<jupyter_start><jupyter_text>Figure 4e<jupyter_code>path_to_excelfile = os.path.join(
    path_to_all_source_data,
    "Source_Data_Figure_4",
    "SourceData_Fig4e.xlsx"
)
excelfile = pd.ExcelFile(path_to_excelfile)
excelfile.sheet_names
single_region_events = pd.read_excel(
    excelfile, 
    sheet_name='SourceDataFig4eInput1'
)
single_region_events_mean_d2margin = pd.read_excel(
    excelfile, 
    sheet_name='SourceDataFig4eInput2'
)
plot_data(
    single_region_events,
    single_region_events_mean_d2margin
)<jupyter_output><empty_output><jupyter_text>Extended Data Figure 7b<jupyter_code>path_to_excelfile = os.path.join(
    path_to_all_source_data,
    "Source_Data_Extended_Data_Figure_7",
    "SourceData_ExtendedData_Fig7b.xlsx"
)
excelfile = pd.ExcelFile(path_to_excelfile)
excelfile.sheet_names
single_region_events = pd.read_excel(
    excelfile, 
    sheet_name='SourceDataEDFig7bInput1'
)
single_region_events_mean_d2margin = pd.read_excel(
    excelfile, 
    sheet_name='SourceDataEDFig7bInput2'
)
plot_data(
    single_region_events,
    single_region_events_mean_d2margin
)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.07964601769911504, 'fraction_numerical': 0.01592920353982301, 'mean_word_length': 6.6938775510204085, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '551681', 'license': 'MIT', 'n_tokens_mistral': 461, 'n_tokens_neox': 447, 'n_words': 43, 'path': 'Scripts for making figures/stripplotYoungestSubclonesTumour.ipynb', 'repo_name': 'iamfuxiao/tumour-growth-patterns-impact-evolution', 'size': '1130'}