<jupyter_start><jupyter_text>Decomposition Exercise<jupyter_code># import pandas
import pandas as pd

# import statsmodels.api as sm
import statsmodels.api as sm

# import matplotlib
import matplotlib.pyplot as plt

# load data
data = sm.datasets.co2.load_pandas()
co2 = data.data<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08064516129032258, 'fraction_numerical': 0.0064516129032258064, 'mean_word_length': 6.232558139534884, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '432983', 'license': 'MIT', 'n_tokens_mistral': 115, 'n_tokens_neox': 111, 'n_words': 28, 'path': 'w9/w9d1/decomposition_exercise.ipynb', 'repo_name': 'bmskarate/lighthouseMain', 'size': '310'}