reverting · Daquisu/pandas@2cb449b (original) (raw)

`@@ -169,8 +169,18 @@ def test_transform_axis_1(request, transformation_func):

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`msg = "DataFrame.groupby with axis=1 is deprecated"

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`with tm.assert_produces_warning(FutureWarning, match=msg):

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`gb = df.groupby([0, 0, 1], axis=1)

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result = gb.transform(transformation_func, *args)

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expected = df.T.groupby([0, 0, 1]).transform(transformation_func, *args).T

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+

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pct_change_msg = (

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"The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"

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)

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if transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=pct_change_msg):

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result = gb.transform("pct_change", *args)

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with tm.assert_produces_warning(FutureWarning, match=pct_change_msg):

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expected = df.T.groupby([0, 0, 1]).transform("pct_change", *args).T

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else:

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result = gb.transform(transformation_func, *args)

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expected = df.T.groupby([0, 0, 1]).transform(transformation_func, *args).T

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`if transformation_func in ["diff", "shift"]:

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`# Result contains nans, so transpose coerces to float

`@@ -404,11 +414,25 @@ def mock_op(x):

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`test_op = lambda x: x.transform(transformation_func)

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`mock_op = lambda x: getattr(x, transformation_func)()

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result = test_op(df.groupby("A"))

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msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"

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groupby_msg = (

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"The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"

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)

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+

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if transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=groupby_msg):

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result = test_op(df.groupby("A"))

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else:

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result = test_op(df.groupby("A"))

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+

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`` # pass the group in same order as iterating for ... in df.groupby(...)

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`# but reorder to match df's index since this is a transform

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`groups = [df[["B"]].iloc[4:6], df[["B"]].iloc[6:], df[["B"]].iloc[:4]]

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expected = concat([mock_op(g) for g in groups]).sort_index()

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if transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=msg):

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expected = concat([mock_op(g) for g in groups]).sort_index()

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else:

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expected = concat([mock_op(g) for g in groups]).sort_index()

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`# sort_index does not preserve the freq

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`expected = expected.set_axis(df.index)

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`@@ -969,14 +993,9 @@ def test_pct_change(frame_or_series, freq, periods, fill_method, limit):

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`else:

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`expected = expected.to_frame("vals")

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msg = (

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"The 'fill_method' and 'limit' keywords in "

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f"{type(gb).name}.pct_change are deprecated"

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result = gb.pct_change(

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periods=periods, fill_method=fill_method, limit=limit, freq=freq

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` )

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with tm.assert_produces_warning(FutureWarning, match=msg):

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result = gb.pct_change(

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periods=periods, fill_method=fill_method, limit=limit, freq=freq

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)

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`tm.assert_equal(result, expected)

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`@@ -1394,13 +1413,21 @@ def test_null_group_str_transformer(request, dropna, transformation_func):

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`args = get_groupby_method_args(transformation_func, df)

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`gb = df.groupby("A", dropna=dropna)

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msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"

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groupby_msg = (

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"The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"

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)

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+

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`buffer = []

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`for k, (idx, group) in enumerate(gb):

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`if transformation_func == "cumcount":

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`# DataFrame has no cumcount method

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`res = DataFrame({"B": range(len(group))}, index=group.index)

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`elif transformation_func == "ngroup":

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`res = DataFrame(len(group) * [k], index=group.index, columns=["B"])

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elif transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=msg):

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res = getattr(group[["B"]], "pct_change")(*args)

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`else:

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`res = getattr(group[["B"]], transformation_func)(*args)

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`buffer.append(res)

`@@ -1413,7 +1440,11 @@ def test_null_group_str_transformer(request, dropna, transformation_func):

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`# ngroup/cumcount always returns a Series as it counts the groups, not values

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`expected = expected["B"].rename(None)

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result = gb.transform(transformation_func, *args)

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if transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=groupby_msg):

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result = gb.transform("pct_change", *args)

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else:

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result = gb.transform(transformation_func, *args)

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`tm.assert_equal(result, expected)

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`@@ -1465,13 +1496,21 @@ def test_null_group_str_transformer_series(dropna, transformation_func):

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`args = get_groupby_method_args(transformation_func, ser)

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`gb = ser.groupby([1, 1, np.nan], dropna=dropna)

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msg = "The default fill_method='pad' in Series.pct_change is deprecated"

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groupby_msg = (

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"The default fill_method='ffill' in SeriesGroupBy.pct_change is deprecated"

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)

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+

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`buffer = []

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`for k, (idx, group) in enumerate(gb):

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`if transformation_func == "cumcount":

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`# Series has no cumcount method

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`res = Series(range(len(group)), index=group.index)

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`elif transformation_func == "ngroup":

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`res = Series(k, index=group.index)

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elif transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=msg):

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res = getattr(group, "pct_change")(*args)

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`else:

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`res = getattr(group, transformation_func)(*args)

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`buffer.append(res)

`@@ -1480,7 +1519,10 @@ def test_null_group_str_transformer_series(dropna, transformation_func):

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`buffer.append(Series([np.nan], index=[3], dtype=dtype))

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`expected = concat(buffer)

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with tm.assert_produces_warning(None):

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if transformation_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=groupby_msg):

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result = gb.transform("pct_change", *args)

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else:

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`result = gb.transform(transformation_func, *args)

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`tm.assert_equal(result, expected)

`@@ -1523,6 +1565,14 @@ def test_as_index_no_change(keys, df, groupby_func):

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`args = get_groupby_method_args(groupby_func, df)

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`gb_as_index_true = df.groupby(keys, as_index=True)

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`gb_as_index_false = df.groupby(keys, as_index=False)

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result = gb_as_index_true.transform(groupby_func, *args)

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expected = gb_as_index_false.transform(groupby_func, *args)

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+

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msg = "The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"

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if groupby_func == "pct_change":

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with tm.assert_produces_warning(FutureWarning, match=msg):

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result = gb_as_index_true.transform("pct_change", *args)

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with tm.assert_produces_warning(FutureWarning, match=msg):

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expected = gb_as_index_false.transform("pct_change", *args)

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else:

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result = gb_as_index_true.transform(groupby_func, *args)

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expected = gb_as_index_false.transform(groupby_func, *args)

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`tm.assert_equal(result, expected)