Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/series/methods/test_combine_first.py

@@ -0,0 +1,149 @@
+from datetime import datetime
+
+import numpy as np
+
+import pandas as pd
+from pandas import (
+    Period,
+    Series,
+    date_range,
+    period_range,
+    to_datetime,
+)
+import pandas._testing as tm
+
+
+class TestCombineFirst:
+    def test_combine_first_period_datetime(self):
+        # GH#3367
+        didx = date_range(start="1950-01-31", end="1950-07-31", freq="ME")
+        pidx = period_range(start=Period("1950-1"), end=Period("1950-7"), freq="M")
+        # check to be consistent with DatetimeIndex
+        for idx in [didx, pidx]:
+            a = Series([1, np.nan, np.nan, 4, 5, np.nan, 7], index=idx)
+            b = Series([9, 9, 9, 9, 9, 9, 9], index=idx)
+
+            result = a.combine_first(b)
+            expected = Series([1, 9, 9, 4, 5, 9, 7], index=idx, dtype=np.float64)
+            tm.assert_series_equal(result, expected)
+
+    def test_combine_first_name(self, datetime_series):
+        result = datetime_series.combine_first(datetime_series[:5])
+        assert result.name == datetime_series.name
+
+    def test_combine_first(self):
+        values = np.arange(20, dtype=np.float64)
+        series = Series(values, index=np.arange(20, dtype=np.int64))
+
+        series_copy = series * 2
+        series_copy[::2] = np.nan
+
+        # nothing used from the input
+        combined = series.combine_first(series_copy)
+
+        tm.assert_series_equal(combined, series)
+
+        # Holes filled from input
+        combined = series_copy.combine_first(series)
+        assert np.isfinite(combined).all()
+
+        tm.assert_series_equal(combined[::2], series[::2])
+        tm.assert_series_equal(combined[1::2], series_copy[1::2])
+
+        # mixed types
+        index = pd.Index([str(i) for i in range(20)])
+        floats = Series(np.random.default_rng(2).standard_normal(20), index=index)
+        strings = Series([str(i) for i in range(10)], index=index[::2], dtype=object)
+
+        combined = strings.combine_first(floats)
+
+        tm.assert_series_equal(strings, combined.loc[index[::2]])
+        tm.assert_series_equal(floats[1::2].astype(object), combined.loc[index[1::2]])
+
+        # corner case
+        ser = Series([1.0, 2, 3], index=[0, 1, 2])
+        empty = Series([], index=[], dtype=object)
+        msg = "The behavior of array concatenation with empty entries is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = ser.combine_first(empty)
+        ser.index = ser.index.astype("O")
+        tm.assert_series_equal(ser, result)
+
+    def test_combine_first_dt64(self, unit):
+        s0 = to_datetime(Series(["2010", np.nan])).dt.as_unit(unit)
+        s1 = to_datetime(Series([np.nan, "2011"])).dt.as_unit(unit)
+        rs = s0.combine_first(s1)
+        xp = to_datetime(Series(["2010", "2011"])).dt.as_unit(unit)
+        tm.assert_series_equal(rs, xp)
+
+        s0 = to_datetime(Series(["2010", np.nan])).dt.as_unit(unit)
+        s1 = Series([np.nan, "2011"])
+        rs = s0.combine_first(s1)
+
+        xp = Series([datetime(2010, 1, 1), "2011"], dtype="datetime64[ns]")
+
+        tm.assert_series_equal(rs, xp)
+
+    def test_combine_first_dt_tz_values(self, tz_naive_fixture):
+        ser1 = Series(
+            pd.DatetimeIndex(["20150101", "20150102", "20150103"], tz=tz_naive_fixture),
+            name="ser1",
+        )
+        ser2 = Series(
+            pd.DatetimeIndex(["20160514", "20160515", "20160516"], tz=tz_naive_fixture),
+            index=[2, 3, 4],
+            name="ser2",
+        )
+        result = ser1.combine_first(ser2)
+        exp_vals = pd.DatetimeIndex(
+            ["20150101", "20150102", "20150103", "20160515", "20160516"],
+            tz=tz_naive_fixture,
+        )
+        exp = Series(exp_vals, name="ser1")
+        tm.assert_series_equal(exp, result)
+
+    def test_combine_first_timezone_series_with_empty_series(self):
+        # GH 41800
+        time_index = date_range(
+            datetime(2021, 1, 1, 1),
+            datetime(2021, 1, 1, 10),
+            freq="h",
+            tz="Europe/Rome",
+        )
+        s1 = Series(range(10), index=time_index)
+        s2 = Series(index=time_index)
+        msg = "The behavior of array concatenation with empty entries is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = s1.combine_first(s2)
+        tm.assert_series_equal(result, s1)
+
+    def test_combine_first_preserves_dtype(self):
+        # GH51764
+        s1 = Series([1666880195890293744, 1666880195890293837])
+        s2 = Series([1, 2, 3])
+        result = s1.combine_first(s2)
+        expected = Series([1666880195890293744, 1666880195890293837, 3])
+        tm.assert_series_equal(result, expected)
+
+    def test_combine_mixed_timezone(self):
+        # GH 26283
+        uniform_tz = Series({pd.Timestamp("2019-05-01", tz="UTC"): 1.0})
+        multi_tz = Series(
+            {
+                pd.Timestamp("2019-05-01 01:00:00+0100", tz="Europe/London"): 2.0,
+                pd.Timestamp("2019-05-02", tz="UTC"): 3.0,
+            }
+        )
+
+        result = uniform_tz.combine_first(multi_tz)
+        expected = Series(
+            [1.0, 3.0],
+            index=pd.Index(
+                [
+                    pd.Timestamp("2019-05-01 00:00:00+00:00", tz="UTC"),
+                    pd.Timestamp("2019-05-02 00:00:00+00:00", tz="UTC"),
+                ],
+                dtype="object",
+            ),
+        )
+        tm.assert_series_equal(result, expected)