<jupyter_start><jupyter_text>Lorem ipsum<jupyter_code>import matplotlib.pyplot as plt
import seaborn as sns<jupyter_output><empty_output><jupyter_text>Condimentum Lorem ipsum dolor sit amet,_consectetur_ adipiscing elit,sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Sunt [in culpa qui officia](https://github.com/paw-lu/nbpreview) deserunt mollit anim id est laborum.<jupyter_code>fmri = sns.load_dataset("fmri")
tips = sns.load_dataset("tips")
fmri.head()
_, (ax_line, ax_box) = plt.subplots(ncols=2, facecolor="#1C1B1F", figsize=(20, 7))
(
    fmri.pipe(
        (sns.lineplot, "data"),
        x="timepoint",
        y="signal",
        hue="event",
        ax=ax_line,
        err_kws={"alpha": 1},
    ).set(
        xlabel=None,
        ylabel=None,
        yticks=[],
        xticks=[],
    )
)

(
    tips.pipe(
        (sns.boxplot, "data"),
        x="day",
        y="total_bill",
        hue="smoker",
        ax=ax_box,
    ).set(
        xlabel=None,
        ylabel=None,
        yticks=[],
        xticks=[],
    )
)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1452358926919519, 'fraction_numerical': 0.0074005550416281225, 'mean_word_length': 2.8920863309352516, 'pattern_counts': {'":': 1, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '249677', 'license': 'MIT', 'n_tokens_mistral': 430, 'n_tokens_neox': 420, 'n_words': 73, 'path': 'tests/unit/assets/notebook.ipynb', 'repo_name': 'WaylonWalker/nbpreview', 'size': '1081'}