statsmodels.imputation.mice.MICEData.plot_fit_obs

MICEData.plot_fit_obs(col_name, lowess_args=None, lowess_min_n=40, jitter=None, plot_points=True, ax=None) [source]

Plot fitted versus imputed or observed values as a scatterplot.

Parameters:	col_name (string) – The variable to be plotted on the horizontal axis. lowess_args (dict-like) – Keyword arguments passed to lowess fit. A dictionary of dictionaries, keys are ‘o’ and ‘i’ denoting ‘observed’ and ‘imputed’, respectively. 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:
Return type:	The matplotlib figure on which the plot is drawn.