41 lines
1.5 KiB
Python
41 lines
1.5 KiB
Python
"""Diagnóstico de outliers no banco SQLite."""
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import sys; sys.path.insert(0, ".")
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from pathlib import Path
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import sqlite3
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import pandas as pd
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conn = sqlite3.connect("dados/met.db")
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LIMITS = {"T": (-25, 55), "Td": (-30, 40), "UR": (0, 100),
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"QNH": (940, 1060), "WS": (0, 200), "WG": (0, 250),
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"WD": (0, 360), "VIS": (0, 9999), "TETO": (0, 9999), "PREC": (0, 500)}
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print("=== Outliers por variável (fora dos limites físicos) ===\n")
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total = conn.execute("SELECT COUNT(*) FROM observations").fetchone()[0]
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print(f"Total observações: {total:,}\n")
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for col, (lo, hi) in LIMITS.items():
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rows = conn.execute(f"""
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SELECT aerodrome, dt, {col}
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FROM observations
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WHERE {col} IS NOT NULL AND ({col} < {lo} OR {col} > {hi})
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ORDER BY ABS({col}) DESC LIMIT 10
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""").fetchall()
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if rows:
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print(f"--- {col} (limite: {lo} a {hi}) ---")
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for r in rows:
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print(f" {r[0]} {r[1]} {col}={r[2]}")
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cnt = conn.execute(f"SELECT COUNT(*) FROM observations WHERE {col} < {lo} OR {col} > {hi}").fetchone()[0]
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print(f" Total fora do limite: {cnt:,} ({cnt/total*100:.2f}%)\n")
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# Estatísticas básicas
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print("\n=== Estatísticas básicas ===\n")
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cols = ", ".join([f"MIN({c}) as min_{c}, MAX({c}) as max_{c}, AVG({c}) as avg_{c}" for c in LIMITS])
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row = conn.execute(f"SELECT {cols} FROM observations").fetchone()
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keys = [f"{fn}_{c}" for c in LIMITS for fn in ("min","max","avg")]
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for k, v in zip(keys, row):
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if v is not None:
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print(f" {k}: {v:.2f}")
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conn.close()
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