pandas 0.24.1 testsuite failure with new numpy (
```
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_daily FAILED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_quarterly FAILED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_monthly FAILED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_monthly_long PASSED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_annual FAILED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_minutely PASSED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_finder_hourly PASSED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_gaps FAILED
../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py::TestTSPlot::test_gap_upsample FAILED
[...]

=================================== FAILURES ===================================
_________________________ TestTSPlot.test_finder_daily _________________________

self = <pandas.tests.plotting.test_datetimelike.TestTSPlot object at 0xc9b0e30c>

    @pytest.mark.slow
    def test_finder_daily(self):
        day_lst = [10, 40, 252, 400, 950, 2750, 10000]
    
        if (self.mpl_ge_3_0_0 or not self.mpl_ge_2_0_1
                or (self.mpl_ge_2_1_0 and not self.mpl_ge_2_2_2)):
            # 2.0.0, 2.2.0 (exactly) or >= 3.0.0
            xpl1 = xpl2 = [Period('1999-1-1', freq='B').ordinal] * len(day_lst)
        else:  # 2.0.1, 2.1.0, 2.2.2, 2.2.3
            xpl1 = [7565, 7564, 7553, 7546, 7518, 7428, 7066]
            xpl2 = [7566, 7564, 7554, 7546, 7519, 7429, 7066]
    
        rs1 = []
        rs2 = []
        for i, n in enumerate(day_lst):
            rng = bdate_range('1999-1-1', periods=n)
            ser = Series(np.random.randn(len(rng)), rng)
            _, ax = self.plt.subplots()
            ser.plot(ax=ax)
            xaxis = ax.get_xaxis()
            rs1.append(xaxis.get_majorticklocs()[0])
    
            vmin, vmax = ax.get_xlim()
            ax.set_xlim(vmin + 0.9, vmax)
            rs2.append(xaxis.get_majorticklocs()[0])
            self.plt.close(ax.get_figure())
    
>       assert rs1 == xpl1
E       assert [7566, 7566, ...66, 7566, ...] == [7565, 7564, 7...18, 7428, ...]
E         At index 0 diff: 7566 != 7565
E         Full diff:
E         - [7566, 7566, 7566, 7566, 7566, 7566, 7566]
E         + [7565, 7564, 7553, 7546, 7518, 7428, 7066]

../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py:425: AssertionError
_______________________ TestTSPlot.test_finder_quarterly _______________________

self = <pandas.tests.plotting.test_datetimelike.TestTSPlot object at 0xa48b6fcc>

    @pytest.mark.slow
    def test_finder_quarterly(self):
        yrs = [3.5, 11]
    
        if (self.mpl_ge_3_0_0 or not self.mpl_ge_2_0_1
                or (self.mpl_ge_2_1_0 and not self.mpl_ge_2_2_2)):
            # 2.0.0, 2.2.0 (exactly) or >= 3.0.0
            xpl1 = xpl2 = [Period('1988Q1').ordinal] * len(yrs)
        else:  # 2.0.1, 2.1.0, 2.2.2, 2.2.3
            xpl1 = [68, 68]
            xpl2 = [72, 68]
    
        rs1 = []
        rs2 = []
        for i, n in enumerate(yrs):
            rng = period_range('1987Q2', periods=int(n * 4), freq='Q')
            ser = Series(np.random.randn(len(rng)), rng)
            _, ax = self.plt.subplots()
            ser.plot(ax=ax)
            xaxis = ax.get_xaxis()
            rs1.append(xaxis.get_majorticklocs()[0])
    
            (vmin, vmax) = ax.get_xlim()
            ax.set_xlim(vmin + 0.9, vmax)
            rs2.append(xaxis.get_majorticklocs()[0])
            self.plt.close(ax.get_figure())
    
>       assert rs1 == xpl1
E       assert [72, 72] == [68, 68]
E         At index 0 diff: 72 != 68
E         Full diff:
E         - [72, 72]
E         + [68, 68]

../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py:455: AssertionError
________________________ TestTSPlot.test_finder_monthly ________________________

self = <pandas.tests.plotting.test_datetimelike.TestTSPlot object at 0xc45a44cc>

    @pytest.mark.slow
    def test_finder_monthly(self):
        yrs = [1.15, 2.5, 4, 11]
    
        if (self.mpl_ge_3_0_0 or not self.mpl_ge_2_0_1
                or (self.mpl_ge_2_1_0 and not self.mpl_ge_2_2_2)):
            # 2.0.0, 2.2.0 (exactly) or >= 3.0.0
            xpl1 = xpl2 = [Period('Jan 1988').ordinal] * len(yrs)
        else:  # 2.0.1, 2.1.0, 2.2.2, 2.2.3
            xpl1 = [216, 216, 204, 204]
            xpl2 = [216, 216, 216, 204]
    
        rs1 = []
        rs2 = []
        for i, n in enumerate(yrs):
            rng = period_range('1987Q2', periods=int(n * 12), freq='M')
            ser = Series(np.random.randn(len(rng)), rng)
            _, ax = self.plt.subplots()
            ser.plot(ax=ax)
            xaxis = ax.get_xaxis()
            rs1.append(xaxis.get_majorticklocs()[0])
    
            vmin, vmax = ax.get_xlim()
            ax.set_xlim(vmin + 0.9, vmax)
            rs2.append(xaxis.get_majorticklocs()[0])
            self.plt.close(ax.get_figure())
    
>       assert rs1 == xpl1
E       assert [216, 216, 216, 216] == [216, 216, 204, 204]
E         At index 2 diff: 216 != 204
E         Full diff:
E         - [216, 216, 216, 216]
E         ?             ^^   ^^
E         + [216, 216, 204, 204]
E         ?             ^^   ^^

../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py:485: AssertionError
________________________ TestTSPlot.test_finder_annual _________________________

self = <pandas.tests.plotting.test_datetimelike.TestTSPlot object at 0xc7d841cc>

    @pytest.mark.slow
    def test_finder_annual(self):
        if (self.mpl_ge_3_0_0 or not self.mpl_ge_2_0_1
                or (self.mpl_ge_2_1_0 and not self.mpl_ge_2_2_2)):
            # 2.0.0, 2.2.0 (exactly) or >= 3.0.0
            xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]
        else:  # 2.0.1, 2.1.0, 2.2.2, 2.2.3
            xp = [1986, 1986, 1990, 1990, 1995, 2020, 1970, 1970]
    
        xp = [Period(x, freq='A').ordinal for x in xp]
        rs = []
        for i, nyears in enumerate([5, 10, 19, 49, 99, 199, 599, 1001]):
            rng = period_range('1987', periods=nyears, freq='A')
            ser = Series(np.random.randn(len(rng)), rng)
            _, ax = self.plt.subplots()
            ser.plot(ax=ax)
            xaxis = ax.get_xaxis()
            rs.append(xaxis.get_majorticklocs()[0])
            self.plt.close(ax.get_figure())
    
>       assert rs == xp
E       assert [17, 18, 20, 20, 25, 50, ...] == [16L, 16L, 20L... 25L, 50L, ...]
E         At index 0 diff: 17 != 16L
E         Full diff:
E         - [17, 18, 20, 20, 25, 50, 100, 200]
E         + [16L, 16L, 20L, 20L, 25L, 50L, 0L, 0L]

../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py:518: AssertionError
_____________________________ TestTSPlot.test_gaps _____________________________

self = <pandas.tests.plotting.test_datetimelike.TestTSPlot object at 0xbf3dfb8c>

    @pytest.mark.slow
    def test_gaps(self):
        ts = tm.makeTimeSeries()
        ts[5:25] = np.nan
        _, ax = self.plt.subplots()
        ts.plot(ax=ax)
        lines = ax.get_lines()
        assert len(lines) == 1
        line = lines[0]
        data = line.get_xydata()
    
        if (self.mpl_ge_3_0_0 or not self.mpl_ge_2_0_1
                or (self.mpl_ge_2_1_0 and not self.mpl_ge_2_2_2)):
            # 2.0.0, 2.2.0 (exactly) or >= 3.0.0
            data = np.ma.MaskedArray(data, mask=isna(data), fill_value=np.nan)
    
>       assert isinstance(data, np.ma.core.MaskedArray)
E       AssertionError: assert False
E        +  where False = isinstance(array([[ 7.82700000e+03, -1.02081446e+00],\n       [ 7.82800000e+03,  8.0754728...[ 7.85500000e+03,  3.90151635e-01],\n       [ 7.85600000e+03, -8.36108671e-01]]), <class 'numpy.ma.core.MaskedArray'>)
E        +    where <class 'numpy.ma.core.MaskedArray'> = <module 'numpy.ma.core' from '/usr/lib/python2.7/dist-packages/numpy/ma/core.pyc'>.MaskedArray
E        +      where <module 'numpy.ma.core' from '/usr/lib/python2.7/dist-packages/numpy/ma/core.pyc'> = <module 'numpy.ma' from '/usr/lib/python2.7/dist-packages/numpy/ma/__init__.pyc'>.core
E        +        where <module 'numpy.ma' from '/usr/lib/python2.7/dist-packages/numpy/ma/__init__.pyc'> = np.ma

../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py:564: AssertionError
_________________________ TestTSPlot.test_gap_upsample _________________________

self = <pandas.tests.plotting.test_datetimelike.TestTSPlot object at 0xc9f115ac>

    @pytest.mark.slow
    def test_gap_upsample(self):
        low = tm.makeTimeSeries()
        low[5:25] = np.nan
        _, ax = self.plt.subplots()
        low.plot(ax=ax)
    
        idxh = date_range(low.index[0], low.index[-1], freq='12h')
        s = Series(np.random.randn(len(idxh)), idxh)
        s.plot(secondary_y=True)
        lines = ax.get_lines()
        assert len(lines) == 1
        assert len(ax.right_ax.get_lines()) == 1
    
        line = lines[0]
        data = line.get_xydata()
        if (self.mpl_ge_3_0_0 or not self.mpl_ge_2_0_1
                or (self.mpl_ge_2_1_0 and not self.mpl_ge_2_2_2)):
            # 2.0.0, 2.2.0 (exactly) or >= 3.0.0
            data = np.ma.MaskedArray(data, mask=isna(data), fill_value=np.nan)
    
>       assert isinstance(data, np.ma.core.MaskedArray)
E       AssertionError: assert False
E        +  where False = isinstance(array([[ 2.63016000e+05, -8.71992271e-01],\n       [ 2.63040000e+05,  2.4476855...[ 2.63928000e+05, -1.46319072e-01],\n       [ 2.63952000e+05,  1.57315404e+00]]), <class 'numpy.ma.core.MaskedArray'>)
E        +    where <class 'numpy.ma.core.MaskedArray'> = <module 'numpy.ma.core' from '/usr/lib/python2.7/dist-packages/numpy/ma/core.pyc'>.MaskedArray
E        +      where <module 'numpy.ma.core' from '/usr/lib/python2.7/dist-packages/numpy/ma/core.pyc'> = <module 'numpy.ma' from '/usr/lib/python2.7/dist-packages/numpy/ma/__init__.pyc'>.core
E        +        where <module 'numpy.ma' from '/usr/lib/python2.7/dist-packages/numpy/ma/__init__.pyc'> = np.ma

../debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_datetimelike.py:630: AssertionError
=============================== warnings summary ===============================
debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/extension/test_integer.py::TestMethods::()::test_combine_le[Int8Dtype]
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/extension/base/methods.py:153: RuntimeWarning: invalid value encountered in greater_equal
    expected = pd.Series([a <= val for a in list(orig_data1)])

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/frame/test_constructors.py::TestDataFrameConstructors::()::test_constructor_dict_nan_tuple_key[nan0]
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/core/common.py:207: RuntimeWarning: invalid value encountered in less
    return sorted(listed)

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/groupby/test_filters.py::test_filter_and_transform_with_non_unique_float_index
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/core/indexes/base.py:2656: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
    return self._engine.get_loc(key)

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_frame.py::TestDataFramePlots::()::test_logscales
  /usr/lib/python2.7/dist-packages/matplotlib/axes/_base.py:3157: UserWarning: Attempted to set non-positive xlimits for log-scale axis; invalid limits will be ignored.
    'Attempted to set non-positive xlimits for log-scale axis; '

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_frame.py::TestDataFramePlots::()::test_errorbar_plot
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/plotting/_core.py:1798: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    plot_obj.generate()
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/plotting/_core.py:1798: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    plot_obj.generate()
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/plotting/_core.py:1798: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    plot_obj.generate()

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_frame.py::TestDataFramePlots::()::test_errorbar_timeseries
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/plotting/_core.py:1798: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    plot_obj.generate()
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/plotting/_core.py:1798: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    plot_obj.generate()
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/plotting/_core.py:1798: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    plot_obj.generate()

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_hist_method.py::TestSeriesPlots::()::test_hist_legacy
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_hist_method.py::TestDataFramePlots::()::test_tight_layout
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_hist_method.py:253: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared
    _check_plot_works(df.hist)

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_misc.py::TestSeriesPlots::()::test_autocorrelation_plot
  /usr/lib/python2.7/dist-packages/matplotlib/pyplot.py:969: UserWarning: Requested projection is different from current axis projection, creating new axis with requested projection.
    return gcf().gca(**kwargs)
  /usr/lib/python2.7/dist-packages/matplotlib/pyplot.py:969: UserWarning: Requested projection is different from current axis projection, creating new axis with requested projection.
    return gcf().gca(**kwargs)

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/plotting/test_series.py::TestSeriesPlots::()::test_hist_legacy
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)
  /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
    warnings.warn(message, mplDeprecation, stacklevel=1)

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/scalar/timedelta/test_arithmetic.py::TestTimedeltaMultiplicationDivision::()::test_td_div_nan[nan1]
  /<<PKGBUILDDIR>>/debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/scalar/timedelta/test_arithmetic.py:334: RuntimeWarning: invalid value encountered in double_scalars
    result = td // nan

debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/tseries/offsets/test_offsets_properties.py::test_apply_index_implementations
  /usr/lib/python2.7/dist-packages/dateutil/zoneinfo/__init__.py:26: UserWarning: I/O error(2): No such file or directory
    warnings.warn("I/O error({0}): {1}".format(e.errno, e.strerror))

-- Docs: https://docs.pytest.org/en/latest/warnings.html
 6 failed, 43011 passed, 3393 skipped, 777 deselected, 767 xfailed, 21 xpassed, 27 warnings in 5632.65 seconds 
```
Do you have any clue for the errors above?
this is the full log
https://launchpadlibrarian.net/411242961/buildlog_ubuntu-disco-i386.pandas_0.24.1-0ubuntu1_BUILDING.txt.gz