<jupyter_start><jupyter_text>This notebook uses the [GapMinder data set](https://www.gapminder.org)<jupyter_code>import pandas as pd
data = pd.read_csv("data/gapminder.tsv", sep='\t')
data.head() # show five entries<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1469387755102041, 'fraction_numerical': 0.0, 'mean_word_length': 7.785714285714286, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 1, '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': '167865', 'license': 'MIT', 'n_tokens_mistral': 96, 'n_tokens_neox': 92, 'n_words': 17, 'path': '18-warmup-blank_hierarchical_indexing.ipynb', 'repo_name': 'hanisaf/advanced-data-management-and-analytics', 'size': '245'}