<jupyter_start><jupyter_text>Latest Access to the dataset: 12/03/2020<jupyter_code>import pandas as pd
file_name = pd.read_csv('https://query.data.world/s/gib6aa6n3tmtuvrqpbdlhcbgdg7tk4')

# Best Practice: Make a copy of the raw data to work on
reviews = file_name.copy()

# Sanity check
reviews.head()
file_name.to_csv("Beer_Reviews.csv.gz",
                index=False,
                compression="gzip")
file_name.to_csv("Ten_Years_of_Beer_Reviews.csv.zip",
                index=False,
                compression="zip")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11171171171171171, 'fraction_numerical': 0.023423423423423424, 'mean_word_length': 3.5950413223140494, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, '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': '310030', 'license': 'MIT', 'n_tokens_mistral': 214, 'n_tokens_neox': 203, 'n_words': 34, 'path': 'Technical Notebook/Getting_Data_beer_reviews.ipynb', 'repo_name': 'tvanwer1/Final-Project', 'size': '555'}