statsmodels.imputation.mice.MICEData.plot_bivariate

MICEData.plot_bivariate(col1_name, col2_name, lowess_args=None, lowess_min_n=40, jitter=None, plot_points=True, ax=None)[source]

Plot observed and imputed values for two variables.

Displays a scatterplot of one variable against another. The points are colored according to whether the values are observed or imputed.

Parameters:

col1_name : string

The variable to be plotted on the horizontal axis.

col2_name : string

The variable to be plotted on the vertical axis.

lowess_args : dictionary

A dictionary of dictionaries, keys are ‘ii’, ‘io’, ‘oi’ and ‘oo’, where ‘o’ denotes ‘observed’ and ‘i’ denotes imputed. See Notes for details.

lowess_min_n : integer

Minimum sample size to plot a lowess fit

jitter : float or tuple

Standard deviation for jittering points in the plot. Either a single scalar applied to both axes, or a tuple containing x-axis jitter and y-axis jitter, respectively.

plot_points : bool

If True, the data points are plotted.

ax : matplotlib axes object

Axes on which to plot, created if not provided.

Returns:

The matplotlib figure on which the plot id drawn.