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.

© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.imputation.mice.MICEData.plot_fit_obs.html