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1 To convert XML data to an Xarray structure, I first used the xml.etree.ElementTree module to parse the XML file and extract relevant information. I then structured the data into a Pandas DataFrame, ensuring the hierarchical race information was properly mapped. Finally, I converted the DataFrame into an Xarray dataset using xarray.Dataset, which allowed for efficient querying and analysis.
2 query method in query_results.py def get_top_3(ds): df = ds.to_dataframe().reset_index() top_3 = df.groupby([“trackID”, “trackName”, “raceDate”, “raceNumber”]).apply( lambda x: x.nsmallest(3, “finishingPosition”) ).reset_index(drop=True) return top_3
3 Top 3 Horses in race 9: Idiomatic – Jockey: Florent Geroux, Trainer: Brad H. Cox, Odds: 1.0 (Winner) Classy Edition – Jockey: Kendrick Carmouche, Trainer: Todd A. Pletcher, Odds: 9.4 (Runner-up) Morning Matcha – Jockey: Paco Lopez, Trainer: Robert E. Reid, Odds: 5.9 (Third Place)