lets_plot.facet_wrap#
- lets_plot.facet_wrap(facets, ncol=None, nrow=None, *, scales=None, order=1, format=None, dir='h', labwidth=None)#
Split data by one or more faceting variables. For each data subset creates a plot panel and lays out panels according to the ncol, nrow and dir settings.
- Parameters:
- facetsstr or list
One or more faceting variable names.
- ncolint
Number of columns.
- nrowint
Number of rows.
- scalesstr
Specify whether scales are shared across all facets. ‘fixed’ - shared (the default), ‘free’ - vary across both rows and columns, ‘free_x’ or ‘free_y’ - vary across rows or columns respectively.
- orderint or list, default=1
Specify ordering direction panels. 1 - ascending, -1 - descending, 0 - no ordering. When a list is given, then values in the list are positionally matched to variables in facets.
- formatstr or list
Specify the format pattern for displaying faceting values. The format values are positionally matched to variables in facets.
- dir{‘h’, ‘v’}, default=’h’
Direction: either ‘h’ for horizontal, or ‘v’ for vertical.
- labwidthint or list
The maximum label length (in characters) before a line breaking is applied. If the original facet label already contains \n as a text separator, the line breaking is not applied.
- Returns:
- FeatureSpec
Facet wrap specification.
Notes
Format patterns in the format parameter can be just a number format (like ‘d’) or a string template where number format is surrounded by curly braces: “{d} cylinders”.
For example:
‘.2f’ -> ‘12.45’,
‘Score: {.2f}’ -> ‘Score: 12.45’,
‘Score: {}’ -> ‘Score: 12.454789’.
For more info see https://lets-plot.org/python/pages/formats.html.
Examples
1import numpy as np 2from lets_plot import * 3LetsPlot.setup_html() 4n = 100 5np.random.seed(42) 6x = np.random.normal(size=n) 7group = np.random.choice(['a', 'b'], size=n) 8ggplot({'x': x, 'group': group}, aes(x='x')) + \ 9 geom_histogram() + facet_wrap(facets='group')
1import numpy as np 2from lets_plot import * 3LetsPlot.setup_html() 4n = 1000 5np.random.seed(42) 6x = np.random.normal(size=n) 7p = [1/6, 1/3, 1/2] 8y = np.random.choice(p, size=n, p=p) 9ggplot({'x': x, 'y': y}, aes(x='x')) + \ 10 geom_histogram() + \ 11 facet_wrap(facets='y', order=-1, ncol=2, dir='v', format='.2f')