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import numpy as np |
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import pandas as pd |
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import vaex |
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from vaex_queries import utils |
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Q_NUM = 6 |
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def q(): |
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date1 = np.datetime64("1994-01-01") |
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date2 = np.datetime64("1995-01-01") |
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var3 = 24 |
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line_item_ds = utils.get_line_item_ds |
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line_item_ds() |
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def query(): |
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nonlocal line_item_ds |
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line_item_ds = line_item_ds() |
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lineitem_filtered = line_item_ds[ |
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["l_quantity", "l_extendedprice", "l_discount", "l_shipdate"] |
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] |
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sel = ( |
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(lineitem_filtered.l_shipdate >= date1) |
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& (lineitem_filtered.l_shipdate < date2) |
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& (lineitem_filtered.l_discount >= 0.05) |
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& (lineitem_filtered.l_discount <= 0.07) |
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& (lineitem_filtered.l_quantity < var3) |
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) |
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flineitem = lineitem_filtered[sel] |
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result_value = (flineitem.l_extendedprice * flineitem.l_discount).sum() |
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result_df = pd.DataFrame({"revenue": [float(result_value)]}) |
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return vaex.from_pandas(result_df) |
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utils.run_query(Q_NUM, query) |
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if __name__ == "__main__": |
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q() |
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