Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/frame/methods/test_to_timestamp.py

@@ -0,0 +1,154 @@
+from datetime import timedelta
+
+import numpy as np
+import pytest
+
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    PeriodIndex,
+    Series,
+    Timedelta,
+    date_range,
+    period_range,
+    to_datetime,
+)
+import pandas._testing as tm
+
+
+def _get_with_delta(delta, freq="YE-DEC"):
+    return date_range(
+        to_datetime("1/1/2001") + delta,
+        to_datetime("12/31/2009") + delta,
+        freq=freq,
+    )
+
+
+class TestToTimestamp:
+    def test_to_timestamp(self, frame_or_series):
+        K = 5
+        index = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        obj = DataFrame(
+            np.random.default_rng(2).standard_normal((len(index), K)),
+            index=index,
+            columns=["A", "B", "C", "D", "E"],
+        )
+        obj["mix"] = "a"
+        obj = tm.get_obj(obj, frame_or_series)
+
+        exp_index = date_range("1/1/2001", end="12/31/2009", freq="YE-DEC")
+        exp_index = exp_index + Timedelta(1, "D") - Timedelta(1, "ns")
+        result = obj.to_timestamp("D", "end")
+        tm.assert_index_equal(result.index, exp_index)
+        tm.assert_numpy_array_equal(result.values, obj.values)
+        if frame_or_series is Series:
+            assert result.name == "A"
+
+        exp_index = date_range("1/1/2001", end="1/1/2009", freq="YS-JAN")
+        result = obj.to_timestamp("D", "start")
+        tm.assert_index_equal(result.index, exp_index)
+
+        result = obj.to_timestamp(how="start")
+        tm.assert_index_equal(result.index, exp_index)
+
+        delta = timedelta(hours=23)
+        result = obj.to_timestamp("H", "end")
+        exp_index = _get_with_delta(delta)
+        exp_index = exp_index + Timedelta(1, "h") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.index, exp_index)
+
+        delta = timedelta(hours=23, minutes=59)
+        result = obj.to_timestamp("T", "end")
+        exp_index = _get_with_delta(delta)
+        exp_index = exp_index + Timedelta(1, "m") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.index, exp_index)
+
+        result = obj.to_timestamp("S", "end")
+        delta = timedelta(hours=23, minutes=59, seconds=59)
+        exp_index = _get_with_delta(delta)
+        exp_index = exp_index + Timedelta(1, "s") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.index, exp_index)
+
+    def test_to_timestamp_columns(self):
+        K = 5
+        index = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        df = DataFrame(
+            np.random.default_rng(2).standard_normal((len(index), K)),
+            index=index,
+            columns=["A", "B", "C", "D", "E"],
+        )
+        df["mix"] = "a"
+
+        # columns
+        df = df.T
+
+        exp_index = date_range("1/1/2001", end="12/31/2009", freq="YE-DEC")
+        exp_index = exp_index + Timedelta(1, "D") - Timedelta(1, "ns")
+        result = df.to_timestamp("D", "end", axis=1)
+        tm.assert_index_equal(result.columns, exp_index)
+        tm.assert_numpy_array_equal(result.values, df.values)
+
+        exp_index = date_range("1/1/2001", end="1/1/2009", freq="YS-JAN")
+        result = df.to_timestamp("D", "start", axis=1)
+        tm.assert_index_equal(result.columns, exp_index)
+
+        delta = timedelta(hours=23)
+        result = df.to_timestamp("H", "end", axis=1)
+        exp_index = _get_with_delta(delta)
+        exp_index = exp_index + Timedelta(1, "h") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.columns, exp_index)
+
+        delta = timedelta(hours=23, minutes=59)
+        result = df.to_timestamp("min", "end", axis=1)
+        exp_index = _get_with_delta(delta)
+        exp_index = exp_index + Timedelta(1, "m") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.columns, exp_index)
+
+        result = df.to_timestamp("S", "end", axis=1)
+        delta = timedelta(hours=23, minutes=59, seconds=59)
+        exp_index = _get_with_delta(delta)
+        exp_index = exp_index + Timedelta(1, "s") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.columns, exp_index)
+
+        result1 = df.to_timestamp("5min", axis=1)
+        result2 = df.to_timestamp("min", axis=1)
+        expected = date_range("2001-01-01", "2009-01-01", freq="YS")
+        assert isinstance(result1.columns, DatetimeIndex)
+        assert isinstance(result2.columns, DatetimeIndex)
+        tm.assert_numpy_array_equal(result1.columns.asi8, expected.asi8)
+        tm.assert_numpy_array_equal(result2.columns.asi8, expected.asi8)
+        # PeriodIndex.to_timestamp always use 'infer'
+        assert result1.columns.freqstr == "YS-JAN"
+        assert result2.columns.freqstr == "YS-JAN"
+
+    def test_to_timestamp_invalid_axis(self):
+        index = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        obj = DataFrame(
+            np.random.default_rng(2).standard_normal((len(index), 5)), index=index
+        )
+
+        # invalid axis
+        with pytest.raises(ValueError, match="axis"):
+            obj.to_timestamp(axis=2)
+
+    def test_to_timestamp_hourly(self, frame_or_series):
+        index = period_range(freq="h", start="1/1/2001", end="1/2/2001")
+        obj = Series(1, index=index, name="foo")
+        if frame_or_series is not Series:
+            obj = obj.to_frame()
+
+        exp_index = date_range("1/1/2001 00:59:59", end="1/2/2001 00:59:59", freq="h")
+        result = obj.to_timestamp(how="end")
+        exp_index = exp_index + Timedelta(1, "s") - Timedelta(1, "ns")
+        tm.assert_index_equal(result.index, exp_index)
+        if frame_or_series is Series:
+            assert result.name == "foo"
+
+    def test_to_timestamp_raises(self, index, frame_or_series):
+        # GH#33327
+        obj = frame_or_series(index=index, dtype=object)
+
+        if not isinstance(index, PeriodIndex):
+            msg = f"unsupported Type {type(index).__name__}"
+            with pytest.raises(TypeError, match=msg):
+                obj.to_timestamp()