390 lines
12 KiB
Python
390 lines
12 KiB
Python
from copy import deepcopy
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import inspect
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import pydoc
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import numpy as np
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import pytest
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from pandas._config.config import option_context
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import pandas.util._test_decorators as td
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from pandas.util._test_decorators import (
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async_mark,
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skip_if_no,
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)
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import pandas as pd
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from pandas import (
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DataFrame,
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Series,
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date_range,
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timedelta_range,
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)
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import pandas._testing as tm
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class TestDataFrameMisc:
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def test_getitem_pop_assign_name(self, float_frame):
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s = float_frame["A"]
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assert s.name == "A"
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s = float_frame.pop("A")
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assert s.name == "A"
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s = float_frame.loc[:, "B"]
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assert s.name == "B"
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s2 = s.loc[:]
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assert s2.name == "B"
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def test_get_axis(self, float_frame):
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f = float_frame
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assert f._get_axis_number(0) == 0
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assert f._get_axis_number(1) == 1
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assert f._get_axis_number("index") == 0
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assert f._get_axis_number("rows") == 0
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assert f._get_axis_number("columns") == 1
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assert f._get_axis_name(0) == "index"
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assert f._get_axis_name(1) == "columns"
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assert f._get_axis_name("index") == "index"
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assert f._get_axis_name("rows") == "index"
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assert f._get_axis_name("columns") == "columns"
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assert f._get_axis(0) is f.index
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assert f._get_axis(1) is f.columns
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with pytest.raises(ValueError, match="No axis named"):
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f._get_axis_number(2)
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with pytest.raises(ValueError, match="No axis.*foo"):
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f._get_axis_name("foo")
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with pytest.raises(ValueError, match="No axis.*None"):
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f._get_axis_name(None)
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with pytest.raises(ValueError, match="No axis named"):
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f._get_axis_number(None)
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def test_column_contains_raises(self, float_frame):
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with pytest.raises(TypeError, match="unhashable type: 'Index'"):
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float_frame.columns in float_frame
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def test_tab_completion(self):
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# DataFrame whose columns are identifiers shall have them in __dir__.
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df = DataFrame([list("abcd"), list("efgh")], columns=list("ABCD"))
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for key in list("ABCD"):
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assert key in dir(df)
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assert isinstance(df.__getitem__("A"), Series)
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# DataFrame whose first-level columns are identifiers shall have
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# them in __dir__.
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df = DataFrame(
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[list("abcd"), list("efgh")],
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columns=pd.MultiIndex.from_tuples(list(zip("ABCD", "EFGH"))),
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)
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for key in list("ABCD"):
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assert key in dir(df)
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for key in list("EFGH"):
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assert key not in dir(df)
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assert isinstance(df.__getitem__("A"), DataFrame)
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def test_display_max_dir_items(self):
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# display.max_dir_items increaes the number of columns that are in __dir__.
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columns = ["a" + str(i) for i in range(420)]
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values = [range(420), range(420)]
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df = DataFrame(values, columns=columns)
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# The default value for display.max_dir_items is 100
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assert "a99" in dir(df)
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assert "a100" not in dir(df)
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with option_context("display.max_dir_items", 300):
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df = DataFrame(values, columns=columns)
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assert "a299" in dir(df)
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assert "a300" not in dir(df)
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with option_context("display.max_dir_items", None):
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df = DataFrame(values, columns=columns)
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assert "a419" in dir(df)
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def test_not_hashable(self):
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empty_frame = DataFrame()
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df = DataFrame([1])
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msg = "unhashable type: 'DataFrame'"
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with pytest.raises(TypeError, match=msg):
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hash(df)
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with pytest.raises(TypeError, match=msg):
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hash(empty_frame)
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def test_column_name_contains_unicode_surrogate(self):
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# GH 25509
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colname = "\ud83d"
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df = DataFrame({colname: []})
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# this should not crash
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assert colname not in dir(df)
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assert df.columns[0] == colname
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def test_new_empty_index(self):
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df1 = DataFrame(np.random.randn(0, 3))
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df2 = DataFrame(np.random.randn(0, 3))
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df1.index.name = "foo"
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assert df2.index.name is None
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def test_get_agg_axis(self, float_frame):
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cols = float_frame._get_agg_axis(0)
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assert cols is float_frame.columns
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idx = float_frame._get_agg_axis(1)
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assert idx is float_frame.index
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msg = r"Axis must be 0 or 1 \(got 2\)"
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with pytest.raises(ValueError, match=msg):
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float_frame._get_agg_axis(2)
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def test_empty(self, float_frame, float_string_frame):
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empty_frame = DataFrame()
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assert empty_frame.empty
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assert not float_frame.empty
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assert not float_string_frame.empty
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# corner case
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df = DataFrame({"A": [1.0, 2.0, 3.0], "B": ["a", "b", "c"]}, index=np.arange(3))
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del df["A"]
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assert not df.empty
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def test_len(self, float_frame):
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assert len(float_frame) == len(float_frame.index)
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# single block corner case
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arr = float_frame[["A", "B"]].values
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expected = float_frame.reindex(columns=["A", "B"]).values
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tm.assert_almost_equal(arr, expected)
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def test_axis_aliases(self, float_frame):
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f = float_frame
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# reg name
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expected = f.sum(axis=0)
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result = f.sum(axis="index")
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tm.assert_series_equal(result, expected)
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expected = f.sum(axis=1)
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result = f.sum(axis="columns")
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tm.assert_series_equal(result, expected)
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def test_class_axis(self):
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# GH 18147
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# no exception and no empty docstring
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assert pydoc.getdoc(DataFrame.index)
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assert pydoc.getdoc(DataFrame.columns)
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def test_series_put_names(self, float_string_frame):
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series = float_string_frame._series
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for k, v in series.items():
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assert v.name == k
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def test_empty_nonzero(self):
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df = DataFrame([1, 2, 3])
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assert not df.empty
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df = DataFrame(index=[1], columns=[1])
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assert not df.empty
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df = DataFrame(index=["a", "b"], columns=["c", "d"]).dropna()
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assert df.empty
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assert df.T.empty
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@pytest.mark.parametrize(
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"df",
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[
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DataFrame(),
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DataFrame(index=[1]),
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DataFrame(columns=[1]),
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DataFrame({1: []}),
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],
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)
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def test_empty_like(self, df):
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assert df.empty
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assert df.T.empty
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def test_with_datetimelikes(self):
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df = DataFrame(
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{
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"A": date_range("20130101", periods=10),
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"B": timedelta_range("1 day", periods=10),
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}
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)
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t = df.T
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result = t.dtypes.value_counts()
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expected = Series({np.dtype("object"): 10})
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tm.assert_series_equal(result, expected)
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def test_deepcopy(self, float_frame):
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cp = deepcopy(float_frame)
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series = cp["A"]
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series[:] = 10
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for idx, value in series.items():
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assert float_frame["A"][idx] != value
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def test_inplace_return_self(self):
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# GH 1893
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data = DataFrame(
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{"a": ["foo", "bar", "baz", "qux"], "b": [0, 0, 1, 1], "c": [1, 2, 3, 4]}
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)
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def _check_f(base, f):
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result = f(base)
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assert result is None
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# -----DataFrame-----
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# set_index
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f = lambda x: x.set_index("a", inplace=True)
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_check_f(data.copy(), f)
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# reset_index
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f = lambda x: x.reset_index(inplace=True)
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_check_f(data.set_index("a"), f)
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# drop_duplicates
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f = lambda x: x.drop_duplicates(inplace=True)
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_check_f(data.copy(), f)
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# sort
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f = lambda x: x.sort_values("b", inplace=True)
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_check_f(data.copy(), f)
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# sort_index
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f = lambda x: x.sort_index(inplace=True)
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_check_f(data.copy(), f)
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# fillna
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f = lambda x: x.fillna(0, inplace=True)
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_check_f(data.copy(), f)
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# replace
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f = lambda x: x.replace(1, 0, inplace=True)
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_check_f(data.copy(), f)
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# rename
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f = lambda x: x.rename({1: "foo"}, inplace=True)
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_check_f(data.copy(), f)
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# -----Series-----
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d = data.copy()["c"]
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# reset_index
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f = lambda x: x.reset_index(inplace=True, drop=True)
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_check_f(data.set_index("a")["c"], f)
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# fillna
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f = lambda x: x.fillna(0, inplace=True)
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_check_f(d.copy(), f)
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# replace
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f = lambda x: x.replace(1, 0, inplace=True)
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_check_f(d.copy(), f)
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# rename
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f = lambda x: x.rename({1: "foo"}, inplace=True)
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_check_f(d.copy(), f)
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@async_mark()
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@td.check_file_leaks
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async def test_tab_complete_warning(self, ip, frame_or_series):
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# GH 16409
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pytest.importorskip("IPython", minversion="6.0.0")
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from IPython.core.completer import provisionalcompleter
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if frame_or_series is DataFrame:
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code = "from pandas import DataFrame; obj = DataFrame()"
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else:
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code = "from pandas import Series; obj = Series(dtype=object)"
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await ip.run_code(code)
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# GH 31324 newer jedi version raises Deprecation warning;
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# appears resolved 2021-02-02
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with tm.assert_produces_warning(None):
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with provisionalcompleter("ignore"):
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list(ip.Completer.completions("obj.", 1))
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def test_attrs(self):
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df = DataFrame({"A": [2, 3]})
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assert df.attrs == {}
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df.attrs["version"] = 1
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result = df.rename(columns=str)
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assert result.attrs == {"version": 1}
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@pytest.mark.parametrize("allows_duplicate_labels", [True, False, None])
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def test_set_flags(
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self, allows_duplicate_labels, frame_or_series, using_copy_on_write
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):
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obj = DataFrame({"A": [1, 2]})
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key = (0, 0)
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if frame_or_series is Series:
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obj = obj["A"]
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key = 0
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result = obj.set_flags(allows_duplicate_labels=allows_duplicate_labels)
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if allows_duplicate_labels is None:
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# We don't update when it's not provided
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assert result.flags.allows_duplicate_labels is True
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else:
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assert result.flags.allows_duplicate_labels is allows_duplicate_labels
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# We made a copy
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assert obj is not result
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# We didn't mutate obj
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assert obj.flags.allows_duplicate_labels is True
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# But we didn't copy data
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if frame_or_series is Series:
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assert np.may_share_memory(obj.values, result.values)
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else:
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assert np.may_share_memory(obj["A"].values, result["A"].values)
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result.iloc[key] = 0
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if using_copy_on_write:
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assert obj.iloc[key] == 1
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else:
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assert obj.iloc[key] == 0
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# set back to 1 for test below
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result.iloc[key] = 1
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# Now we do copy.
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result = obj.set_flags(
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copy=True, allows_duplicate_labels=allows_duplicate_labels
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)
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result.iloc[key] = 10
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assert obj.iloc[key] == 1
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def test_constructor_expanddim(self):
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# GH#33628 accessing _constructor_expanddim should not raise NotImplementedError
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# GH38782 pandas has no container higher than DataFrame (two-dim), so
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# DataFrame._constructor_expand_dim, doesn't make sense, so is removed.
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df = DataFrame()
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msg = "'DataFrame' object has no attribute '_constructor_expanddim'"
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with pytest.raises(AttributeError, match=msg):
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df._constructor_expanddim(np.arange(27).reshape(3, 3, 3))
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@skip_if_no("jinja2")
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def test_inspect_getmembers(self):
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# GH38740
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df = DataFrame()
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with tm.assert_produces_warning(None):
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inspect.getmembers(df)
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def test_dataframe_iteritems_deprecated(self):
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df = DataFrame([1])
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with tm.assert_produces_warning(FutureWarning):
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next(df.iteritems())
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