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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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DataFrame, |
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Index, |
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NaT, |
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date_range, |
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) |
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@pytest.fixture |
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def datetime_frame() -> DataFrame: |
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""" |
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Fixture for DataFrame of floats with DatetimeIndex |
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Columns are ['A', 'B', 'C', 'D'] |
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""" |
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return DataFrame( |
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np.random.default_rng(2).standard_normal((100, 4)), |
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columns=Index(list("ABCD"), dtype=object), |
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index=date_range("2000-01-01", periods=100, freq="B"), |
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) |
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@pytest.fixture |
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def float_string_frame(): |
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""" |
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Fixture for DataFrame of floats and strings with index of unique strings |
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Columns are ['A', 'B', 'C', 'D', 'foo']. |
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""" |
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df = DataFrame( |
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np.random.default_rng(2).standard_normal((30, 4)), |
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index=Index([f"foo_{i}" for i in range(30)], dtype=object), |
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columns=Index(list("ABCD"), dtype=object), |
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) |
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df["foo"] = "bar" |
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return df |
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@pytest.fixture |
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def mixed_float_frame(): |
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""" |
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Fixture for DataFrame of different float types with index of unique strings |
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Columns are ['A', 'B', 'C', 'D']. |
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""" |
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df = DataFrame( |
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{ |
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col: np.random.default_rng(2).random(30, dtype=dtype) |
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for col, dtype in zip( |
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list("ABCD"), ["float32", "float32", "float32", "float64"] |
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) |
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}, |
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index=Index([f"foo_{i}" for i in range(30)], dtype=object), |
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) |
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df["C"] = df["C"].astype("float16") |
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return df |
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@pytest.fixture |
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def mixed_int_frame(): |
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""" |
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Fixture for DataFrame of different int types with index of unique strings |
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Columns are ['A', 'B', 'C', 'D']. |
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""" |
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return DataFrame( |
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{ |
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col: np.ones(30, dtype=dtype) |
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for col, dtype in zip(list("ABCD"), ["int32", "uint64", "uint8", "int64"]) |
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}, |
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index=Index([f"foo_{i}" for i in range(30)], dtype=object), |
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) |
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@pytest.fixture |
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def timezone_frame(): |
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""" |
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Fixture for DataFrame of date_range Series with different time zones |
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Columns are ['A', 'B', 'C']; some entries are missing |
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A B C |
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0 2013-01-01 2013-01-01 00:00:00-05:00 2013-01-01 00:00:00+01:00 |
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1 2013-01-02 NaT NaT |
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2 2013-01-03 2013-01-03 00:00:00-05:00 2013-01-03 00:00:00+01:00 |
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""" |
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df = DataFrame( |
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{ |
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"A": date_range("20130101", periods=3), |
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"B": date_range("20130101", periods=3, tz="US/Eastern"), |
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"C": date_range("20130101", periods=3, tz="CET"), |
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} |
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) |
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df.iloc[1, 1] = NaT |
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df.iloc[1, 2] = NaT |
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return df |
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