Prophet: df.plot() does not work for time series after importing Prophet

[sudhNau]

Code Sample, a copy-pastable example if possible
from fbprophet import Prophet
import pandas as pd
import numpy as np

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

Problem description

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

TypeError                                 Traceback (most recent call last)
<ipython-input-14-7ea99c00ceb5> in <module>
      1 ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
      2 ts = ts.cumsum()
----> 3 ts.plot()

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/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)
   2740                            colormap=colormap, table=table, yerr=yerr,
   2741                            xerr=xerr, label=label, secondary_y=secondary_y,
-> 2742                            **kwds)
   2743     __call__.__doc__ = plot_series.__doc__
   2744 

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/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)
   1996                  yerr=yerr, xerr=xerr,
   1997                  label=label, secondary_y=secondary_y,
-> 1998                  **kwds)
   1999 
   2000 

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/pandas/plotting/_core.py in _plot(data, x, y, subplots, ax, kind, **kwds)
   1799         plot_obj = klass(data, subplots=subplots, ax=ax, kind=kind, **kwds)
   1800 
-> 1801     plot_obj.generate()
   1802     plot_obj.draw()
   1803     return plot_obj.result

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/pandas/plotting/_core.py in generate(self)
    249         self._compute_plot_data()
    250         self._setup_subplots()
--> 251         self._make_plot()
    252         self._add_table()
    253         self._make_legend()

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/pandas/plotting/_core.py in _make_plot(self)
    994                              stacking_id=stacking_id,
    995                              is_errorbar=is_errorbar,
--> 996                              **kwds)
    997             self._add_legend_handle(newlines[0], label, index=i)
    998 

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/pandas/plotting/_core.py in _ts_plot(cls, ax, x, data, style, **kwds)
   1032         ax._plot_data.append((data, cls._kind, kwds))
   1033 
-> 1034         lines = cls._plot(ax, data.index, data.values, style=style, **kwds)
   1035         # set date formatter, locators and rescale limits
   1036         format_dateaxis(ax, ax.freq, data.index)

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/pandas/plotting/_core.py in _plot(cls, ax, x, y, style, column_num, stacking_id, **kwds)
   1009             cls._initialize_stacker(ax, stacking_id, len(y))
   1010         y_values = cls._get_stacked_values(ax, stacking_id, y, kwds['label'])
-> 1011         lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)
   1012         cls._update_stacker(ax, stacking_id, y)
   1013         return lines

/usr/local/anaconda3/envs/order_forecast/lib/python3.7/site-packages/pandas/plotting/_core.py in _plot(cls, ax, x, y, style, is_errorbar, **kwds)
    599             else:
    600                 args = (x, y)
--> 601             return ax.plot(*args, **kwds)
    602 
    603     def _get_index_name(self):

/usr/local/anaconda3/envs/order_forecast/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

/usr/local/anaconda3/envs/order_forecast/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))

/usr/local/anaconda3/envs/order_forecast/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

/usr/local/anaconda3/envs/order_forecast/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 

/usr/local/anaconda3/envs/order_forecast/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

/usr/local/anaconda3/envs/order_forecast/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 

/usr/local/anaconda3/envs/order_forecast/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'

[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

[alexgawrilow]

I have the same issue since upgrading to the newest version of fbprophet (0.5). The older version (0.4.post2) works fine.

[daikonradish]

Try this

# Assuming you have imported Pandas appropriately
pd.plotting.register_matplotlib_converters()
ts.plot()

See #999.