feat(browser): auto-commit con 178 cambios

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/functions/datascience/summarize_categorical_test.py

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+"""Tests para summarize_categorical."""
+
+import sys
+import os
+
+sys.path.insert(0, os.path.dirname(__file__))
+
+from summarize_categorical import summarize_categorical
+
+
+def test_summarize_categorical_repeated():
+    """Lista con repetidos: top ordenado por count desc, mode/n_distinct/entropy."""
+    values = ["a", "a", "b", "c", "a", None, ""]
+    result = summarize_categorical(values)
+
+    # None descartado; total no-nulo = 6 (a,a,b,c,a,"").
+    assert [t["value"] for t in result["top"]] == ["a", "b", "c", ""]
+    assert result["top"][0]["count"] == 3
+    # top ordenado por count descendente.
+    counts = [t["count"] for t in result["top"]]
+    assert counts == sorted(counts, reverse=True)
+    assert abs(result["top"][0]["pct"] - 3 / 6) < 1e-12
+
+    assert result["mode"] == "a"
+    assert abs(result["mode_pct"] - 3 / 6) < 1e-12
+    assert result["n_distinct"] == 4
+    assert result["entropy"] > 0
+    assert result["imbalance"] == 3 / 1  # max_count(3) / min_count(1)
+    assert result["len_min"] == 0  # the "" value
+    assert result["len_max"] == 1
+
+
+def test_summarize_categorical_empty():
+    """Lista vacia: top=[] y resto de claves None."""
+    result = summarize_categorical([])
+    assert result["top"] == []
+    for key in (
+        "mode",
+        "mode_pct",
+        "n_distinct",
+        "entropy",
+        "imbalance",
+        "len_mean",
+        "len_min",
+        "len_max",
+    ):
+        assert result[key] is None
+
+
+def test_summarize_categorical_all_none():
+    """Lista de solo None se trata como vacia."""
+    result = summarize_categorical([None, None, None])
+    assert result["top"] == []
+    assert result["n_distinct"] is None
+    assert result["entropy"] is None
+
+
+def test_summarize_categorical_single_value():
+    """Un solo valor distinto: entropy 0.0, imbalance 1.0."""
+    result = summarize_categorical(["x", "x", "x"])
+    assert result["n_distinct"] == 1
+    assert result["entropy"] == 0.0
+    assert result["imbalance"] == 1.0
+    assert result["mode"] == "x"
+    assert result["mode_pct"] == 1.0
+    assert result["len_mean"] == 1.0
+
+
+def test_summarize_categorical_top_k():
+    """top_k limita el numero de entradas en top sin alterar n_distinct."""
+    values = ["a", "a", "b", "b", "c", "d", "e"]
+    result = summarize_categorical(values, top_k=2)
+    assert len(result["top"]) == 2
+    assert result["n_distinct"] == 5
+
+
+def test_summarize_categorical_keys():
+    """El dict tiene exactamente las claves del contrato categorical_sub."""
+    result = summarize_categorical(["a", "b"])
+    assert set(result.keys()) == {
+        "top",
+        "mode",
+        "mode_pct",
+        "n_distinct",
+        "entropy",
+        "imbalance",
+        "len_mean",
+        "len_min",
+        "len_max",
+    }