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Map calendar dates to categorical season phases (offseason, preseason, regular, postseason) using np.select with boundary date conditions
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| name | tabular-season-phase-labeling |
| description | Map calendar dates to categorical season phases (offseason, preseason, regular, postseason) using np.select with boundary date conditions |
Sports, retail, and event-driven datasets exhibit distinct behavioral regimes tied to calendar phases. Mapping each date to its season phase (offseason, preseason, regular season, postseason) creates a powerful categorical feature that captures regime-dependent patterns. Using np.select with ordered conditions and boundary dates handles complex multi-phase calendars cleanly.
import numpy as np
conditions = [
df["date"] < df["preseason_start"],
df["date"] < df["regular_start"],
df["date"] <= df["regular_end"],
df["date"] < df["postseason_start"],
df["date"] <= df["postseason_end"],
df["date"] > df["postseason_end"],
]
labels = ["offseason", "preseason", "regular", "postseason_gap", "postseason", "offseason"]
df["season_phase"] = np.select(conditions, labels, default="unknown")
np.select evaluates top-to-bottom, first match wins