lets_plot.sampling_random_stratified#
- lets_plot.sampling_random_stratified(n, seed=None, min_subsample=None)#
Randomly sample from each stratum (subgroup).
- Parameters:
- nint
Number of items to return.
- seedint
Number used to initialize a pseudo random number generator.
- min_subsampleint
Minimal number of items in sub sample.
- Returns:
- FeatureSpec
Stratified random sample specification.
Examples
1import numpy as np 2from lets_plot import * 3LetsPlot.setup_html() 4np.random.seed(27) 5n = 1000 6x = np.random.normal(0, 1, n) 7y = np.random.normal(0, 1, n) 8cond = np.random.choice(['a', 'b'], n, p=[.9, .1]) 9ggplot({'x': x, 'y': y, 'cond': cond}, aes('x', 'y', color='cond')) + \ 10 geom_point(sampling=sampling_random_stratified(50, 35, min_subsample=10))