我正在使用一个包含日期，温度和湿度数据的csv文件，然后使用pandas和matplotlib pyplot加载它以创建数据图。
对于某些日期时间值，我得到带有有效值的错误“ ValueError：年份超出范围”，没有明显的规律。
这是针对Raspberry Pi（通过apt-get完全更新），Python 2.7.13，pandas 0.19.2和matplotlib 2.0.0。我已经通过Google搜索查看了无数页面，但还没有任何工作。
请注意，我使用的是日/月/年格式（我在新西兰）。
好的行和坏的行之间没有明显的区别，即它们看起来都具有有效的日期和时间值以及相同的行尾（CR LF）。
显示问题的代码：
#!/usr/bin/env python2
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
filename = 'tempfile.csv'
df = pd.read_csv(filename, names=['DateTime','Air Temperature','Humidity','CPU Temperature'], header = 0)
df['DateTime'] = pd.to_datetime(df['DateTime'], format='%d/%m/%Y %H:%M', utc=None)
df.plot(kind='line',x='DateTime',y='Air Temperature')
ax = plt.gca()
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
plt.savefig('graph.png')
plt.close()
通常，这会导致生成图形，但是某些值会导致错误。
示例数据文件：
16/06/2019 02:15,13.7,90.6,30.0
16/06/2019 02:30,13.7,92.2,30.0
16/06/2019 02:45,13.6,92.2,30.0
16/06/2019 03:00,13.4,92.0,30.0
16/06/2019 03:15,13.5,91.9,28.9
16/06/2019 03:30,13.5,91.9,28.9
导致错误的行：
16/06/2019 03:15,13.5,91.9,28.9
“修复”是通过将分钟值减小1来修改时间分量，因此将问题行更改为以下结果可以避免错误。
16/06/2019 03:14,13.5,91.9,28.9
另一个“解决方法”是只保存csv数据的前三行或后三行。
另一个“修复程序”正在注释掉以下行，这虽然使x轴格式丢失，但也会导致代码正常工作。
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
这有效的事实使我认为错误消息错误地指出了一年的问题。
完整的错误消息是：
Traceback (most recent call last):
File "./max.py", line 18, in <module> plt.savefig('graph.png')
File "/usr/lib/python2.7/dist-packages/matplotlib/pyplot.py", line 697, in savefig res = fig.savefig(*args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/figure.py", line 1572, in savefig self.canvas.print_figure(*args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/backend_bases.py", line 2244, in print_figure **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.py", line 545, in print_png FigureCanvasAgg.draw(self)
File "/usr/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.py", line 464, in draw self.figure.draw(self.renderer)
File "/usr/lib/python2.7/dist-packages/matplotlib/artist.py", line 63, in draw_wrapper draw(artist, renderer, *args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/figure.py", line 1143, in draw renderer, self, dsu, self.suppressComposite)
File "/usr/lib/python2.7/dist-packages/matplotlib/image.py", line 139, in _draw_list_compositing_images a.draw(renderer)
File "/usr/lib/python2.7/dist-packages/matplotlib/artist.py", line 63, in draw_wrapper draw(artist, renderer, *args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/axes/_base.py", line 2409, in draw mimage._draw_list_compositing_images(renderer, self, dsu)
File "/usr/lib/python2.7/dist-packages/matplotlib/image.py", line 139, in _draw_list_compositing_images a.draw(renderer)
File "/usr/lib/python2.7/dist-packages/matplotlib/artist.py", line 63, in draw_wrapper draw(artist, renderer, *args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/axis.py", line 1136, in draw ticks_to_draw = self._update_ticks(renderer)
File "/usr/lib/python2.7/dist-packages/matplotlib/axis.py", line 969, in _update_ticks tick_tups = [t for t in self.iter_ticks()]
File "/usr/lib/python2.7/dist-packages/matplotlib/axis.py", line 916, in iter_ticks for i, val in enumerate(majorLocs)]
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 466, in __call__ dt = num2date(x, self.tz)
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 401, in num2date return _from_ordinalf(x, tz)
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 254, in _from_ordinalf dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC)
ValueError: year is out of range
已更新为仅显示最小测试用例。
统计函数是用于计算均值和标准差的函数，由于不影响结果，因此已从上述代码中删除。