<jupyter_start><jupyter_text>Try out the Vortexa SDK First, let's import our requirements<jupyter_code>from datetime import datetime
from vortexasdk import OnshoreInventoriesTimeseries
df = OnshoreInventoriesTimeseries().search(time_min=datetime(2020,1,1), time_max=datetime(2021,1,1)).to_df()
df.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10510510510510511, 'fraction_numerical': 0.036036036036036036, 'mean_word_length': 12.36, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '621721', 'license': 'Apache-2.0', 'n_tokens_mistral': 124, 'n_tokens_neox': 113, 'n_words': 21, 'path': 'docs/examples/try_me_out/onshore_inventories_timeseries.ipynb', 'repo_name': 'VorTECHsa/python-sdk', 'size': '333'}