from datetime import datetime import numpy as np import pytest from pandas import ( Series, Timestamp, ) import pandas._testing as tm class TestConvert: def test_convert(self): # GH#10265 dt = datetime(2001, 1, 1, 0, 0) td = dt - datetime(2000, 1, 1, 0, 0) # Test coercion with mixed types ser = Series(["a", "3.1415", dt, td]) results = ser._convert(numeric=True) expected = Series([np.nan, 3.1415, np.nan, np.nan]) tm.assert_series_equal(results, expected) # Test standard conversion returns original results = ser._convert(datetime=True) tm.assert_series_equal(results, ser) results = ser._convert(numeric=True) expected = Series([np.nan, 3.1415, np.nan, np.nan]) tm.assert_series_equal(results, expected) results = ser._convert(timedelta=True) tm.assert_series_equal(results, ser) def test_convert_numeric_strings_with_other_true_args(self): # test pass-through and non-conversion when other types selected ser = Series(["1.0", "2.0", "3.0"]) results = ser._convert(datetime=True, numeric=True, timedelta=True) expected = Series([1.0, 2.0, 3.0]) tm.assert_series_equal(results, expected) results = ser._convert(True, False, True) tm.assert_series_equal(results, ser) def test_convert_datetime_objects(self): ser = Series( [datetime(2001, 1, 1, 0, 0), datetime(2001, 1, 1, 0, 0)], dtype="O" ) results = ser._convert(datetime=True, numeric=True, timedelta=True) expected = Series([datetime(2001, 1, 1, 0, 0), datetime(2001, 1, 1, 0, 0)]) tm.assert_series_equal(results, expected) results = ser._convert(datetime=False, numeric=True, timedelta=True) tm.assert_series_equal(results, ser) def test_convert_datetime64(self): # no-op if already dt64 dtype ser = Series( [ datetime(2001, 1, 1, 0, 0), datetime(2001, 1, 2, 0, 0), datetime(2001, 1, 3, 0, 0), ] ) result = ser._convert(datetime=True) expected = Series( [Timestamp("20010101"), Timestamp("20010102"), Timestamp("20010103")], dtype="M8[ns]", ) tm.assert_series_equal(result, expected) result = ser._convert(datetime=True) tm.assert_series_equal(result, expected) def test_convert_timedeltas(self): td = datetime(2001, 1, 1, 0, 0) - datetime(2000, 1, 1, 0, 0) ser = Series([td, td], dtype="O") results = ser._convert(datetime=True, numeric=True, timedelta=True) expected = Series([td, td]) tm.assert_series_equal(results, expected) results = ser._convert(True, True, False) tm.assert_series_equal(results, ser) def test_convert_numeric_strings(self): ser = Series([1.0, 2, 3], index=["a", "b", "c"]) result = ser._convert(numeric=True) tm.assert_series_equal(result, ser) # force numeric conversion res = ser.copy().astype("O") res["a"] = "1" result = res._convert(numeric=True) tm.assert_series_equal(result, ser) res = ser.copy().astype("O") res["a"] = "1." result = res._convert(numeric=True) tm.assert_series_equal(result, ser) res = ser.copy().astype("O") res["a"] = "garbled" result = res._convert(numeric=True) expected = ser.copy() expected["a"] = np.nan tm.assert_series_equal(result, expected) def test_convert_mixed_type_noop(self): # GH 4119, not converting a mixed type (e.g.floats and object) ser = Series([1, "na", 3, 4]) result = ser._convert(datetime=True, numeric=True) expected = Series([1, np.nan, 3, 4]) tm.assert_series_equal(result, expected) ser = Series([1, "", 3, 4]) result = ser._convert(datetime=True, numeric=True) tm.assert_series_equal(result, expected) def test_convert_preserve_non_object(self): # preserve if non-object ser = Series([1], dtype="float32") result = ser._convert(datetime=True) tm.assert_series_equal(result, ser) def test_convert_no_arg_error(self): ser = Series(["1.0", "2"]) msg = r"At least one of datetime, numeric or timedelta must be True\." with pytest.raises(ValueError, match=msg): ser._convert() def test_convert_preserve_bool(self): ser = Series([1, True, 3, 5], dtype=object) res = ser._convert(datetime=True, numeric=True) expected = Series([1, 1, 3, 5], dtype="i8") tm.assert_series_equal(res, expected) def test_convert_preserve_all_bool(self): ser = Series([False, True, False, False], dtype=object) res = ser._convert(datetime=True, numeric=True) expected = Series([False, True, False, False], dtype=bool) tm.assert_series_equal(res, expected)