"""
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Tests for DataFrame.mask; tests DataFrame.where as a side-effect.
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"""
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import numpy as np
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from pandas import (
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NA,
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DataFrame,
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Float64Dtype,
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Series,
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StringDtype,
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Timedelta,
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isna,
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)
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import pandas._testing as tm
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class TestDataFrameMask:
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def test_mask(self):
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df = DataFrame(np.random.randn(5, 3))
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cond = df > 0
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rs = df.where(cond, np.nan)
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tm.assert_frame_equal(rs, df.mask(df <= 0))
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tm.assert_frame_equal(rs, df.mask(~cond))
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other = DataFrame(np.random.randn(5, 3))
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rs = df.where(cond, other)
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tm.assert_frame_equal(rs, df.mask(df <= 0, other))
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tm.assert_frame_equal(rs, df.mask(~cond, other))
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def test_mask2(self):
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# see GH#21891
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df = DataFrame([1, 2])
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res = df.mask([[True], [False]])
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exp = DataFrame([np.nan, 2])
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tm.assert_frame_equal(res, exp)
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def test_mask_inplace(self):
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# GH#8801
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df = DataFrame(np.random.randn(5, 3))
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cond = df > 0
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rdf = df.copy()
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return_value = rdf.where(cond, inplace=True)
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assert return_value is None
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tm.assert_frame_equal(rdf, df.where(cond))
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tm.assert_frame_equal(rdf, df.mask(~cond))
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rdf = df.copy()
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return_value = rdf.where(cond, -df, inplace=True)
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assert return_value is None
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tm.assert_frame_equal(rdf, df.where(cond, -df))
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tm.assert_frame_equal(rdf, df.mask(~cond, -df))
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def test_mask_edge_case_1xN_frame(self):
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# GH#4071
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df = DataFrame([[1, 2]])
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res = df.mask(DataFrame([[True, False]]))
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expec = DataFrame([[np.nan, 2]])
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tm.assert_frame_equal(res, expec)
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def test_mask_callable(self):
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# GH#12533
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df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
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result = df.mask(lambda x: x > 4, lambda x: x + 1)
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exp = DataFrame([[1, 2, 3], [4, 6, 7], [8, 9, 10]])
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tm.assert_frame_equal(result, exp)
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tm.assert_frame_equal(result, df.mask(df > 4, df + 1))
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# return ndarray and scalar
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result = df.mask(lambda x: (x % 2 == 0).values, lambda x: 99)
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exp = DataFrame([[1, 99, 3], [99, 5, 99], [7, 99, 9]])
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tm.assert_frame_equal(result, exp)
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tm.assert_frame_equal(result, df.mask(df % 2 == 0, 99))
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# chain
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result = (df + 2).mask(lambda x: x > 8, lambda x: x + 10)
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exp = DataFrame([[3, 4, 5], [6, 7, 8], [19, 20, 21]])
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tm.assert_frame_equal(result, exp)
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tm.assert_frame_equal(result, (df + 2).mask((df + 2) > 8, (df + 2) + 10))
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def test_mask_dtype_bool_conversion(self):
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# GH#3733
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df = DataFrame(data=np.random.randn(100, 50))
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df = df.where(df > 0) # create nans
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bools = df > 0
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mask = isna(df)
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expected = bools.astype(object).mask(mask)
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result = bools.mask(mask)
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tm.assert_frame_equal(result, expected)
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def test_mask_stringdtype(frame_or_series):
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# GH 40824
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obj = DataFrame(
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{"A": ["foo", "bar", "baz", NA]},
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index=["id1", "id2", "id3", "id4"],
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dtype=StringDtype(),
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)
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filtered_obj = DataFrame(
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{"A": ["this", "that"]}, index=["id2", "id3"], dtype=StringDtype()
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)
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expected = DataFrame(
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{"A": [NA, "this", "that", NA]},
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index=["id1", "id2", "id3", "id4"],
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dtype=StringDtype(),
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)
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if frame_or_series is Series:
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obj = obj["A"]
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filtered_obj = filtered_obj["A"]
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expected = expected["A"]
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filter_ser = Series([False, True, True, False])
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result = obj.mask(filter_ser, filtered_obj)
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tm.assert_equal(result, expected)
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def test_mask_where_dtype_timedelta():
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# https://github.com/pandas-dev/pandas/issues/39548
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df = DataFrame([Timedelta(i, unit="d") for i in range(5)])
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expected = DataFrame(np.full(5, np.nan, dtype="timedelta64[ns]"))
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tm.assert_frame_equal(df.mask(df.notna()), expected)
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expected = DataFrame(
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[np.nan, np.nan, np.nan, Timedelta("3 day"), Timedelta("4 day")]
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)
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tm.assert_frame_equal(df.where(df > Timedelta(2, unit="d")), expected)
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def test_mask_return_dtype():
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# GH#50488
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ser = Series([0.0, 1.0, 2.0, 3.0], dtype=Float64Dtype())
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cond = ~ser.isna()
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other = Series([True, False, True, False])
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excepted = Series([1.0, 0.0, 1.0, 0.0], dtype=ser.dtype)
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result = ser.mask(cond, other)
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tm.assert_series_equal(result, excepted)
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def test_mask_inplace_no_other():
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# GH#51685
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df = DataFrame({"a": [1, 2], "b": ["x", "y"]})
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cond = DataFrame({"a": [True, False], "b": [False, True]})
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df.mask(cond, inplace=True)
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expected = DataFrame({"a": [np.nan, 2], "b": ["x", np.nan]})
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tm.assert_frame_equal(df, expected)
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