import ehrdata as ed
>>> edata = ed.dt.mimic_2_preprocessed()
>>> bal = ep.tl.covariate_balance(
...     edata,
...     "aline_flg",
...     covariates=["age", "sofa_first", "sapsi_first"],
... )
>>> ep.pl.love_plot(bal)
Preview:
../../_images/love_plot.png
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