report.coefplot

report.coefplot(
    models
    alpha=0.05
    figsize=None
    yintercept=0
    xintercept=None
    rotate_xticks=0
    title=None
    coord_flip=True
    keep=None
    drop=None
    exact_match=False
    plot_backend='lets_plot'
    labels=None
    joint=None
    seed=None
    ax=None
)

Plot model coefficients with confidence intervals.

Parameters

Name Type Description Default
models list or object A list of fitted models of type Feols or Fepois, or just a single model. required
figsize tuple or None The size of the figure. If None, the default size is used. None
alpha float The significance level for the confidence intervals. 0.05
yintercept float or None The value at which to draw a horizontal line on the plot. Default is 0. 0
xintercept float or None The value at which to draw a vertical line on the plot. Default is None. None
rotate_xticks float The angle in degrees to rotate the xticks labels. Default is 0 (no rotation). 0
title str The title of the plot. None
coord_flip bool Whether to flip the coordinates of the plot. Default is True. True
keep Optional[Union[list, str]] The pattern for retaining coefficient names. You can pass a string (one pattern) or a list (multiple patterns). Default is keeping all coefficients. You should use regular expressions to select coefficients. “age”, # would keep all coefficients containing age r”^tr”, # would keep all coefficients starting with tr r”\d$“, # would keep all coefficients ending with number Output will be in the order of the patterns. None
drop Optional[Union[list, str]] The pattern for excluding coefficient names. You can pass a string (one pattern) or a list (multiple patterns). Syntax is the same as for keep. Default is keeping all coefficients. Parameter keep and drop can be used simultaneously. None
exact_match bool Whether to use exact match for keep and drop. Default is False. If True, the pattern will be matched exactly to the coefficient name instead of using regular expressions. False
plot_backend str The plotting backend to use between “lets_plot” (default) and “matplotlib”. 'lets_plot'
labels Optional[dict] A dictionary to relabel the variables. The keys are the original variable names and the values the new names. The renaming is applied after the selection of the coefficients via keep and drop. None
joint Optional[Union[str, bool]] Whether to plot simultaneous confidence bands for the coefficients. If True, simultaneous confidence bands are plotted. If False, “standard” confidence intervals are plotted. If “both”, both are plotted in one figure. Default is None, which returns the standard confidence intervals. Note that this option is not available for objects of type FixestMulti, i.e. multiple estimation. None
seed Optional[int] The seed for the random number generator. Default is None. Only required / used when joint is True. None

Returns

Name Type Description
object A lets-plot figure.

Examples

import pyfixest as pf
from pyfixest.report.utils import rename_categoricals

df = pf.get_data()
fit1 = pf.feols("Y ~ X1", data = df)
fit2 = pf.feols("Y ~ X1 + X2", data = df)
fit3 = pf.feols("Y ~ X1 + X2 | f1", data = df)
fit4 = pf.feols("Y ~ C(X1)", data = df)

pf.coefplot([fit1, fit2, fit3])
pf.coefplot([fit4], labels = rename_categoricals(fit1._coefnames))

pf.coefplot([fit1], joint = "both")