# 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. The matplotlib figure on which the plot id drawn.