<jupyter_start><jupyter_text>Aula 1<jupyter_code>#
import numpy as np
x = np.arange(4,10,0.01)
print('x=',x)<jupyter_output>x= [4.   4.01 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 4.1  4.11 4.12 4.13
 4.14 4.15 4.16 4.17 4.18 4.19 4.2  4.21 4.22 4.23 4.24 4.25 4.26 4.27
 4.28 4.29 4.3  4.31 4.32 4.33 4.34 4.35 4.36 4.37 4.38 4.39 4.4  4.41
 4.42 4.43 4.44 4.45 4.46 4.47 4.48 4.49 4.5  4.51 4.52 4.53 4.54 4.55
 4.56 4.57 4.58 4.59 4.6  4.61 4.62 4.63 4.64 4.65 4.66 4.67 4.68 4.69
 4.7  4.71 4.72 4.73 4.74 4.75 4.76 4.77 4.78 4.79 4.8  4.81 4.82 4.83
 4.84 4.85 4.86 4.87 4.88 4.89 4.9  4.91 4.92 4.93 4.94 4.95 4.96 4.97
 4.98 4.99 5.   5.01 5.02 5.03 5.04 5.05 5.06 5.07 5.08 5.09 5.1  5.11
 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19 5.2  5.21 5.22 5.23 5.24 5.25
 5.26 5.27 5.28 5.29 5.3  5.31 5.32 5.33 5.34 5.35 5.36 5.37 5.38 5.39
 5.4  5.41 5.42 5.43 5.44 5.45 5.46 5.47 5.48 5.49 5.5  5.51 5.52 5.53
 5.54 5.55 5.56 5.57 5.58 5.59 5.6  5.61 5.62 5.63 5.64 5.65 5.66 5.67
 5.68 5.69 5.7  5.71 5.72 5.73 5.74 5.75 5.76 5.77 5.78 5.79 5.8  5.81
 5.82 5.83 5.84 5.85 5.86 5.87 5.88 5.89 5.9  5.91 5.92 5.93 5.94 5.95
 5.[...]
{'fraction_non_alphanumeric': 0.20017714791851196, 'fraction_numerical': 0.508414526129318, 'mean_word_length': 1.5393258426966292, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 14, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '604589', 'license': 'Apache-2.0', 'n_tokens_mistral': 1047, 'n_tokens_neox': 689, 'n_words': 206, 'path': 'Aula_1.ipynb', 'repo_name': 'zavaleta/ciencia-de-dados-com-python', 'size': '1129'}