119 lines
3.7 KiB
Python
119 lines
3.7 KiB
Python
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import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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from pandas import (
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DataFrame,
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DatetimeIndex,
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date_range,
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)
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import pandas._testing as tm
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class TestTranspose:
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def test_transpose_empty_preserves_datetimeindex(self):
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# GH#41382
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df = DataFrame(index=DatetimeIndex([]))
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expected = DatetimeIndex([], dtype="datetime64[ns]", freq=None)
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result1 = df.T.sum().index
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result2 = df.sum(axis=1).index
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tm.assert_index_equal(result1, expected)
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tm.assert_index_equal(result2, expected)
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def test_transpose_tzaware_1col_single_tz(self):
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# GH#26825
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dti = date_range("2016-04-05 04:30", periods=3, tz="UTC")
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df = DataFrame(dti)
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assert (df.dtypes == dti.dtype).all()
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res = df.T
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assert (res.dtypes == dti.dtype).all()
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def test_transpose_tzaware_2col_single_tz(self):
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# GH#26825
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dti = date_range("2016-04-05 04:30", periods=3, tz="UTC")
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df3 = DataFrame({"A": dti, "B": dti})
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assert (df3.dtypes == dti.dtype).all()
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res3 = df3.T
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assert (res3.dtypes == dti.dtype).all()
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def test_transpose_tzaware_2col_mixed_tz(self):
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# GH#26825
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dti = date_range("2016-04-05 04:30", periods=3, tz="UTC")
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dti2 = dti.tz_convert("US/Pacific")
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df4 = DataFrame({"A": dti, "B": dti2})
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assert (df4.dtypes == [dti.dtype, dti2.dtype]).all()
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assert (df4.T.dtypes == object).all()
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tm.assert_frame_equal(df4.T.T, df4)
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@pytest.mark.parametrize("tz", [None, "America/New_York"])
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def test_transpose_preserves_dtindex_equality_with_dst(self, tz):
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# GH#19970
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idx = date_range("20161101", "20161130", freq="4H", tz=tz)
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df = DataFrame({"a": range(len(idx)), "b": range(len(idx))}, index=idx)
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result = df.T == df.T
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expected = DataFrame(True, index=list("ab"), columns=idx)
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tm.assert_frame_equal(result, expected)
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def test_transpose_object_to_tzaware_mixed_tz(self):
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# GH#26825
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dti = date_range("2016-04-05 04:30", periods=3, tz="UTC")
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dti2 = dti.tz_convert("US/Pacific")
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# mixed all-tzaware dtypes
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df2 = DataFrame([dti, dti2])
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assert (df2.dtypes == object).all()
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res2 = df2.T
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assert (res2.dtypes == [dti.dtype, dti2.dtype]).all()
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def test_transpose_uint64(self, uint64_frame):
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result = uint64_frame.T
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expected = DataFrame(uint64_frame.values.T)
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expected.index = ["A", "B"]
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tm.assert_frame_equal(result, expected)
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def test_transpose_float(self, float_frame):
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frame = float_frame
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dft = frame.T
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for idx, series in dft.items():
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for col, value in series.items():
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if np.isnan(value):
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assert np.isnan(frame[col][idx])
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else:
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assert value == frame[col][idx]
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# mixed type
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index, data = tm.getMixedTypeDict()
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mixed = DataFrame(data, index=index)
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mixed_T = mixed.T
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for col, s in mixed_T.items():
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assert s.dtype == np.object_
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@td.skip_array_manager_invalid_test
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def test_transpose_get_view(self, float_frame):
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dft = float_frame.T
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dft.values[:, 5:10] = 5
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assert (float_frame.values[5:10] == 5).all()
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@td.skip_array_manager_invalid_test
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def test_transpose_get_view_dt64tzget_view(self):
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dti = date_range("2016-01-01", periods=6, tz="US/Pacific")
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arr = dti._data.reshape(3, 2)
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df = DataFrame(arr)
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assert df._mgr.nblocks == 1
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result = df.T
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assert result._mgr.nblocks == 1
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rtrip = result._mgr.blocks[0].values
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assert np.shares_memory(arr._ndarray, rtrip._ndarray)
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