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