<jupyter_start><jupyter_text>text = u'Hello, world!'document = types.Document(    content=text,    type=enums.Document.Type.PLAIN_TEXT) sentiment = client.analyze_sentiment(document=document).document_sentiment print('Text: {}'.format(text))print('Sentiment: {}, {}'.format(sentiment.score, sentiment.magnitude)) ex_text = '''The city of Charlotte had sought a public university since 1871 but was never able to sustain one. For years, the nearest state-supported university was 90 miles (140 km) away. The city submitted a bid in the late 1880s for what would become North Carolina State University, but lost to the city of Raleigh after a local farmer offered to donate land for the campus.[11] In 1946, the city sought a state-run medical school; instead, the state expanded the existing two-year school at UNC-Chapel Hill.''' print('Text: {}'.format(text))<jupyter_code>print(df)<jupyter_output>Hired   Salary  Sick Days
Employee                                     
<NAME> 2014-03-15  50000.0         10
<NAME>    2015-06-01  65000.0          8
<NAME>      2014-05-12  45000.0         10
<NAME>    2013-11-01  70000.0          3
<NAME>  2014-08-12  48000.0          7
<NAME>  2013-05-23  66000.0          8<jupyter_text>for e in language_analysis.entities:    print(e.name, e.entity_type, e.metadata, e.salience)<jupyter_code>print('Sentiment: {}, {}'.format(sentiment.score, sentiment.magnitude))<jupyter_output>Sentiment: 0.30000001192092896, 0.30000001192092896
{'fraction_non_alphanumeric': 0.10755616065350579, 'fraction_numerical': 0.10006807351940095, 'mean_word_length': 3.7115384615384617, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '640346', 'license': 'MIT', 'n_tokens_mistral': 552, 'n_tokens_neox': 453, 'n_words': 139, 'path': 'natural_language_sementic.ipynb', 'repo_name': 'TheRichSquad/HackNC2019', 'size': '1504'}