我最近使用 Python 3.6.4 将 pandas 升级到 1.1.5，但我无法再绘制任何带有日期时间索引列的图表。
请参阅以下示例，其中我从 csv 文件导入时间序列。我也试过注册 matplotlib 转换器，以防这是问题所在。我收到如下所示的错误消息。顺便说一句，seaborn 也不再有效，但不确定这是否相关。
谢谢
import matplotlib.pyplot as plt
import pandas as pd
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
df = pd.read_csv('example.csv', parse_dates=True, index_col=0, dayfirst=True)
df.head()
Click here to see output for df.head()
df.plot()
如果我尝试绘制，我会收到以下错误
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-37-848b80e64df8> in <module>()
----> 1 df.plot()
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_core.py in __call__(self, *args, **kwargs)
947 data.columns = label_name
948
--> 949 return plot_backend.plot(data, kind=kind, **kwargs)
950
951 __call__.__doc__ = __doc__
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\__init__.py in plot(data, kind, **kwargs)
59 kwargs["ax"] = getattr(ax, "left_ax", ax)
60 plot_obj = PLOT_CLASSES[kind](data, **kwargs)
---> 61 plot_obj.generate()
62 plot_obj.draw()
63 return plot_obj.result
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\core.py in generate(self)
269 self._compute_plot_data()
270 self._setup_subplots()
--> 271 self._make_plot()
272 self._add_table()
273 self._make_legend()
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\core.py in _make_plot(self)
1124 stacking_id=stacking_id,
1125 is_errorbar=is_errorbar,
-> 1126 **kwds,
1127 )
1128 self._add_legend_handle(newlines[0], label, index=i)
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\core.py in _plot(cls, ax, x, y, style, column_num, stacking_id, **kwds)
1143 cls._initialize_stacker(ax, stacking_id, len(y))
1144 y_values = cls._get_stacked_values(ax, stacking_id, y, kwds["label"])
-> 1145 lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)
1146 cls._update_stacker(ax, stacking_id, y)
1147 return lines
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\converter.py in wrapper(*args, **kwargs)
63 def wrapper(*args, **kwargs):
64 with pandas_converters():
---> 65 return func(*args, **kwargs)
66
67 return wrapper
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\core.py in _plot(cls, ax, x, y, style, is_errorbar, **kwds)
666 else:
667 args = (x, y)
--> 668 return ax.plot(*args, **kwds)
669
670 def _get_index_name(self):
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\__init__.py in inner(ax, *args, **kwargs)
1715 warnings.warn(msg % (label_namer, func.__name__),
1716 RuntimeWarning, stacklevel=2)
-> 1717 return func(ax, *args, **kwargs)
1718 pre_doc = inner.__doc__
1719 if pre_doc is None:
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in plot(self, *args, **kwargs)
1371
1372 for line in self._get_lines(*args, **kwargs):
-> 1373 self.add_line(line)
1374 lines.append(line)
1375
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in add_line(self, line)
1777 line.set_clip_path(self.patch)
1778
-> 1779 self._update_line_limits(line)
1780 if not line.get_label():
1781 line.set_label('_line%d' % len(self.lines))
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in _update_line_limits(self, line)
1799 Figures out the data limit of the given line, updating self.dataLim.
1800 """
-> 1801 path = line.get_path()
1802 if path.vertices.size == 0:
1803 return
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\lines.py in get_path(self)
955 """
956 if self._invalidy or self._invalidx:
--> 957 self.recache()
958 return self._path
959
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\lines.py in recache(self, always)
655 def recache(self, always=False):
656 if always or self._invalidx:
--> 657 xconv = self.convert_xunits(self._xorig)
658 x = _to_unmasked_float_array(xconv).ravel()
659 else:
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\artist.py in convert_xunits(self, x)
189 if ax is None or ax.xaxis is None:
190 return x
--> 191 return ax.xaxis.convert_units(x)
192
193 def convert_yunits(self, y):
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\axis.py in convert_units(self, x)
1489 return x
1490
-> 1491 ret = self.converter.convert(x, self.units, self)
1492 return ret
1493
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\converter.py in convert(values, unit, axis)
254 values = [DatetimeConverter._convert_1d(v, unit, axis) for v in values]
255 else:
--> 256 values = DatetimeConverter._convert_1d(values, unit, axis)
257 return values
258
C:\Program Files\Anaconda3\lib\site-packages\pandas\plotting\_matplotlib\converter.py in _convert_1d(values, unit, axis)
289 pass
290
--> 291 values = dates.date2num(values)
292
293 return values
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\dates.py in date2num(d)
394 if not d.size:
395 return d
--> 396 return _to_ordinalf_np_vectorized(d)
397
398
C:\Program Files\Anaconda3\lib\site-packages\numpy\lib\function_base.py in __call__(self, *args, **kwargs)
2106 vargs.extend([kwargs[_n] for _n in names])
2107
-> 2108 return self._vectorize_call(func=func, args=vargs)
2109
2110 def _get_ufunc_and_otypes(self, func, args):
C:\Program Files\Anaconda3\lib\site-packages\numpy\lib\function_base.py in _vectorize_call(self, func, args)
2184 res = func()
2185 else:
-> 2186 ufunc, otypes = self._get_ufunc_and_otypes(func=func, args=args)
2187
2188 # Convert args to object arrays first
C:\Program Files\Anaconda3\lib\site-packages\numpy\lib\function_base.py in _get_ufunc_and_otypes(self, func, args)
2144
2145 inputs = [arg.flat[0] for arg in args]
-> 2146 outputs = func(*inputs)
2147
2148 # Performance note: profiling indicates that -- for simple
C:\Program Files\Anaconda3\lib\site-packages\matplotlib\dates.py in _to_ordinalf(dt)
243 tzi = UTC
244
--> 245 base = float(dt.toordinal())
246
247 # If it's sufficiently datetime-like, it will have a `date()` method
AttributeError: 'numpy.datetime64' object has no attribute 'toordinal'
答案 0 :(得分：0)
旧版本的 matplotlib (2.1.2) 已经过时，不再与新版本的 pandas (1.1.5) 兼容。升级到 matplotlib 3.3.4 解决了这个问题 - 如评论中所述。