146 lines
4.8 KiB
Python
146 lines
4.8 KiB
Python
import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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DataFrame,
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DatetimeIndex,
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Index,
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MultiIndex,
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Series,
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concat,
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date_range,
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)
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import pandas._testing as tm
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@pytest.fixture(params=[True, False])
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def sort(request):
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"""Boolean sort keyword for concat and DataFrame.append."""
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return request.param
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class TestSeriesConcat:
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def test_concat_series(self):
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ts = tm.makeTimeSeries()
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ts.name = "foo"
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pieces = [ts[:5], ts[5:15], ts[15:]]
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result = concat(pieces)
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tm.assert_series_equal(result, ts)
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assert result.name == ts.name
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result = concat(pieces, keys=[0, 1, 2])
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expected = ts.copy()
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ts.index = DatetimeIndex(np.array(ts.index.values, dtype="M8[ns]"))
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exp_codes = [np.repeat([0, 1, 2], [len(x) for x in pieces]), np.arange(len(ts))]
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exp_index = MultiIndex(levels=[[0, 1, 2], ts.index], codes=exp_codes)
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expected.index = exp_index
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tm.assert_series_equal(result, expected)
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def test_concat_empty_and_non_empty_series_regression(self):
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# GH 18187 regression test
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s1 = Series([1])
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s2 = Series([], dtype=object)
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expected = s1
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result = pd.concat([s1, s2])
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tm.assert_series_equal(result, expected)
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def test_concat_series_axis1(self, sort=sort):
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ts = tm.makeTimeSeries()
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pieces = [ts[:-2], ts[2:], ts[2:-2]]
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result = concat(pieces, axis=1)
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expected = DataFrame(pieces).T
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tm.assert_frame_equal(result, expected)
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result = concat(pieces, keys=["A", "B", "C"], axis=1)
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expected = DataFrame(pieces, index=["A", "B", "C"]).T
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tm.assert_frame_equal(result, expected)
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# preserve series names, #2489
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s = Series(np.random.randn(5), name="A")
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s2 = Series(np.random.randn(5), name="B")
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result = concat([s, s2], axis=1)
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expected = DataFrame({"A": s, "B": s2})
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tm.assert_frame_equal(result, expected)
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s2.name = None
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result = concat([s, s2], axis=1)
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tm.assert_index_equal(result.columns, Index(["A", 0], dtype="object"))
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# must reindex, #2603
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s = Series(np.random.randn(3), index=["c", "a", "b"], name="A")
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s2 = Series(np.random.randn(4), index=["d", "a", "b", "c"], name="B")
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result = concat([s, s2], axis=1, sort=sort)
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expected = DataFrame({"A": s, "B": s2})
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tm.assert_frame_equal(result, expected)
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def test_concat_series_axis1_names_applied(self):
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# ensure names argument is not ignored on axis=1, #23490
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s = Series([1, 2, 3])
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s2 = Series([4, 5, 6])
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result = concat([s, s2], axis=1, keys=["a", "b"], names=["A"])
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expected = DataFrame(
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[[1, 4], [2, 5], [3, 6]], columns=Index(["a", "b"], name="A")
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)
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tm.assert_frame_equal(result, expected)
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result = concat([s, s2], axis=1, keys=[("a", 1), ("b", 2)], names=["A", "B"])
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expected = DataFrame(
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[[1, 4], [2, 5], [3, 6]],
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columns=MultiIndex.from_tuples([("a", 1), ("b", 2)], names=["A", "B"]),
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)
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tm.assert_frame_equal(result, expected)
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def test_concat_series_axis1_same_names_ignore_index(self):
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dates = date_range("01-Jan-2013", "01-Jan-2014", freq="MS")[0:-1]
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s1 = Series(np.random.randn(len(dates)), index=dates, name="value")
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s2 = Series(np.random.randn(len(dates)), index=dates, name="value")
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result = concat([s1, s2], axis=1, ignore_index=True)
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expected = Index(range(2))
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tm.assert_index_equal(result.columns, expected, exact=True)
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@pytest.mark.parametrize(
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"s1name,s2name", [(np.int64(190), (43, 0)), (190, (43, 0))]
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)
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def test_concat_series_name_npscalar_tuple(self, s1name, s2name):
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# GH21015
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s1 = Series({"a": 1, "b": 2}, name=s1name)
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s2 = Series({"c": 5, "d": 6}, name=s2name)
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result = pd.concat([s1, s2])
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expected = Series({"a": 1, "b": 2, "c": 5, "d": 6})
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tm.assert_series_equal(result, expected)
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def test_concat_series_partial_columns_names(self):
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# GH10698
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foo = Series([1, 2], name="foo")
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bar = Series([1, 2])
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baz = Series([4, 5])
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result = concat([foo, bar, baz], axis=1)
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expected = DataFrame(
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{"foo": [1, 2], 0: [1, 2], 1: [4, 5]}, columns=["foo", 0, 1]
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)
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tm.assert_frame_equal(result, expected)
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result = concat([foo, bar, baz], axis=1, keys=["red", "blue", "yellow"])
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expected = DataFrame(
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{"red": [1, 2], "blue": [1, 2], "yellow": [4, 5]},
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columns=["red", "blue", "yellow"],
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)
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tm.assert_frame_equal(result, expected)
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result = concat([foo, bar, baz], axis=1, ignore_index=True)
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expected = DataFrame({0: [1, 2], 1: [1, 2], 2: [4, 5]})
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tm.assert_frame_equal(result, expected)
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