<jupyter_start><jupyter_text>Try out the VortexaSDK First let's import our requirements<jupyter_code>from datetime import datetime
import vortexasdk as v<jupyter_output><empty_output><jupyter_text>Lets use the CargoTimeSeries endpoint to answer the following question: -  _What was the monthly average barrels per day of crude loaded from Rotterdam over the last year_? First we'll find the IDs corresponding to Rotterdam and Crude<jupyter_code>rotterdam = [g.id for g in v.Geographies().search("Rotterdam", exact_term_match=True).to_list()]
crude = [p.id for p in v.Products().search("Crude", exact_term_match=True).to_list()]
search_result = v.CargoTimeSeries().search(
    timeseries_unit='bpd',
    timeseries_frequency='month',
    filter_origins=rotterdam,
    filter_products=crude,
    filter_activity='loading_state',
    filter_time_min=datetime(2018, 1, 1),
    filter_time_max=datetime(2018, 12, 31))
df = search_result.to_df()
df.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10010214504596528, 'fraction_numerical': 0.014300306435137897, 'mean_word_length': 6.65625, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '52832', 'license': 'Apache-2.0', 'n_tokens_mistral': 343, 'n_tokens_neox': 318, 'n_words': 81, 'path': 'docs/examples/try_me_out/cargo_timeseries.ipynb', 'repo_name': 'VorTECHsa/python-sdk', 'size': '979'}