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