df.plot() does not work for time series after deregistering converters Prophet
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np

from pandas.plotting import deregister_matplotlib_converters

deregister_matplotlib_converters()


ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
ts.plot()
```


```pytb
~/sandbox/pandas/pandas/plotting/_core.py in __call__(self, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)
    808                            colormap=colormap, table=table, yerr=yerr,
    809                            xerr=xerr, label=label, secondary_y=secondary_y,
--> 810                            **kwds)
    811     __call__.__doc__ = plot_series.__doc__
    812

~/sandbox/pandas/pandas/plotting/_core.py in plot_series(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)
    766                  yerr=yerr, xerr=xerr,
    767                  label=label, secondary_y=secondary_y,
--> 768                  **kwds)
    769
    770

~/sandbox/pandas/pandas/plotting/_core.py in _plot(data, x, y, subplots, ax, kind, **kwds)
    714         plot_obj = klass(data, subplots=subplots, ax=ax, kind=kind, **kwds)
    715
--> 716     plot_obj.generate()
    717     plot_obj.draw()
    718     return plot_obj.result

~/sandbox/pandas/pandas/plotting/_matplotlib/core.py in generate(self)
    214         self._compute_plot_data()
    215         self._setup_subplots()
--> 216         self._make_plot()
    217         self._add_table()
    218         self._make_legend()

~/sandbox/pandas/pandas/plotting/_matplotlib/core.py in _make_plot(self)
    987                              stacking_id=stacking_id,
    988                              is_errorbar=is_errorbar,
--> 989                              **kwds)
    990             self._add_legend_handle(newlines[0], label, index=i)
    991

~/sandbox/pandas/pandas/plotting/_matplotlib/core.py in _ts_plot(cls, ax, x, data, style, **kwds)
   1025         ax._plot_data.append((data, cls._kind, kwds))
   1026
-> 1027         lines = cls._plot(ax, data.index, data.values, style=style, **kwds)
   1028         # set date formatter, locators and rescale limits
   1029         format_dateaxis(ax, ax.freq, data.index)

~/sandbox/pandas/pandas/plotting/_matplotlib/core.py in _plot(cls, ax, x, y, style, column_num, stacking_id, **kwds)
   1002             cls._initialize_stacker(ax, stacking_id, len(y))
   1003         y_values = cls._get_stacked_values(ax, stacking_id, y, kwds['label'])
-> 1004         lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)
   1005         cls._update_stacker(ax, stacking_id, y)
   1006         return lines

~/sandbox/pandas/pandas/plotting/_matplotlib/core.py in _plot(cls, ax, x, y, style, is_errorbar, **kwds)
    581             else:
    582                 args = (x, y)
--> 583             return ax.plot(*args, **kwds)
    584
    585     def _get_index_name(self):

~/Envs/pandas-dev/lib/python3.7/site-packages/matplotlib/axes/_axes.py in plot(self, scalex, scaley, data, *args, **kwargs)
   1666         lines = [*self._get_lines(*args, data=data, **kwargs)]
   1667         for line in lines:
-> 1668             self.add_line(line)
   1669         self.autoscale_view(scalex=scalex, scaley=scaley)
   1670         return lines

~/Envs/pandas-dev/lib/python3.7/site-packages/matplotlib/axes/_base.py in add_line(self, line)
   1898             line.set_clip_path(self.patch)
   1899
-> 1900         self._update_line_limits(line)
   1901         if not line.get_label():
   1902             line.set_label('_line%d' % len(self.lines))

~/Envs/pandas-dev/lib/python3.7/site-packages/matplotlib/axes/_base.py in _update_line_limits(self, line)
   1920         Figures out the data limit of the given line, updating self.dataLim.
   1921         """
-> 1922         path = line.get_path()
   1923         if path.vertices.size == 0:
   1924             return

~/Envs/pandas-dev/lib/python3.7/site-packages/matplotlib/lines.py in get_path(self)
   1025         """
   1026         if self._invalidy or self._invalidx:
-> 1027             self.recache()
   1028         return self._path
   1029

~/Envs/pandas-dev/lib/python3.7/site-packages/matplotlib/lines.py in recache(self, always)
    668         if always or self._invalidx:
    669             xconv = self.convert_xunits(self._xorig)
--> 670             x = _to_unmasked_float_array(xconv).ravel()
    671         else:
    672             x = self._x

~/Envs/pandas-dev/lib/python3.7/site-packages/matplotlib/cbook/__init__.py in _to_unmasked_float_array(x)
   1388         return np.ma.asarray(x, float).filled(np.nan)
   1389     else:
-> 1390         return np.asarray(x, float)
   1391
   1392

~/Envs/pandas-dev/lib/python3.7/site-packages/numpy/core/numeric.py in asarray(a, dtype, order)
    536
    537     """
--> 538     return array(a, dtype, copy=False, order=order)
    539
    540

TypeError: float() argument must be a string or a number, not 'Period'
```

#### Problem description

Above code is the first time series plotting example in the docs. It throws a type error as follows 

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None

pandas: 0.24.2
pytest: None
pip: 19.1.1
setuptools: 41.0.1
Cython: 0.29.10
numpy: 1.16.4
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.5.0
sphinx: None
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.1.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: 2.7.5 (dt dec pq3 ext lo64)
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
