<jupyter_start><jupyter_text>Practical Lab Exam 1<jupyter_code>import numpy as np
A = np.array([[1,2,3],[4,5,6]])
B = np.array([[1,2],[3,4],[5,6]])
dot = np.dot(A,B)
print("a.", dot)

D = np.array([[1,2],[3,4]])
sum = D+D
print("b. ", sum)

C = np.array([[1,2,3], [4,5,6], [7,8,9]])
scaling = 2*C
print("c.", scaling)
prob2 = np.matrix([5, 3, -1])
print(prob2)
print("Type: Row Matrix")
print("Shape:", prob2.shape)
print("Dimension:", prob2.ndim)<jupyter_output>[[ 5  3 -1]]
Type: Row Matrix
Shape: (1, 3)
Dimension: 2
{'fraction_non_alphanumeric': 0.27167630057803466, 'fraction_numerical': 0.07707129094412331, 'mean_word_length': 5.753246753246753, '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': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '19689', 'license': 'Apache-2.0', 'n_tokens_mistral': 259, 'n_tokens_neox': 251, 'n_words': 52, 'path': 'Practical_Lab_Exam_1.ipynb', 'repo_name': 'qwertinuiop/Linear-Algebra-58019', 'size': '519'}