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
str The variable to be plotted on the horizontal axis.
- col2_name
str The variable to be plotted on the vertical axis.
- lowess_args
dictionary,optional 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
int,optional Minimum sample size to plot a lowess fit
- jitter
floatortuple,optional 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_pointsbool,
optional If True, the data points are plotted.
- ax
AxesSubplot,optional Axes on which to plot, created if not provided.
- col1_name
- Returns:
FigureThe matplotlib figure on which the plot is drawn.