517 lines
17 KiB
Python
517 lines
17 KiB
Python
from string import ascii_letters as letters
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import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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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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Timestamp,
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date_range,
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option_context,
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)
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import pandas._testing as tm
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import pandas.core.common as com
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msg = "A value is trying to be set on a copy of a slice from a DataFrame"
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def random_text(nobs=100):
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# Construct a DataFrame where each row is a random slice from 'letters'
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idxs = np.random.randint(len(letters), size=(nobs, 2))
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idxs.sort(axis=1)
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strings = [letters[x[0] : x[1]] for x in idxs]
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return DataFrame(strings, columns=["letters"])
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class TestCaching:
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def test_slice_consolidate_invalidate_item_cache(self):
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# this is chained assignment, but will 'work'
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with option_context("chained_assignment", None):
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# #3970
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df = DataFrame({"aa": np.arange(5), "bb": [2.2] * 5})
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# Creates a second float block
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df["cc"] = 0.0
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# caches a reference to the 'bb' series
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df["bb"]
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# repr machinery triggers consolidation
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repr(df)
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# Assignment to wrong series
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df["bb"].iloc[0] = 0.17
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df._clear_item_cache()
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tm.assert_almost_equal(df["bb"][0], 0.17)
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@pytest.mark.parametrize("do_ref", [True, False])
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def test_setitem_cache_updating(self, do_ref):
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# GH 5424
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cont = ["one", "two", "three", "four", "five", "six", "seven"]
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df = DataFrame({"a": cont, "b": cont[3:] + cont[:3], "c": np.arange(7)})
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# ref the cache
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if do_ref:
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df.loc[0, "c"]
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# set it
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df.loc[7, "c"] = 1
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assert df.loc[0, "c"] == 0.0
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assert df.loc[7, "c"] == 1.0
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def test_setitem_cache_updating_slices(self):
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# GH 7084
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# not updating cache on series setting with slices
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expected = DataFrame(
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{"A": [600, 600, 600]}, index=date_range("5/7/2014", "5/9/2014")
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)
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out = DataFrame({"A": [0, 0, 0]}, index=date_range("5/7/2014", "5/9/2014"))
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df = DataFrame({"C": ["A", "A", "A"], "D": [100, 200, 300]})
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# loop through df to update out
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six = Timestamp("5/7/2014")
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eix = Timestamp("5/9/2014")
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for ix, row in df.iterrows():
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out.loc[six:eix, row["C"]] = out.loc[six:eix, row["C"]] + row["D"]
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tm.assert_frame_equal(out, expected)
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tm.assert_series_equal(out["A"], expected["A"])
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# try via a chain indexing
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# this actually works
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out = DataFrame({"A": [0, 0, 0]}, index=date_range("5/7/2014", "5/9/2014"))
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for ix, row in df.iterrows():
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v = out[row["C"]][six:eix] + row["D"]
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out[row["C"]][six:eix] = v
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tm.assert_frame_equal(out, expected)
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tm.assert_series_equal(out["A"], expected["A"])
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out = DataFrame({"A": [0, 0, 0]}, index=date_range("5/7/2014", "5/9/2014"))
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for ix, row in df.iterrows():
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out.loc[six:eix, row["C"]] += row["D"]
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tm.assert_frame_equal(out, expected)
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tm.assert_series_equal(out["A"], expected["A"])
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def test_altering_series_clears_parent_cache(self):
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# GH #33675
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df = DataFrame([[1, 2], [3, 4]], index=["a", "b"], columns=["A", "B"])
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ser = df["A"]
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assert "A" in df._item_cache
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# Adding a new entry to ser swaps in a new array, so "A" needs to
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# be removed from df._item_cache
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ser["c"] = 5
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assert len(ser) == 3
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assert "A" not in df._item_cache
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assert df["A"] is not ser
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assert len(df["A"]) == 2
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class TestChaining:
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def test_setitem_chained_setfault(self):
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# GH6026
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data = ["right", "left", "left", "left", "right", "left", "timeout"]
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mdata = ["right", "left", "left", "left", "right", "left", "none"]
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df = DataFrame({"response": np.array(data)})
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mask = df.response == "timeout"
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df.response[mask] = "none"
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tm.assert_frame_equal(df, DataFrame({"response": mdata}))
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recarray = np.rec.fromarrays([data], names=["response"])
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df = DataFrame(recarray)
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mask = df.response == "timeout"
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df.response[mask] = "none"
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tm.assert_frame_equal(df, DataFrame({"response": mdata}))
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df = DataFrame({"response": data, "response1": data})
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mask = df.response == "timeout"
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df.response[mask] = "none"
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tm.assert_frame_equal(df, DataFrame({"response": mdata, "response1": data}))
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# GH 6056
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expected = DataFrame({"A": [np.nan, "bar", "bah", "foo", "bar"]})
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df = DataFrame({"A": np.array(["foo", "bar", "bah", "foo", "bar"])})
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df["A"].iloc[0] = np.nan
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result = df.head()
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tm.assert_frame_equal(result, expected)
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df = DataFrame({"A": np.array(["foo", "bar", "bah", "foo", "bar"])})
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df.A.iloc[0] = np.nan
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result = df.head()
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tm.assert_frame_equal(result, expected)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment(self):
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pd.set_option("chained_assignment", "raise")
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# work with the chain
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expected = DataFrame([[-5, 1], [-6, 3]], columns=list("AB"))
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df = DataFrame(np.arange(4).reshape(2, 2), columns=list("AB"), dtype="int64")
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assert df._is_copy is None
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df["A"][0] = -5
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df["A"][1] = -6
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tm.assert_frame_equal(df, expected)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_raises(self, using_array_manager):
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# test with the chaining
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df = DataFrame(
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{
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"A": Series(range(2), dtype="int64"),
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"B": np.array(np.arange(2, 4), dtype=np.float64),
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}
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)
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assert df._is_copy is None
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if not using_array_manager:
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df["A"][0] = -5
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df["A"][1] = np.nan
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assert df["A"]._is_copy is None
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else:
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# INFO(ArrayManager) for ArrayManager it doesn't matter that it's
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# a mixed dataframe
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df["A"][0] = -5
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df["A"][1] = -6
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expected = DataFrame([[-5, 2], [-6, 3]], columns=list("AB"))
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expected["B"] = expected["B"].astype("float64")
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tm.assert_frame_equal(df, expected)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_fails(self):
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# Using a copy (the chain), fails
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df = DataFrame(
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{
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"A": Series(range(2), dtype="int64"),
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"B": np.array(np.arange(2, 4), dtype=np.float64),
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}
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)
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df.loc[0]["A"] = -5
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_doc_example(self):
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# Doc example
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df = DataFrame(
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{
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"a": ["one", "one", "two", "three", "two", "one", "six"],
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"c": Series(range(7), dtype="int64"),
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}
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)
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assert df._is_copy is None
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with pytest.raises(com.SettingWithCopyError, match=msg):
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indexer = df.a.str.startswith("o")
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df[indexer]["c"] = 42
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_object_dtype(self, using_array_manager):
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expected = DataFrame({"A": [111, "bbb", "ccc"], "B": [1, 2, 3]})
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df = DataFrame({"A": ["aaa", "bbb", "ccc"], "B": [1, 2, 3]})
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df.loc[0]["A"] = 111
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if not using_array_manager:
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df["A"][0] = 111
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df.loc[0, "A"] = 111
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else:
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# INFO(ArrayManager) for ArrayManager it doesn't matter that it's
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# a mixed dataframe
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df["A"][0] = 111
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tm.assert_frame_equal(df, expected)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_is_copy_pickle(self):
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# gh-5475: Make sure that is_copy is picked up reconstruction
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df = DataFrame({"A": [1, 2]})
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assert df._is_copy is None
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with tm.ensure_clean("__tmp__pickle") as path:
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df.to_pickle(path)
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df2 = pd.read_pickle(path)
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df2["B"] = df2["A"]
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df2["B"] = df2["A"]
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_setting_entire_column(self):
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# gh-5597: a spurious raise as we are setting the entire column here
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df = random_text(100000)
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# Always a copy
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x = df.iloc[[0, 1, 2]]
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assert x._is_copy is not None
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x = df.iloc[[0, 1, 2, 4]]
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assert x._is_copy is not None
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# Explicitly copy
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indexer = df.letters.apply(lambda x: len(x) > 10)
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df = df.loc[indexer].copy()
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assert df._is_copy is None
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df["letters"] = df["letters"].apply(str.lower)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_implicit_take(self):
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# Implicitly take
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df = random_text(100000)
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indexer = df.letters.apply(lambda x: len(x) > 10)
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df = df.loc[indexer]
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assert df._is_copy is not None
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df["letters"] = df["letters"].apply(str.lower)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_implicit_take2(self):
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# Implicitly take 2
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df = random_text(100000)
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indexer = df.letters.apply(lambda x: len(x) > 10)
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df = df.loc[indexer]
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assert df._is_copy is not None
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df.loc[:, "letters"] = df["letters"].apply(str.lower)
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# Should be ok even though it's a copy!
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assert df._is_copy is None
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df["letters"] = df["letters"].apply(str.lower)
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assert df._is_copy is None
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_str(self):
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df = random_text(100000)
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indexer = df.letters.apply(lambda x: len(x) > 10)
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df.loc[indexer, "letters"] = df.loc[indexer, "letters"].apply(str.lower)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_is_copy(self):
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# an identical take, so no copy
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df = DataFrame({"a": [1]}).dropna()
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assert df._is_copy is None
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df["a"] += 1
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_sorting(self):
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df = DataFrame(np.random.randn(10, 4))
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ser = df.iloc[:, 0].sort_values()
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tm.assert_series_equal(ser, df.iloc[:, 0].sort_values())
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tm.assert_series_equal(ser, df[0].sort_values())
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_false_positives(self):
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# see gh-6025: false positives
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df = DataFrame({"column1": ["a", "a", "a"], "column2": [4, 8, 9]})
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str(df)
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df["column1"] = df["column1"] + "b"
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str(df)
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df = df[df["column2"] != 8]
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str(df)
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df["column1"] = df["column1"] + "c"
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str(df)
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_undefined_column(self):
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# from SO:
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# https://stackoverflow.com/questions/24054495/potential-bug-setting-value-for-undefined-column-using-iloc
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df = DataFrame(np.arange(0, 9), columns=["count"])
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df["group"] = "b"
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df.iloc[0:5]["group"] = "a"
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@pytest.mark.arm_slow
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def test_detect_chained_assignment_changing_dtype(self, using_array_manager):
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# Mixed type setting but same dtype & changing dtype
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df = DataFrame(
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{
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"A": date_range("20130101", periods=5),
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"B": np.random.randn(5),
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"C": np.arange(5, dtype="int64"),
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"D": ["a", "b", "c", "d", "e"],
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}
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)
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df.loc[2]["D"] = "foo"
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df.loc[2]["C"] = "foo"
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if not using_array_manager:
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df["C"][2] = "foo"
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else:
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# INFO(ArrayManager) for ArrayManager it doesn't matter if it's
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# changing the dtype or not
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df["C"][2] = "foo"
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assert df.loc[2, "C"] == "foo"
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def test_setting_with_copy_bug(self):
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# operating on a copy
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df = DataFrame(
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{"a": list(range(4)), "b": list("ab.."), "c": ["a", "b", np.nan, "d"]}
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)
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mask = pd.isna(df.c)
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df[["c"]][mask] = df[["b"]][mask]
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def test_setting_with_copy_bug_no_warning(self):
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# invalid warning as we are returning a new object
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# GH 8730
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df1 = DataFrame({"x": Series(["a", "b", "c"]), "y": Series(["d", "e", "f"])})
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df2 = df1[["x"]]
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# this should not raise
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df2["y"] = ["g", "h", "i"]
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def test_detect_chained_assignment_warnings_errors(self):
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df = DataFrame({"A": ["aaa", "bbb", "ccc"], "B": [1, 2, 3]})
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with option_context("chained_assignment", "warn"):
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with tm.assert_produces_warning(com.SettingWithCopyWarning):
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df.loc[0]["A"] = 111
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with option_context("chained_assignment", "raise"):
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with pytest.raises(com.SettingWithCopyError, match=msg):
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df.loc[0]["A"] = 111
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def test_detect_chained_assignment_warnings_filter_and_dupe_cols(self):
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# xref gh-13017.
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with option_context("chained_assignment", "warn"):
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df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, -9]], columns=["a", "a", "c"])
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with tm.assert_produces_warning(com.SettingWithCopyWarning):
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df.c.loc[df.c > 0] = None
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expected = DataFrame(
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[[1, 2, 3], [4, 5, 6], [7, 8, -9]], columns=["a", "a", "c"]
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)
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tm.assert_frame_equal(df, expected)
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@pytest.mark.parametrize("rhs", [3, DataFrame({0: [1, 2, 3, 4]})])
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def test_detect_chained_assignment_warning_stacklevel(self, rhs):
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# GH#42570
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df = DataFrame(np.arange(25).reshape(5, 5))
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chained = df.loc[:3]
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with option_context("chained_assignment", "warn"):
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with tm.assert_produces_warning(com.SettingWithCopyWarning) as t:
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chained[2] = rhs
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assert t[0].filename == __file__
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# TODO(ArrayManager) fast_xs with array-like scalars is not yet working
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@td.skip_array_manager_not_yet_implemented
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def test_chained_getitem_with_lists(self):
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# GH6394
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# Regression in chained getitem indexing with embedded list-like from
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# 0.12
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df = DataFrame({"A": 5 * [np.zeros(3)], "B": 5 * [np.ones(3)]})
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expected = df["A"].iloc[2]
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result = df.loc[2, "A"]
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tm.assert_numpy_array_equal(result, expected)
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result2 = df.iloc[2]["A"]
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tm.assert_numpy_array_equal(result2, expected)
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result3 = df["A"].loc[2]
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tm.assert_numpy_array_equal(result3, expected)
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result4 = df["A"].iloc[2]
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tm.assert_numpy_array_equal(result4, expected)
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def test_cache_updating(self):
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# GH 4939, make sure to update the cache on setitem
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df = tm.makeDataFrame()
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df["A"] # cache series
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df.loc["Hello Friend"] = df.iloc[0]
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assert "Hello Friend" in df["A"].index
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assert "Hello Friend" in df["B"].index
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def test_cache_updating2(self):
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# 10264
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df = DataFrame(
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np.zeros((5, 5), dtype="int64"),
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columns=["a", "b", "c", "d", "e"],
|
|
index=range(5),
|
|
)
|
|
df["f"] = 0
|
|
df.f.values[3] = 1
|
|
|
|
df.f.values[3] = 2
|
|
expected = DataFrame(
|
|
np.zeros((5, 6), dtype="int64"),
|
|
columns=["a", "b", "c", "d", "e", "f"],
|
|
index=range(5),
|
|
)
|
|
expected.at[3, "f"] = 2
|
|
tm.assert_frame_equal(df, expected)
|
|
expected = Series([0, 0, 0, 2, 0], name="f")
|
|
tm.assert_series_equal(df.f, expected)
|
|
|
|
def test_iloc_setitem_chained_assignment(self):
|
|
# GH#3970
|
|
with option_context("chained_assignment", None):
|
|
df = DataFrame({"aa": range(5), "bb": [2.2] * 5})
|
|
df["cc"] = 0.0
|
|
|
|
ck = [True] * len(df)
|
|
|
|
df["bb"].iloc[0] = 0.13
|
|
|
|
# GH#3970 this lookup used to break the chained setting to 0.15
|
|
df.iloc[ck]
|
|
|
|
df["bb"].iloc[0] = 0.15
|
|
assert df["bb"].iloc[0] == 0.15
|
|
|
|
def test_getitem_loc_assignment_slice_state(self):
|
|
# GH 13569
|
|
df = DataFrame({"a": [10, 20, 30]})
|
|
df["a"].loc[4] = 40
|
|
tm.assert_frame_equal(df, DataFrame({"a": [10, 20, 30]}))
|
|
tm.assert_series_equal(df["a"], Series([10, 20, 30], name="a"))
|