lets_plot.GGBunch#
- class lets_plot.GGBunch#
Collection of plots created by ggplot function. Use method add_plot() to add plot to ‘bunch’. Each plot can have arbitrary location and size. Use show() to draw all plots in bunch.
Examples
1import numpy as np 2from lets_plot import * 3LetsPlot.setup_html() 4np.random.seed(42) 5n = 100 6x = np.arange(n) 7y = np.random.normal(size=n) 8w, h = 200, 150 9p = ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + ggsize(w, h) 10bunch = GGBunch() 11bunch.add_plot(p + geom_point(), 0, 0) 12bunch.add_plot(p + geom_histogram(bins=3), w, 0) 13bunch.add_plot(p + geom_line(), 0, h, 2*w, h) 14bunch.show()
- __init__()#
Initialize self.
- add_plot(plot_spec: PlotSpec, x, y, width=None, height=None)#
Add plot to ‘bunch’.
- Parameters:
- plot_spec
Plot specification created by ggplot() function.
- xint
x-coordinate of plot origin in px.
- yint
y-coordinate of plot origin in px.
- widthint
Width of plot in px.
- heightint
Height of plot in px.
- as_dict()#
Return the dictionary of all properties of the object with as_dict() applied recursively to all subproperties of FeatureSpec type.
- Returns:
- dict
Dictionary of properties.
Examples
1from lets_plot import * 2LetsPlot.setup_html() 3p = ggplot({'x': [0], 'y': [0]}) + geom_point(aes('x', 'y')) 4p.as_dict()
{'data': {'x': [0], 'y': [0]}, 'mapping': {}, 'data_meta': {'series_annotations': [{'type': 'int', 'column': 'x'}, {'type': 'int', 'column': 'y'}]}, 'kind': 'plot', 'scales': [], 'layers': [{'geom': 'point', 'mapping': {'x': 'x', 'y': 'y'}, 'data_meta': {}}], 'metainfo_list': []}
- show()#
Draw all plots currently in this ‘bunch’.