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66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
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import numpy as np
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import pandas as pd
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from pandas import DataFrame, date_range, to_datetime
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import pandas._testing as tm
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class TestDataFrameTimeSeriesMethods:
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def test_frame_ctor_datetime64_column(self):
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rng = date_range("1/1/2000 00:00:00", "1/1/2000 1:59:50", freq="10s")
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dates = np.asarray(rng)
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df = DataFrame({"A": np.random.randn(len(rng)), "B": dates})
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assert np.issubdtype(df["B"].dtype, np.dtype("M8[ns]"))
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def test_frame_append_datetime64_col_other_units(self):
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n = 100
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units = ["h", "m", "s", "ms", "D", "M", "Y"]
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ns_dtype = np.dtype("M8[ns]")
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for unit in units:
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dtype = np.dtype(f"M8[{unit}]")
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vals = np.arange(n, dtype=np.int64).view(dtype)
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df = DataFrame({"ints": np.arange(n)}, index=np.arange(n))
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df[unit] = vals
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ex_vals = to_datetime(vals.astype("O")).values
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assert df[unit].dtype == ns_dtype
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assert (df[unit].values == ex_vals).all()
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# Test insertion into existing datetime64 column
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df = DataFrame({"ints": np.arange(n)}, index=np.arange(n))
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df["dates"] = np.arange(n, dtype=np.int64).view(ns_dtype)
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for unit in units:
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dtype = np.dtype(f"M8[{unit}]")
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vals = np.arange(n, dtype=np.int64).view(dtype)
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tmp = df.copy()
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tmp["dates"] = vals
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ex_vals = to_datetime(vals.astype("O")).values
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assert (tmp["dates"].values == ex_vals).all()
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def test_datetime_assignment_with_NaT_and_diff_time_units(self):
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# GH 7492
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data_ns = np.array([1, "nat"], dtype="datetime64[ns]")
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result = pd.Series(data_ns).to_frame()
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result["new"] = data_ns
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expected = pd.DataFrame(
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{0: [1, None], "new": [1, None]}, dtype="datetime64[ns]"
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)
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tm.assert_frame_equal(result, expected)
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# OutOfBoundsDatetime error shouldn't occur
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data_s = np.array([1, "nat"], dtype="datetime64[s]")
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result["new"] = data_s
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expected = pd.DataFrame(
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{0: [1, None], "new": [1e9, None]}, dtype="datetime64[ns]"
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)
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tm.assert_frame_equal(result, expected)
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