import numpy as np
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from pandas import (
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DataFrame,
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date_range,
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)
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import pandas._testing as tm
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class TestEquals:
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def test_dataframe_not_equal(self):
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# see GH#28839
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df1 = DataFrame({"a": [1, 2], "b": ["s", "d"]})
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df2 = DataFrame({"a": ["s", "d"], "b": [1, 2]})
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assert df1.equals(df2) is False
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def test_equals_different_blocks(self, using_array_manager):
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# GH#9330
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df0 = DataFrame({"A": ["x", "y"], "B": [1, 2], "C": ["w", "z"]})
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df1 = df0.reset_index()[["A", "B", "C"]]
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if not using_array_manager:
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# this assert verifies that the above operations have
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# induced a block rearrangement
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assert df0._mgr.blocks[0].dtype != df1._mgr.blocks[0].dtype
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# do the real tests
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tm.assert_frame_equal(df0, df1)
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assert df0.equals(df1)
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assert df1.equals(df0)
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def test_equals(self):
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# Add object dtype column with nans
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index = np.random.random(10)
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df1 = DataFrame(np.random.random(10), index=index, columns=["floats"])
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df1["text"] = "the sky is so blue. we could use more chocolate.".split()
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df1["start"] = date_range("2000-1-1", periods=10, freq="T")
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df1["end"] = date_range("2000-1-1", periods=10, freq="D")
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df1["diff"] = df1["end"] - df1["start"]
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# Explicitly cast to object, to avoid implicit cast when setting np.nan
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df1["bool"] = (np.arange(10) % 3 == 0).astype(object)
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df1.loc[::2] = np.nan
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df2 = df1.copy()
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assert df1["text"].equals(df2["text"])
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assert df1["start"].equals(df2["start"])
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assert df1["end"].equals(df2["end"])
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assert df1["diff"].equals(df2["diff"])
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assert df1["bool"].equals(df2["bool"])
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assert df1.equals(df2)
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assert not df1.equals(object)
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# different dtype
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different = df1.copy()
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different["floats"] = different["floats"].astype("float32")
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assert not df1.equals(different)
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# different index
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different_index = -index
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different = df2.set_index(different_index)
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assert not df1.equals(different)
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# different columns
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different = df2.copy()
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different.columns = df2.columns[::-1]
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assert not df1.equals(different)
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# DatetimeIndex
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index = date_range("2000-1-1", periods=10, freq="T")
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df1 = df1.set_index(index)
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df2 = df1.copy()
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assert df1.equals(df2)
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# MultiIndex
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df3 = df1.set_index(["text"], append=True)
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df2 = df1.set_index(["text"], append=True)
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assert df3.equals(df2)
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df2 = df1.set_index(["floats"], append=True)
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assert not df3.equals(df2)
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# NaN in index
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df3 = df1.set_index(["floats"], append=True)
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df2 = df1.set_index(["floats"], append=True)
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assert df3.equals(df2)
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