<jupyter_start><jupyter_text>Main title of exampleSome explanation Author: <NAME>  Synthetic datasetSome explanation with a reference [1]_<jupyter_code>import numpy as np

m = 1000
n = 10
com_dataset = np.zeros((m, n))<jupyter_output><empty_output><jupyter_text>Multivariate AmputationSome explanation<jupyter_code>from pyampute import MultivariateAmputation

ma = MultivariateAmputation()
incomplete_data = ma.fit_transform(com_dataset)
from pyampute.exploration.md_patterns import mdPatterns

mdp = mdPatterns()
plot = mdp._get_patterns(incomplete_data)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08205128205128205, 'fraction_numerical': 0.011965811965811967, 'mean_word_length': 9.280701754385966, 'pattern_counts': {'":': 0, '<': 10, '<?xml version=': 0, '>': 10, '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': '567129', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 212, 'n_tokens_neox': 193, 'n_words': 41, 'path': 'docs/build/html/_downloads/b79c62fbec6fa865e4aadf8d30a8fc64/plot_introduction.ipynb', 'repo_name': 'RianneSchouten/pyampute', 'size': '594'}