<jupyter_start><jupyter_text>Vega backend examples<jupyter_code>from physt.examples import normal_h1, iris_h1, normal_h2, normal_h3, munros
from physt.plotting import set_default_backend

import numpy as np
np.random.seed(42)

set_default_backend("vega")
H = normal_h1()
H.plot.scatter()
H.plot.bar(cumulative=True, xlabel="Other label")
H = iris_h1()
H.plot.line(cumulative=True)
H2 = munros().T
H2.plot(cmap="YellowGreen", show_values=True, height=333, width=333, value_format=".:;oO##############".__getitem__)<jupyter_output><empty_output><jupyter_text>Example of an interactive 3D histogram**Note:** Unfortunately, this example does not render properly nor in GitHub renderer or notebook viewer. A live notebook must be running.<jupyter_code>H3 = normal_h3()
H3.axis_names = ("first", "second", "third")
H3.plot(show_values=True, show_zero=False, cmap="Blues", density=True, show_colorbar=False, value_format=".1f")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1431578947368421, 'fraction_numerical': 0.023157894736842106, 'mean_word_length': 8.704081632653061, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '208013', 'license': 'MIT', 'n_tokens_mistral': 356, 'n_tokens_neox': 339, 'n_words': 72, 'path': 'doc/vega-examples.ipynb', 'repo_name': 'toddrme2178/physt', 'size': '950'}