我正在尝试绘制一些简单的时间序列，通常它可以正常工作，但是这种特殊情况无法获得预期的结果：
我在获得相同错误消息的Visual Studio和CLI中运行代码。但是，当我尝试在jupyter笔记本中运行相同的代码时，我得到了三个单元格（CELL1，CELL2和CELL3分开），整个代码可以正常工作。仅当我将CELL2和CELL3放在一个单独的CELL中时，它才再次产生典型错误。
# CELL 1
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import datetime
from pandas import Series
import sys
input_array = np.array([[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.]])
date_list = [datetime.date(2019, 1, 2), datetime.date(2019, 1, 9), datetime.date(2019, 1, 16), datetime.date(2019, 1, 23), datetime.date(2019, 1, 30), datetime.date(2019, 2, 6), datetime.date(2019, 2, 13), datetime.date(2019, 2, 20), datetime.date(2019, 2, 27), datetime.date(2019, 3, 6), datetime.date(2019, 3, 13), datetime.date(2019, 3, 20), datetime.date(2019, 3, 27), datetime.date(2019, 4, 3), datetime.date(2019, 4, 10)]
def get_indiv_series(table, index):
out_series = []
for i in table:
out_series.append(i[index])
return out_series
def make_indiv_category_plot(times, table, index, axis):
print(get_indiv_series(table, index))
series = Series(get_indiv_series(table, index), index=times)
try:
series.plot(style='-', ax=axis)
except ValueError as err:
print(' A value Error ocurred')
print(index)
print(series)
print(get_indiv_series(table, index))
print(sys.exc_info())
raise err
line_i, = plt.plot([])
return line_i
# CELL 2
fig = plt.figure(figsize=(10, 10))
ax = plt.gca()
# CELL 3
line_0 = make_indiv_category_plot(date_list, input_array, 0, ax)
line_1 = make_indiv_category_plot(date_list, input_array, 1, ax)
line_2 = make_indiv_category_plot(date_list, input_array, 2, ax)
line_3 = make_indiv_category_plot(date_list, input_array, 3, ax)
line_4 = make_indiv_category_plot(date_list, input_array, 4, ax)
结果（合并CELL2和CELL 3）：
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
2019-01-02 0.0
2019-01-09 0.0
2019-01-16 0.0
2019-01-23 0.0
2019-01-30 0.0
2019-02-06 0.0
2019-02-13 0.0
2019-02-20 0.0
2019-02-27 0.0
2019-03-06 0.0
2019-03-13 0.0
2019-03-20 0.0
2019-03-27 0.0
2019-04-03 0.0
2019-04-10 0.0
dtype: float64
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
2019-01-02 0.0
2019-01-09 0.0
2019-01-16 0.0
2019-01-23 0.0
2019-01-30 0.0
2019-02-06 0.0
2019-02-13 0.0
2019-02-20 0.0
2019-02-27 0.0
2019-03-06 0.0
2019-03-13 0.0
2019-03-20 0.0
2019-03-27 0.0
2019-04-03 0.0
2019-04-10 0.0
dtype: float64
A value Error ocurred
1
2019-01-02 0.0
2019-01-09 0.0
2019-01-16 0.0
2019-01-23 0.0
2019-01-30 0.0
2019-02-06 0.0
2019-02-13 0.0
2019-02-20 0.0
2019-02-27 0.0
2019-03-06 0.0
2019-03-13 0.0
2019-03-20 0.0
2019-03-27 0.0
2019-04-03 0.0
2019-04-10 0.0
dtype: float64
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
(<class 'ValueError'>, ValueError('zero-size array to reduction operation fmin which has no identity',), <traceback object at 0x000001DB4550C208>)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-4-814d54a9ca4b> in <module>()
5 line_0 = make_indiv_category_plot(date_list, input_array, 0, ax)
6
----> 7 line_1 = make_indiv_category_plot(date_list, input_array, 1, ax)
8
9 line_2 = make_indiv_category_plot(date_list, input_array, 2, ax)
<ipython-input-3-ddbd896b3735> in make_indiv_category_plot(times, table, index, axis)
57 print(get_indiv_series(table, index))
58 print(sys.exc_info())
---> 59 raise err
60 # create a empty line with the same properties as the time series for legends
61 line_i, = plt.plot([])#, color='%s'%db_fplive.Get_color_table()[index+1], label=db_fplive.Get_label_table()[index+1])
<ipython-input-3-ddbd896b3735> in make_indiv_category_plot(times, table, index, axis)
48 # plot the series with the color and label from the category dictionaries
49 try:
---> 50 series.plot()#style='-', ax=axis, color='%s'%db_fplive.Get_color_table()[index+1], label=db_fplive.Get_label_table()[index+1])
51 except ValueError as err:
52 print(' A value Error ocurred')
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\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
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\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
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\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
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\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()
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_core.py in _make_plot(self)
998
999 lines = _get_all_lines(ax)
-> 1000 left, right = _get_xlim(lines)
1001 ax.set_xlim(left, right)
1002
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_tools.py in _get_xlim(lines)
362 for l in lines:
363 x = l.get_xdata(orig=False)
--> 364 left = min(np.nanmin(x), left)
365 right = max(np.nanmax(x), right)
366 return left, right
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\numpy\lib\nanfunctions.py in nanmin(a, axis, out, keepdims)
278 # Fast, but not safe for subclasses of ndarray, or object arrays,
279 # which do not implement isnan (gh-9009), or fmin correctly (gh-8975)
--> 280 res = np.fmin.reduce(a, axis=axis, out=out, **kwargs)
281 if np.isnan(res).any():
282 warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2)
ValueError: zero-size array to reduction operation fmin which has no identity
有人知道如何处理该问题或熟悉该错误消息吗？
答案 0 :(得分：0)
好的，与此同时，我找到了解决方案以使代码正常工作：
将创建的Series对象转换为具有一列的DataFrame对象（其内部表示形式仍应为Series对象）
总而言之，以下代码神奇地起作用：
# CELL 1
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import datetime
from pandas import Series
import sys
input_array = np.array([[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.]])
date_list = [datetime.date(2019, 1, 2), datetime.date(2019, 1, 9), datetime.date(2019, 1, 16), datetime.date(2019, 1, 23), datetime.date(2019, 1, 30), datetime.date(2019, 2, 6), datetime.date(2019, 2, 13), datetime.date(2019, 2, 20), datetime.date(2019, 2, 27), datetime.date(2019, 3, 6), datetime.date(2019, 3, 13), datetime.date(2019, 3, 20), datetime.date(2019, 3, 27), datetime.date(2019, 4, 3), datetime.date(2019, 4, 10)]
def get_indiv_series(table, index):
out_series = []
for i in table:
out_series.append(i[index])
return out_series
def make_indiv_category_plot(times, table, index, axis):
print(get_indiv_series(table, index))
series = pd.DataFrame(get_indiv_series(table, index), index=times)
try:
series.plot(style='-', use_index = True)
except ValueError as err:
print(' A value Error ocurred')
print(index)
print(series)
print(get_indiv_series(table, index))
print(sys.exc_info())
raise err
line_i, = plt.plot([])
return line_i
fig = plt.figure(figsize=(10, 10))
ax = plt.gca()
line_0 = make_indiv_category_plot(date_list, input_array, 0, ax)
line_1 = make_indiv_category_plot(date_list, input_array, 1, ax)
line_2 = make_indiv_category_plot(date_list, input_array, 2, ax)
line_3 = make_indiv_category_plot(date_list, input_array, 3, ax)
line_4 = make_indiv_category_plot(date_list, input_array, 4, ax)
给任何人关于这种奇怪行为的解释？