1from datetime import datetime
2
3import numpy as np
4
5import pandas as pd
6from pandas import Period, Series, date_range, period_range, to_datetime
7import pandas._testing as tm
8
9
10class TestCombineFirst:
11    def test_combine_first_period_datetime(self):
12        # GH#3367
13        didx = date_range(start="1950-01-31", end="1950-07-31", freq="M")
14        pidx = period_range(start=Period("1950-1"), end=Period("1950-7"), freq="M")
15        # check to be consistent with DatetimeIndex
16        for idx in [didx, pidx]:
17            a = Series([1, np.nan, np.nan, 4, 5, np.nan, 7], index=idx)
18            b = Series([9, 9, 9, 9, 9, 9, 9], index=idx)
19
20            result = a.combine_first(b)
21            expected = Series([1, 9, 9, 4, 5, 9, 7], index=idx, dtype=np.float64)
22            tm.assert_series_equal(result, expected)
23
24    def test_combine_first_name(self, datetime_series):
25        result = datetime_series.combine_first(datetime_series[:5])
26        assert result.name == datetime_series.name
27
28    def test_combine_first(self):
29        values = tm.makeIntIndex(20).values.astype(float)
30        series = Series(values, index=tm.makeIntIndex(20))
31
32        series_copy = series * 2
33        series_copy[::2] = np.NaN
34
35        # nothing used from the input
36        combined = series.combine_first(series_copy)
37
38        tm.assert_series_equal(combined, series)
39
40        # Holes filled from input
41        combined = series_copy.combine_first(series)
42        assert np.isfinite(combined).all()
43
44        tm.assert_series_equal(combined[::2], series[::2])
45        tm.assert_series_equal(combined[1::2], series_copy[1::2])
46
47        # mixed types
48        index = tm.makeStringIndex(20)
49        floats = Series(tm.randn(20), index=index)
50        strings = Series(tm.makeStringIndex(10), index=index[::2])
51
52        combined = strings.combine_first(floats)
53
54        tm.assert_series_equal(strings, combined.loc[index[::2]])
55        tm.assert_series_equal(floats[1::2].astype(object), combined.loc[index[1::2]])
56
57        # corner case
58        ser = Series([1.0, 2, 3], index=[0, 1, 2])
59        empty = Series([], index=[], dtype=object)
60        result = ser.combine_first(empty)
61        ser.index = ser.index.astype("O")
62        tm.assert_series_equal(ser, result)
63
64    def test_combine_first_dt64(self):
65
66        s0 = to_datetime(Series(["2010", np.NaN]))
67        s1 = to_datetime(Series([np.NaN, "2011"]))
68        rs = s0.combine_first(s1)
69        xp = to_datetime(Series(["2010", "2011"]))
70        tm.assert_series_equal(rs, xp)
71
72        s0 = to_datetime(Series(["2010", np.NaN]))
73        s1 = Series([np.NaN, "2011"])
74        rs = s0.combine_first(s1)
75        xp = Series([datetime(2010, 1, 1), "2011"])
76        tm.assert_series_equal(rs, xp)
77
78    def test_combine_first_dt_tz_values(self, tz_naive_fixture):
79        ser1 = Series(
80            pd.DatetimeIndex(["20150101", "20150102", "20150103"], tz=tz_naive_fixture),
81            name="ser1",
82        )
83        ser2 = Series(
84            pd.DatetimeIndex(["20160514", "20160515", "20160516"], tz=tz_naive_fixture),
85            index=[2, 3, 4],
86            name="ser2",
87        )
88        result = ser1.combine_first(ser2)
89        exp_vals = pd.DatetimeIndex(
90            ["20150101", "20150102", "20150103", "20160515", "20160516"],
91            tz=tz_naive_fixture,
92        )
93        exp = Series(exp_vals, name="ser1")
94        tm.assert_series_equal(exp, result)
95