<jupyter_start><jupyter_text>First, load up the dataFirst you're going to want to create a data frame from the `dailybots.csv` file which can be found in the `data` directory.  You should be able to do this with the `pd.read_csv()` function.  Take a minute to look at the dataframe because we are going to be using it for this entire worksheet.<jupyter_code>data = pd.read_csv( '../data/dailybots.csv' )<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08314087759815242, 'fraction_numerical': 0.0, 'mean_word_length': 4.864864864864865, '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': '422816', 'license': 'Apache-2.0', 'n_tokens_mistral': 138, 'n_tokens_neox': 133, 'n_words': 60, 'path': 'Notebooks/EDA/EDA Worksheet - Python Version.ipynb', 'repo_name': 'jayjacobs/fundamentals-datasci', 'size': '433'}