<jupyter_start><jupyter_text>Load Data<jupyter_code># Paths
yelp_covid19_path = "../data/covid_19_dataset_2020_06_10/yelp_academic_dataset_covid_features.json"
yelp_business_path = "../data/yelp_dataset/yelp_academic_dataset_business.json"
yelp_checkin_path = "../data/yelp_dataset/yelp_academic_dataset_checkin.json"

#Load Data into DF's
yelp_covid_df = pd.read_json(yelp_covid19_path, lines=True)
yelp_b_df = pd.read_json(yelp_business_path, lines=True)
yelp_check_df = pd.read_json(yelp_checkin_path, lines=True)<jupyter_output><empty_output><jupyter_text>Covid Data<jupyter_code>print(yelp_covid_df.shape)
yelp_covid_df.head()<jupyter_output>(209795, 9)<jupyter_text>Business Data<jupyter_code>print(yelp_b_df.shape)
yelp_b_df.head()
yelp_b_df["state"].value_counts()[:15]<jupyter_output><empty_output><jupyter_text>Checkin Data<jupyter_code>print(yelp_check_df.shape)
yelp_check_df.head()
yelp_check_df.iloc[0]["date"].split(",")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12849740932642487, 'fraction_numerical': 0.024870466321243522, 'mean_word_length': 13.205882352941176, 'pattern_counts': {'":': 0, '<': 16, '<?xml version=': 0, '>': 16, '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}}
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