Period Index plotting method, non standard intervals · Issue #14763 · pandas-dev/pandas (original) (raw)
Plotting a period index with 'D' or 'H' works fine, but changing the interval to 6-hr throws an error: IncompatibleFrequency: Input has different freq=6H from PeriodIndex(freq=H)
Should make a nice plot. Using the same example above with alternative frequencies of 'D' or 'H' plots as expected, but 3H, 6H, and even 24H throw an error.
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tseries\period.py in _from_arraylike(cls, data, freq, tz) 263 try: --> 264 data = com._ensure_int64(data) 265 except (TypeError, ValueError):
pandas\src\generated.pyx in pandas.algos.ensure_int64 (pandas\algos.c:64659)()
pandas\src\generated.pyx in pandas.algos.ensure_int64 (pandas\algos.c:64550)()
TypeError: int() argument must be a string, a bytes-like object or a number, not 'pandas._period.Period'
During handling of the above exception, another exception occurred:
IncompatibleFrequency Traceback (most recent call last)
in ()
2 idx = ps.period_range('2000-01-01', '2000-01-05', freq='6H')
3 s = ps.Series(np.random.randn(len(idx)), index=idx)
----> 4 s.plot()
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.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)
3564 colormap=colormap, table=table, yerr=yerr,
3565 xerr=xerr, label=label, secondary_y=secondary_y,
-> 3566 **kwds)
3567 call.doc = plot_series.doc
3568
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.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)
2643 yerr=yerr, xerr=xerr,
2644 label=label, secondary_y=secondary_y,
-> 2645 **kwds)
2646
2647
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.py in _plot(data, x, y, subplots, ax, kind, **kwds)
2439 plot_obj = klass(data, subplots=subplots, ax=ax, kind=kind, **kwds)
2440
-> 2441 plot_obj.generate()
2442 plot_obj.draw()
2443 return plot_obj.result
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.py in generate(self)
1026 self._compute_plot_data()
1027 self._setup_subplots()
-> 1028 self._make_plot()
1029 self._add_table()
1030 self._make_legend()
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.py in _make_plot(self)
1705 stacking_id=stacking_id,
1706 is_errorbar=is_errorbar,
-> 1707 **kwds)
1708 self._add_legend_handle(newlines[0], label, index=i)
1709
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.py in _ts_plot(cls, ax, x, data, style, **kwds)
1743 ax._plot_data.append((data, cls._kind, kwds))
1744
-> 1745 lines = cls._plot(ax, data.index, data.values, style=style, **kwds)
1746 # set date formatter, locators and rescale limits
1747 format_dateaxis(ax, ax.freq)
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.py in _plot(cls, ax, x, y, style, column_num, stacking_id, **kwds)
1720 cls._initialize_stacker(ax, stacking_id, len(y))
1721 y_values = cls._get_stacked_values(ax, stacking_id, y, kwds['label'])
-> 1722 lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)
1723 cls._update_stacker(ax, stacking_id, y)
1724 return lines
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tools\plotting.py in _plot(cls, ax, x, y, style, is_errorbar, **kwds)
1340 else:
1341 args = (x, y)
-> 1342 return ax.plot(*args, **kwds)
1343
1344 def _get_index_name(self):
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib_ init_.py in inner(ax, *args, **kwargs)
1816 warnings.warn(msg % (label_namer, func.name),
1817 RuntimeWarning, stacklevel=2)
-> 1818 return func(ax, *args, **kwargs)
1819 pre_doc = inner.doc
1820 if pre_doc is None:
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\axes_axes.py in plot(self, *args, **kwargs)
1381
1382 for line in self._get_lines(*args, **kwargs):
-> 1383 self.add_line(line)
1384 lines.append(line)
1385
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\axes_base.py in add_line(self, line)
1701 line.set_clip_path(self.patch)
1702
-> 1703 self._update_line_limits(line)
1704 if not line.get_label():
1705 line.set_label('_line%d' % len(self.lines))
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\axes_base.py in _update_line_limits(self, line)
1723 Figures out the data limit of the given line, updating self.dataLim.
1724 """
-> 1725 path = line.get_path()
1726 if path.vertices.size == 0:
1727 return
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\lines.py in get_path(self)
936 """
937 if self._invalidy or self._invalidx:
--> 938 self.recache()
939 return self._path
940
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\lines.py in recache(self, always)
619 def recache(self, always=False):
620 if always or self._invalidx:
--> 621 xconv = self.convert_xunits(self._xorig)
622 if ma.isMaskedArray(self.xorig):
623 x = ma.asarray(xconv, np.float).filled(np.nan)
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\artist.py in convert_xunits(self, x)
188 if ax is None or ax.xaxis is None:
189 return x
--> 190 return ax.xaxis.convert_units(x)
191
192 def convert_yunits(self, y):
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\matplotlib\axis.py in convert_units(self, x)
1442 return x
1443
-> 1444 ret = self.converter.convert(x, self.units, self)
1445 return ret
1446
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tseries\converter.py in convert(values, units, axis)
120 return values.map(lambda x: get_datevalue(x, axis.freq))
121 if com.is_period_arraylike(values):
--> 122 return PeriodIndex(values, freq=axis.freq).values
123 if isinstance(values, (list, tuple, np.ndarray, Index)):
124 return [get_datevalue(x, axis.freq) for x in values]
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tseries\period.py in new(cls, data, ordinal, freq, start, end, periods, copy, name, tz, **kwargs)
188 freq, kwargs)
189 else:
--> 190 ordinal, freq = cls._from_arraylike(data, freq, tz)
191 data = np.array(ordinal, dtype=np.int64, copy=False)
192
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tseries\period.py in _from_arraylike(cls, data, freq, tz)
265 except (TypeError, ValueError):
266 data = com._ensure_object(data)
--> 267 data = _get_ordinals(data, freq)
268
269 return data, freq
C:\Users\jaq\AppData\Local\Continuum\Anaconda\envs\py35\lib\site-packages\pandas\tseries\period.py in _get_ordinals(data, freq)
42 f = lambda x: Period(x, freq=freq).ordinal
43 if isinstance(data[0], Period):
---> 44 return period.extract_ordinals(data, freq)
45 else:
46 return lib.map_infer(data, f)
pandas\src\period.pyx in pandas._period.extract_ordinals (pandas\src\period.c:7030)()
IncompatibleFrequency: Input has different freq=6H from PeriodIndex(freq=H)