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ValueError Traceback (most recent call last)
<ipython-input-15-afa502da7217> in <module>
1 x = np.arange(25, 250, 25)
----> 2 plt.plot(x, spcat1, x, spcat1a, x, spcat1b, x, spcat2)
3 plt.legend(('spcat1', 'spcat1a', 'spcat1b', 'spcat2'))
4 plt.title('Speed of Sparse Dummy Functions')
5 plt.xlabel('Sample Size')
/srv/conda/lib/python3.7/site-packages/matplotlib/pyplot.py in plot(scalex, scaley, data, *args, **kwargs)
2809 return gca().plot(
2810 *args, scalex=scalex, scaley=scaley, **({"data": data} if data
-> 2811 is not None else {}), **kwargs)
2812
2813
/srv/conda/lib/python3.7/site-packages/matplotlib/__init__.py in inner(ax, data, *args, **kwargs)
1808 "the Matplotlib list!)" % (label_namer, func.__name__),
1809 RuntimeWarning, stacklevel=2)
-> 1810 return func(ax, *args, **kwargs)
1811
1812 inner.__doc__ = _add_data_doc(inner.__doc__,
/srv/conda/lib/python3.7/site-packages/matplotlib/axes/_axes.py in plot(self, scalex, scaley, *args, **kwargs)
1609 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D._alias_map)
1610
-> 1611 for line in self._get_lines(*args, **kwargs):
1612 self.add_line(line)
1613 lines.append(line)
/srv/conda/lib/python3.7/site-packages/matplotlib/axes/_base.py in _grab_next_args(self, *args, **kwargs)
391 this += args[0],
392 args = args[1:]
--> 393 yield from self._plot_args(this, kwargs)
394
395
/srv/conda/lib/python3.7/site-packages/matplotlib/axes/_base.py in _plot_args(self, tup, kwargs)
368 x, y = index_of(tup[-1])
369
--> 370 x, y = self._xy_from_xy(x, y)
371
372 if self.command == 'plot':
/srv/conda/lib/python3.7/site-packages/matplotlib/axes/_base.py in _xy_from_xy(self, x, y)
229 if x.shape[0] != y.shape[0]:
230 raise ValueError("x and y must have same first dimension, but "
--> 231 "have shapes {} and {}".format(x.shape, y.shape))
232 if x.ndim > 2 or y.ndim > 2:
233 raise ValueError("x and y can be no greater than 2-D, but have "
ValueError: x and y must have same first dimension, but have shapes (9,) and (0,)
The text was updated successfully, but these errors were encountered:
Sparse Categorical Speed
The text was updated successfully, but these errors were encountered: