<jupyter_start><jupyter_text>Operations<jupyter_code>np.random.seed(101)
arr = np.random.randint(0,100,10)
arr
arr2 = np.random.randint(0, 100, 10)
arr2
arr.max()
arr.min()
arr.mean()
arr.argmin()
arr.argmax()
arr.reshape(2,5)
## indexing
mat = np.arange(0,100).reshape(10,10)
mat
row =0
col = 1
mat[row, col]
mat[:, col]
mat > 50<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18888888888888888, 'fraction_numerical': 0.08611111111111111, 'mean_word_length': 6.36734693877551, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '582696', 'license': 'MIT', 'n_tokens_mistral': 186, 'n_tokens_neox': 169, 'n_words': 29, 'path': 'study_python/tensorflow/workspace/numpy/01.ipynb', 'repo_name': 'AlphaSunny/study', 'size': '360'}