<jupyter_start><jupyter_text>Calendar Data frame<jupyter_code># SHOW ALL COLUMNS FOR CALENDAR
for i in calendar_df.columns:
    print(i)
calendar_df.dtypes
calendar_df.head()
missingValues = calendar_df[['minimum_nights', 'maximum_nights']]
missingValues.isnull().any().sum()
calendar_df.isnull().any()<jupyter_output><empty_output><jupyter_text>Listings Data frame<jupyter_code># SHOW ALL COLUMNS FOR LISTINGS

for i in listings_df.columns:
    print(i)
listings_df.dtypes
# THIS SHOWS THE ARRAY OF AMMENITIES FOR EACH ROW

test = listings_df['amenities']
test
# THIS SHOWS A FULL LIST OF AMENITIES 
# MAYBE WE CAN CHOOSE A COUPLE?
amenities_list = list(listings_df.amenities)
amenities_list_string = " ".join(amenities_list)
amenities_list_string = amenities_list_string.replace('{', '')
amenities_list_string = amenities_list_string.replace('}', ',')
amenities_list_string = amenities_list_string.replace('"', '')
amenities_set = [x.strip() for x in amenities_list_string.split(',')]
amenities_set = set(amenities_set)
amenities_set
listings_df.head()<jupyter_output><empty_output><jupyter_text>Reviews Data frame<jupyter_code>for i in reviews_df.columns:
    print(i)
reviews_df.dtypes
reviews_df.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11479385610347616, 'fraction_numerical': 0.0, 'mean_word_length': 7.971014492753623, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '222016', 'license': 'MIT', 'n_tokens_mistral': 467, 'n_tokens_neox': 452, 'n_words': 86, 'path': 'Airbnb_DB/data_manipulation/Airbnb_data_manipulation_for_database.ipynb', 'repo_name': 'lmkennedy/DataBases', 'size': '1237'}