from datetime import timezone import numpy as np import pytest import pandas as pd from pandas import ( DataFrame, Index, Series, date_range, ) import pandas._testing as tm class TestDataFrameAlign: def test_frame_align_aware(self): idx1 = date_range("2001", periods=5, freq="H", tz="US/Eastern") idx2 = date_range("2001", periods=5, freq="2H", tz="US/Eastern") df1 = DataFrame(np.random.randn(len(idx1), 3), idx1) df2 = DataFrame(np.random.randn(len(idx2), 3), idx2) new1, new2 = df1.align(df2) assert df1.index.tz == new1.index.tz assert df2.index.tz == new2.index.tz # different timezones convert to UTC # frame with frame df1_central = df1.tz_convert("US/Central") new1, new2 = df1.align(df1_central) assert new1.index.tz is timezone.utc assert new2.index.tz is timezone.utc # frame with Series new1, new2 = df1.align(df1_central[0], axis=0) assert new1.index.tz is timezone.utc assert new2.index.tz is timezone.utc df1[0].align(df1_central, axis=0) assert new1.index.tz is timezone.utc assert new2.index.tz is timezone.utc def test_align_float(self, float_frame, using_copy_on_write): af, bf = float_frame.align(float_frame) assert af._mgr is not float_frame._mgr af, bf = float_frame.align(float_frame, copy=False) if not using_copy_on_write: assert af._mgr is float_frame._mgr else: assert af._mgr is not float_frame._mgr # axis = 0 other = float_frame.iloc[:-5, :3] af, bf = float_frame.align(other, axis=0, fill_value=-1) tm.assert_index_equal(bf.columns, other.columns) # test fill value join_idx = float_frame.index.join(other.index) diff_a = float_frame.index.difference(join_idx) diff_a_vals = af.reindex(diff_a).values assert (diff_a_vals == -1).all() af, bf = float_frame.align(other, join="right", axis=0) tm.assert_index_equal(bf.columns, other.columns) tm.assert_index_equal(bf.index, other.index) tm.assert_index_equal(af.index, other.index) # axis = 1 other = float_frame.iloc[:-5, :3].copy() af, bf = float_frame.align(other, axis=1) tm.assert_index_equal(bf.columns, float_frame.columns) tm.assert_index_equal(bf.index, other.index) # test fill value join_idx = float_frame.index.join(other.index) diff_a = float_frame.index.difference(join_idx) diff_a_vals = af.reindex(diff_a).values assert (diff_a_vals == -1).all() af, bf = float_frame.align(other, join="inner", axis=1) tm.assert_index_equal(bf.columns, other.columns) af, bf = float_frame.align(other, join="inner", axis=1, method="pad") tm.assert_index_equal(bf.columns, other.columns) af, bf = float_frame.align( other.iloc[:, 0], join="inner", axis=1, method=None, fill_value=None ) tm.assert_index_equal(bf.index, Index([])) af, bf = float_frame.align( other.iloc[:, 0], join="inner", axis=1, method=None, fill_value=0 ) tm.assert_index_equal(bf.index, Index([])) # Try to align DataFrame to Series along bad axis msg = "No axis named 2 for object type DataFrame" with pytest.raises(ValueError, match=msg): float_frame.align(af.iloc[0, :3], join="inner", axis=2) # align dataframe to series with broadcast or not idx = float_frame.index s = Series(range(len(idx)), index=idx) left, right = float_frame.align(s, axis=0) tm.assert_index_equal(left.index, float_frame.index) tm.assert_index_equal(right.index, float_frame.index) assert isinstance(right, Series) left, right = float_frame.align(s, broadcast_axis=1) tm.assert_index_equal(left.index, float_frame.index) expected = {c: s for c in float_frame.columns} expected = DataFrame( expected, index=float_frame.index, columns=float_frame.columns ) tm.assert_frame_equal(right, expected) # see gh-9558 df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) result = df[df["a"] == 2] expected = DataFrame([[2, 5]], index=[1], columns=["a", "b"]) tm.assert_frame_equal(result, expected) result = df.where(df["a"] == 2, 0) expected = DataFrame({"a": [0, 2, 0], "b": [0, 5, 0]}) tm.assert_frame_equal(result, expected) def test_align_int(self, int_frame): # test other non-float types other = DataFrame(index=range(5), columns=["A", "B", "C"]) af, bf = int_frame.align(other, join="inner", axis=1, method="pad") tm.assert_index_equal(bf.columns, other.columns) def test_align_mixed_type(self, float_string_frame): af, bf = float_string_frame.align( float_string_frame, join="inner", axis=1, method="pad" ) tm.assert_index_equal(bf.columns, float_string_frame.columns) def test_align_mixed_float(self, mixed_float_frame): # mixed floats/ints other = DataFrame(index=range(5), columns=["A", "B", "C"]) af, bf = mixed_float_frame.align( other.iloc[:, 0], join="inner", axis=1, method=None, fill_value=0 ) tm.assert_index_equal(bf.index, Index([])) def test_align_mixed_int(self, mixed_int_frame): other = DataFrame(index=range(5), columns=["A", "B", "C"]) af, bf = mixed_int_frame.align( other.iloc[:, 0], join="inner", axis=1, method=None, fill_value=0 ) tm.assert_index_equal(bf.index, Index([])) @pytest.mark.parametrize( "l_ordered,r_ordered,expected", [ [True, True, pd.CategoricalIndex], [True, False, Index], [False, True, Index], [False, False, pd.CategoricalIndex], ], ) def test_align_categorical(self, l_ordered, r_ordered, expected): # GH-28397 df_1 = DataFrame( { "A": np.arange(6, dtype="int64"), "B": Series(list("aabbca")).astype( pd.CategoricalDtype(list("cab"), ordered=l_ordered) ), } ).set_index("B") df_2 = DataFrame( { "A": np.arange(5, dtype="int64"), "B": Series(list("babca")).astype( pd.CategoricalDtype(list("cab"), ordered=r_ordered) ), } ).set_index("B") aligned_1, aligned_2 = df_1.align(df_2) assert isinstance(aligned_1.index, expected) assert isinstance(aligned_2.index, expected) tm.assert_index_equal(aligned_1.index, aligned_2.index) def test_align_multiindex(self): # GH#10665 # same test cases as test_align_multiindex in test_series.py midx = pd.MultiIndex.from_product( [range(2), range(3), range(2)], names=("a", "b", "c") ) idx = Index(range(2), name="b") df1 = DataFrame(np.arange(12, dtype="int64"), index=midx) df2 = DataFrame(np.arange(2, dtype="int64"), index=idx) # these must be the same results (but flipped) res1l, res1r = df1.align(df2, join="left") res2l, res2r = df2.align(df1, join="right") expl = df1 tm.assert_frame_equal(expl, res1l) tm.assert_frame_equal(expl, res2r) expr = DataFrame([0, 0, 1, 1, np.nan, np.nan] * 2, index=midx) tm.assert_frame_equal(expr, res1r) tm.assert_frame_equal(expr, res2l) res1l, res1r = df1.align(df2, join="right") res2l, res2r = df2.align(df1, join="left") exp_idx = pd.MultiIndex.from_product( [range(2), range(2), range(2)], names=("a", "b", "c") ) expl = DataFrame([0, 1, 2, 3, 6, 7, 8, 9], index=exp_idx) tm.assert_frame_equal(expl, res1l) tm.assert_frame_equal(expl, res2r) expr = DataFrame([0, 0, 1, 1] * 2, index=exp_idx) tm.assert_frame_equal(expr, res1r) tm.assert_frame_equal(expr, res2l) def test_align_series_combinations(self): df = DataFrame({"a": [1, 3, 5], "b": [1, 3, 5]}, index=list("ACE")) s = Series([1, 2, 4], index=list("ABD"), name="x") # frame + series res1, res2 = df.align(s, axis=0) exp1 = DataFrame( {"a": [1, np.nan, 3, np.nan, 5], "b": [1, np.nan, 3, np.nan, 5]}, index=list("ABCDE"), ) exp2 = Series([1, 2, np.nan, 4, np.nan], index=list("ABCDE"), name="x") tm.assert_frame_equal(res1, exp1) tm.assert_series_equal(res2, exp2) # series + frame res1, res2 = s.align(df) tm.assert_series_equal(res1, exp2) tm.assert_frame_equal(res2, exp1) def test_multiindex_align_to_series_with_common_index_level(self): # GH-46001 foo_index = Index([1, 2, 3], name="foo") bar_index = Index([1, 2], name="bar") series = Series([1, 2], index=bar_index, name="foo_series") df = DataFrame( {"col": np.arange(6)}, index=pd.MultiIndex.from_product([foo_index, bar_index]), ) expected_r = Series([1, 2] * 3, index=df.index, name="foo_series") result_l, result_r = df.align(series, axis=0) tm.assert_frame_equal(result_l, df) tm.assert_series_equal(result_r, expected_r) def test_multiindex_align_to_series_with_common_index_level_missing_in_left(self): # GH-46001 foo_index = Index([1, 2, 3], name="foo") bar_index = Index([1, 2], name="bar") series = Series( [1, 2, 3, 4], index=Index([1, 2, 3, 4], name="bar"), name="foo_series" ) df = DataFrame( {"col": np.arange(6)}, index=pd.MultiIndex.from_product([foo_index, bar_index]), ) expected_r = Series([1, 2] * 3, index=df.index, name="foo_series") result_l, result_r = df.align(series, axis=0) tm.assert_frame_equal(result_l, df) tm.assert_series_equal(result_r, expected_r) def test_multiindex_align_to_series_with_common_index_level_missing_in_right(self): # GH-46001 foo_index = Index([1, 2, 3], name="foo") bar_index = Index([1, 2, 3, 4], name="bar") series = Series([1, 2], index=Index([1, 2], name="bar"), name="foo_series") df = DataFrame( {"col": np.arange(12)}, index=pd.MultiIndex.from_product([foo_index, bar_index]), ) expected_r = Series( [1, 2, np.nan, np.nan] * 3, index=df.index, name="foo_series" ) result_l, result_r = df.align(series, axis=0) tm.assert_frame_equal(result_l, df) tm.assert_series_equal(result_r, expected_r) def test_multiindex_align_to_series_with_common_index_level_missing_in_both(self): # GH-46001 foo_index = Index([1, 2, 3], name="foo") bar_index = Index([1, 3, 4], name="bar") series = Series( [1, 2, 3], index=Index([1, 2, 4], name="bar"), name="foo_series" ) df = DataFrame( {"col": np.arange(9)}, index=pd.MultiIndex.from_product([foo_index, bar_index]), ) expected_r = Series([1, np.nan, 3] * 3, index=df.index, name="foo_series") result_l, result_r = df.align(series, axis=0) tm.assert_frame_equal(result_l, df) tm.assert_series_equal(result_r, expected_r) def test_multiindex_align_to_series_with_common_index_level_non_unique_cols(self): # GH-46001 foo_index = Index([1, 2, 3], name="foo") bar_index = Index([1, 2], name="bar") series = Series([1, 2], index=bar_index, name="foo_series") df = DataFrame( np.arange(18).reshape(6, 3), index=pd.MultiIndex.from_product([foo_index, bar_index]), ) df.columns = ["cfoo", "cbar", "cfoo"] expected = Series([1, 2] * 3, index=df.index, name="foo_series") result_left, result_right = df.align(series, axis=0) tm.assert_series_equal(result_right, expected) tm.assert_index_equal(result_left.columns, df.columns) def test_missing_axis_specification_exception(self): df = DataFrame(np.arange(50).reshape((10, 5))) series = Series(np.arange(5)) with pytest.raises(ValueError, match=r"axis=0 or 1"): df.align(series) def _check_align(self, a, b, axis, fill_axis, how, method, limit=None): aa, ab = a.align( b, axis=axis, join=how, method=method, limit=limit, fill_axis=fill_axis ) join_index, join_columns = None, None ea, eb = a, b if axis is None or axis == 0: join_index = a.index.join(b.index, how=how) ea = ea.reindex(index=join_index) eb = eb.reindex(index=join_index) if axis is None or axis == 1: join_columns = a.columns.join(b.columns, how=how) ea = ea.reindex(columns=join_columns) eb = eb.reindex(columns=join_columns) ea = ea.fillna(axis=fill_axis, method=method, limit=limit) eb = eb.fillna(axis=fill_axis, method=method, limit=limit) tm.assert_frame_equal(aa, ea) tm.assert_frame_equal(ab, eb) @pytest.mark.parametrize("meth", ["pad", "bfill"]) @pytest.mark.parametrize("ax", [0, 1, None]) @pytest.mark.parametrize("fax", [0, 1]) @pytest.mark.parametrize("how", ["inner", "outer", "left", "right"]) def test_align_fill_method(self, how, meth, ax, fax, float_frame): df = float_frame self._check_align_fill(df, how, meth, ax, fax) def _check_align_fill(self, frame, kind, meth, ax, fax): left = frame.iloc[0:4, :10] right = frame.iloc[2:, 6:] empty = frame.iloc[:0, :0] self._check_align(left, right, axis=ax, fill_axis=fax, how=kind, method=meth) self._check_align( left, right, axis=ax, fill_axis=fax, how=kind, method=meth, limit=1 ) # empty left self._check_align(empty, right, axis=ax, fill_axis=fax, how=kind, method=meth) self._check_align( empty, right, axis=ax, fill_axis=fax, how=kind, method=meth, limit=1 ) # empty right self._check_align(left, empty, axis=ax, fill_axis=fax, how=kind, method=meth) self._check_align( left, empty, axis=ax, fill_axis=fax, how=kind, method=meth, limit=1 ) # both empty self._check_align(empty, empty, axis=ax, fill_axis=fax, how=kind, method=meth) self._check_align( empty, empty, axis=ax, fill_axis=fax, how=kind, method=meth, limit=1 ) def test_align_series_check_copy(self): # GH# df = DataFrame({0: [1, 2]}) ser = Series([1], name=0) expected = ser.copy() result, other = df.align(ser, axis=1) ser.iloc[0] = 100 tm.assert_series_equal(other, expected) def test_align_identical_different_object(self): # GH#51032 df = DataFrame({"a": [1, 2]}) ser = Series([3, 4]) result, result2 = df.align(ser, axis=0) tm.assert_frame_equal(result, df) tm.assert_series_equal(result2, ser) assert df is not result assert ser is not result2 def test_align_identical_different_object_columns(self): # GH#51032 df = DataFrame({"a": [1, 2]}) ser = Series([1], index=["a"]) result, result2 = df.align(ser, axis=1) tm.assert_frame_equal(result, df) tm.assert_series_equal(result2, ser) assert df is not result assert ser is not result2