Linear regression line

daspi.plotlib.plotter.LinearRegressionLine(source, target, feature, target_on_y=True, color=None, marker=None, show_scatter=True, show_fit_ci=True, show_pred_ci=False, ax=None, visible_spines=None, hide_axis=None, **kwds)

Bases: Plotter

A linear regression plotter that extends the Plotter base class.

PARAMETER	DESCRIPTION
source	Pandas long format DataFrame containing the data source for the plot. TYPE: pandas DataFrame
target	Column name of the target variable for the plot. TYPE: str
feature	Column name of the feature variable for the plot, by default '' TYPE: str
target_on_y	Flag indicating whether the target variable is plotted on the y-axis, by default True TYPE: bool DEFAULT: True
color	Color to be used to draw the artists. If None, the first color is taken from the color cycle, by default None. TYPE: str | None DEFAULT: None
marker	The marker style for the scatter plot. Available markers see: https://matplotlib.org/stable/api/markers_api.html, by default None TYPE: str | None DEFAULT: None
show_scatter	Flag indicating whether to show the individual points, by default True. TYPE: bool DEFAULT: True
show_fit_ci	Flag indicating whether to show the confidence interval for the fitted line as filled area, by default True. TYPE: bool DEFAULT: True
show_pred_ci	Flag indicating whether to show the confidence interval for predictions as additional lines, by default False TYPE: bool DEFAULT: False
ax	The axes object for the plot. If None, the current axes is fetched using plt.gca(). If no axes are available, a new one is created. Defaults to None. TYPE: Axes | None DEFAULT: None
visible_spines	Specifies which spines are visible, the others are hidden. If 'none', no spines are visible. If None, the spines are drawn according to the stylesheet. Defaults to None. TYPE: Literal['target', 'feature', 'none'] | None DEFAULT: None
hide_axis	Specifies which axes should be hidden. If None, both axes are displayed. Defaults to None. TYPE: Literal['target', 'feature', 'both'] | None DEFAULT: None
**kwds	Those arguments have no effect. Only serves to catch further arguments that have no use here (occurs when this class is used within chart objects). DEFAULT: {}

Examples:

Apply to an existing Axes object:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from daspi import LinearRegressionLine

fig, ax = plt.subplots()
x = np.linspace(0, 10, 100)
df = pd.DataFrame(dict(
    x=x,
    y=x + np.random.randn(100) - 0.05 * np.square(x)))
reg_line = LinearRegressionLine(
    source=df, target='y', feature='x', ax=ax,
    show_scatter=True, show_fit_ci=True, show_pred_ci=True)
reg_line(
    kw_scatter=dict(color='black', s=10, alpha=0.5),
    kw_fit_ci=dict(color='skyblue'),
    kw_pred_ci=dict(color='steelblue', alpha=1),
    color='deepskyblue')

Apply using the plot method of a DaSPi Chart object

import numpy as np
import daspi as dsp
import pandas as pd

x = np.linspace(0, 10, 100)
df = pd.DataFrame(dict(
    x=x,
    y=x + np.random.randn(100) - 0.05 * np.square(x)))
chart = dsp.SingleChart(
        source=df,
        target='y',
        feature='x'
    ).plot(
        dsp.LinearRegressionLine,
        show_scatter=True,
        show_fit_ci=True,
        show_pred_ci=True,
        kw_call=dict(
            kw_scatter=dict(color='black', s=10, alpha=0.5),
            kw_fit_ci=dict(color='skyblue'),
            kw_pred_ci=dict(color='steelblue', alpha=1),
            color='deepskyblue'))

fit = PLOTTER.FITTED_VALUES instance-attribute

The name of the column containing the fitted values as defined in the PLOTTER.FITTED_VALUES.

show_scatter = show_scatter instance-attribute

Whether to show the individual points in the plot.

show_fit_ci = show_fit_ci instance-attribute

Whether to show the confidence interval for the fitted line.

show_pred_ci = show_pred_ci instance-attribute

Whether to show the confidence interval for the predictions.

model = sm.OLS(df[target], sm.add_constant(df[feature])).fit() instance-attribute

The fitted results of the linear regression model.

kw_default property

Default keyword arguments for plotting (read-only)

x_fit property

Get values used for x-axis for fitted line (read-only).

y_fit property

Get values used for y-axis for fitted line (read-only)

ci_data()

Get confidence interval for prediction and fitted line as DataFrame.