did.visualize.panelview
did.visualize.panelview(data, unit, time, treat, collapse_to_cohort=False, subsamp=None, sort_by_timing=False, xlab=None, ylab=None, noticks=False, title=None, legend=False, ax=None)
Generate a panel view of the treatment variable over time for each unit.
Parameters
Name | Type | Description | Default |
---|---|---|---|
data |
pandas.DataFrame | The input dataframe containing the data. | required |
unit |
str | The column name representing the unit identifier. | required |
time |
str | The column name representing the time identifier. | required |
treat |
str | The column name representing the treatment variable. | required |
collapse_to_cohort |
bool | Whether to collapse units into treatment cohorts. | False |
subsamp |
int | The number of samples to draw from data set for display (default is None). | None |
sort_by_timing |
bool | Whether to sort the treatment cohorts by the number of treated periods. | False |
xlab |
str | The label for the x-axis. Default is None, in which case default labels are used. | None |
ylab |
str | The label for the y-axis. Default is None, in which case default labels are used. | None |
noticks |
bool | Whether to display ticks on the plot. Default is False. | False |
title |
str | The title for the plot. Default is None, in which case no title is displayed. | None |
legend |
bool | Whether to display a legend. Default is False (since binary treatments are self-explanatory). | False |
ax |
matplotlib.pyplot.Axes | The axes on which to draw the plot. Default is None, in which case a new figure is created. | None |
Returns
Type | Description |
---|---|
matplotlib.pyplot.Axes |
Examples
import pandas as pd
import numpy as np
= pd.read_csv("pd.read_csv("pyfixest/did/data/df_het.csv")
df_het panelview(
= df_het,
data = "unit",
unit = "year",
time = "treat",
treat = 50,
subsamp = "Treatment Assignment"
title )