Oct 8, 2023 · Oct 15, 2023
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
        # further processed by the rest of the function
        linewidths = kwargs.pop('linewidth', None)
        edgecolors = kwargs.pop('edgecolor', None)
        # Process **kwargs to handle aliases, conflicts with explicit kwargs:
        x, y = self._process_unit_info([("x", x), ("y", y)], kwargs)
        # np.ma.ravel yields an ndarray, not a masked array,
        # unless its argument is a masked array.
        x = np.ma.ravel(x)
        y = np.ma.ravel(y)
        if x.size != y.size:
            raise ValueError("x and y must be the same size")
        # Process **kwargs to handle aliases, conflicts with explicit kwargs:
        x, y = self._process_unit_info([("x", x), ("y", y)], kwargs)

        if s is None:
            s = (20 if mpl.rcParams['_internal.classic_mode'] else
diff --git a/lib/matplotlib/tests/test_category.py b/lib/matplotlib/tests/test_category.py
    failing_test_cases = [("mixed", ['A', 3.14]),
                          ("number integer", ['1', 1]),
                          ("string integer", ['42', 42]),
                          ("nested categorical", [["a", "b"], ["c", "d"]]),
                          ("missing", ['12', np.nan])]

    fids, fvalues = zip(*failing_test_cases)

    plotters = [Axes.scatter, Axes.bar,
    plotters = [pytest.param(Axes.scatter, marks=pytest.mark.xfail),
                Axes.bar,
                pytest.param(Axes.plot, marks=pytest.mark.xfail)]

    @pytest.mark.parametrize("plotter", plotters)
    ax.plot(["a", "b", "c", "d"], [1, 2, 3, 4])
    with warnings.catch_warnings():
        ax.set_xlim("b", "c")


 categorical_examples = [("nested categorical", [["a", "b"], ["c", "d"]]),
                        ("nested with nan", [['0', np.nan], ["aa", "bb"]]),
                        ("nested mixed", [[1, 'a'], ['b', np.nan]])]
 cids, cvalues = zip(*categorical_examples)


 @pytest.mark.parametrize("xdata", cvalues, ids=cids)
 @pytest.mark.parametrize("ydata", cvalues, ids=cids)
 def test_nested_categorical(xdata, ydata):
    ax = plt.figure().subplots()
    ax.scatter(xdata, ydata)

    xtexts = [xelement._text for xelement in ax.get_xticklabels()]

    assert np.all(xtexts == np.ma.ravel(xdata))


 @pytest.mark.parametrize("xdata", cvalues, ids=cids)
 def test_nested_categorical_and_numerical(xdata):
    ydata = [[0, 1], [2, 3]]
    ax = plt.figure().subplots()
    splot = ax.scatter(xdata, ydata)

    xtexts = [xelement._text for xelement in ax.get_xticklabels()]
    y_offset_processed = list(zip(*splot.get_offsets()))[1]

    assert np.all(xtexts == np.ma.ravel(xdata))
    assert np.all(np.ma.ravel(ydata) == y_offset_processed)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -4657,14 +4657,14 @@ def scatter(self, x, y, s=None, c=None, marker=None, cmap=None, norm=None,
		# further processed by the rest of the function
		linewidths = kwargs.pop('linewidth', None)
		edgecolors = kwargs.pop('edgecolor', None)
		# Process **kwargs to handle aliases, conflicts with explicit kwargs:
		x, y = self._process_unit_info([("x", x), ("y", y)], kwargs)
		# np.ma.ravel yields an ndarray, not a masked array,
		# unless its argument is a masked array.
		x = np.ma.ravel(x)
		y = np.ma.ravel(y)
		if x.size != y.size:
		raise ValueError("x and y must be the same size")
		# Process **kwargs to handle aliases, conflicts with explicit kwargs:
		x, y = self._process_unit_info([("x", x), ("y", y)], kwargs)

		if s is None:
		s = (20 if mpl.rcParams['_internal.classic_mode'] else
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -249,11 +249,13 @@ def test_update_plot(self, plotter):
		failing_test_cases = [("mixed", ['A', 3.14]),
		("number integer", ['1', 1]),
		("string integer", ['42', 42]),
		("nested categorical", [["a", "b"], ["c", "d"]]),
		("missing", ['12', np.nan])]

		fids, fvalues = zip(*failing_test_cases)

		plotters = [Axes.scatter, Axes.bar,
		plotters = [pytest.param(Axes.scatter, marks=pytest.mark.xfail),
		Axes.bar,
		pytest.param(Axes.plot, marks=pytest.mark.xfail)]

		@pytest.mark.parametrize("plotter", plotters)
Expand DownExpand Up		@@ -321,3 +323,33 @@ def test_set_lim():
		ax.plot(["a", "b", "c", "d"], [1, 2, 3, 4])
		with warnings.catch_warnings():
		ax.set_xlim("b", "c")


		categorical_examples = [("nested categorical", [["a", "b"], ["c", "d"]]),
		("nested with nan", [['0', np.nan], ["aa", "bb"]]),
		("nested mixed", [[1, 'a'], ['b', np.nan]])]
Copy link Member story645Oct 15, 2023 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. By mixed, I meant what happens for [[1,2], ['a', 'b']] -> they all get cased to the same type b/c they get raveled into one list, so what happens then?
		cids, cvalues = zip(*categorical_examples)


		@pytest.mark.parametrize("xdata", cvalues, ids=cids)
		@pytest.mark.parametrize("ydata", cvalues, ids=cids)
		def test_nested_categorical(xdata, ydata):
		ax = plt.figure().subplots()
		ax.scatter(xdata, ydata)

		xtexts = [xelement._text for xelement in ax.get_xticklabels()]

		assert np.all(xtexts == np.ma.ravel(xdata))


		@pytest.mark.parametrize("xdata", cvalues, ids=cids)
		def test_nested_categorical_and_numerical(xdata):
		ydata = [[0, 1], [2, 3]]
		ax = plt.figure().subplots()
		splot = ax.scatter(xdata, ydata)

		xtexts = [xelement._text for xelement in ax.get_xticklabels()]
		y_offset_processed = list(zip(*splot.get_offsets()))[1]

		assert np.all(xtexts == np.ma.ravel(xdata))
		assert np.all(np.ma.ravel(ydata) == y_offset_processed)