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
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
Minimum sample size to plot a lowess fit
- jitter
float
ortuple
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
If True, the data points are plotted.
- ax
AxesSubplot
Axes on which to plot, created if not provided.
- col1_name
- Returns:¶
The
matplotlib
figure
on
which
the
plot
id
drawn.
Last update:
Dec 16, 2024