def test_beeswarm(): # Set the random seed for consistency np.random.seed(123) data1 = np.random.normal(loc=1, size=(6, 6), scale=0.2) data2 = np.random.normal(size=(6, 6), scale=0.2) fig, ax = plt.subplots() ppl.beeswarm([data1, data2], \ colors=[ppl.colors.set1[1], ppl.colors.set1[2]], \ xticklabels=["data1", "data2"]) ax.set_ylabel("Mean")
def test_beeswarm(): # Set the random seed for consistency np.random.seed(123) data1 = np.random.normal(loc=1, size=(6,6), scale=0.2) data2 = np.random.normal(size=(6,6), scale=0.2) fig, ax = plt.subplots() ppl.beeswarm([data1, data2], \ colors=[ppl.colors.set1[1], ppl.colors.set1[2]], \ xticklabels=["data1", "data2"]) ax.set_ylabel("Mean")
import matplotlib.pyplot as plt import prettyplotlib as ppl import numpy as np fig = plt.figure() ax = fig.add_subplot(111) np.random.seed(123) data1 = np.random.normal(loc=1, size=(6,6), scale=0.2) data2 = np.random.normal(size=(6,6), scale=0.2) ppl.beeswarm([data1, data2], \ colors=[ppl.colors.set1[1], ppl.colors.set1[2]], \ xticklabels=["data1", "data2"]) ax.set_ylabel("Mean") fig.savefig("plot.png")