<jupyter_start><jupyter_text><jupyter_code>import requests
import pandas as pd
url2 = "https://8oi9s0nnth.apigw.ntruss.com/corona19-masks/v1/sales/json?page=1"
res = requests.get(url2)
text = res.text
corona19_mask = json.loads(text)

# print(json.dumps(corona19_mask,indent=4,sort_keys = True))
corona19_mask_list = []
for i in corona19_mask['sales']:
  corona19_mask_list.append([i['created_at'],i['code'],i['remain_stat']])
corona19_mask_dataframe = pd.DataFrame(corona19_mask_list)

corona19_mask_dataframe.head(10)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14571948998178508, 'fraction_numerical': 0.051001821493624776, 'mean_word_length': 9.0, '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': '561966', 'license': 'MIT', 'n_tokens_mistral': 244, 'n_tokens_neox': 230, 'n_words': 25, 'path': 'ipynb/corona19_mask.ipynb', 'repo_name': 'limjun92/limjun92.github.io', 'size': '549'}