<jupyter_start><jupyter_text><jupyter_code>import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats

np.seed = 33<jupyter_output><empty_output><jupyter_text>Z Score significance<jupyter_code>a = np.random.randint(100,1000,10)
a_zscores = stats.zscore(a)
plt.figure(1,figsize=(9,3))
plt.subplot(2,1,1)
plt.plot(a)
plt.subplot(2,1,2)
plt.plot(a_zscores)
plt.show()<jupyter_output><empty_output><jupyter_text>Percentile Scores<jupyter_code><jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1390593047034765, 'fraction_numerical': 0.0408997955010225, 'mean_word_length': 10.666666666666666, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '167173', 'license': 'Apache-2.0', 'n_tokens_mistral': 230, 'n_tokens_neox': 213, 'n_words': 26, 'path': 'Python/probabilistic/stat101.ipynb', 'repo_name': 'vbsteja/code', 'size': '489'}