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AttributeError: Unknown property color_cycle

I am learning 'pandas' and trying to plot id column but I get an error AttributeError: Unknown property color_cycle and empty graph. The graph only appears in interactive shell. When I execute as script I get same error except the graph doesn't appear.

Below is the log:

>>> import pandas as pd
>>> pd.set_option('display.mpl_style', 'default')
>>> df = pd.read_csv('2015.csv', parse_dates=['log_date'])
>>> employee_198 = df[df['employee_id'] == 198]
>>> print(employee_198)
          id  version  company_id early_minutes  employee_id late_minutes  \
90724  91635        0           1           NaN          198          NaN
90725  91636        0           1           NaN          198      0:20:00
90726  91637        0           1       0:20:00          198          NaN
90727  91638        0           1       0:05:00          198          NaN
90728  91639        0           1       0:25:00          198          NaN
90729  91640        0           1       0:15:00          198      0:20:00
90730  91641        0           1           NaN          198      0:15:00
90731  91642        0           1           NaN          198          NaN
90732  91643        0           1           NaN          198          NaN
90733  91644        0           1           NaN          198          NaN
90734  91645        0           1           NaN          198          NaN
90735  91646        0           1           NaN          198          NaN
90736  91647        0           1           NaN          198          NaN
90737  91648        0           1           NaN          198          NaN
90738  91649        0           1           NaN          198          NaN
90739  91650        0           1           NaN          198      0:10:00
90740  91651        0           1           NaN          198          NaN
90741  91652        0           1           NaN          198          NaN
90742  91653        0           1           NaN          198          NaN
90743  91654        0           1           NaN          198          NaN
90744  91655        0           1           NaN          198          NaN
90745  91656        0           1           NaN          198          NaN
90746  91657        0           1       1:30:00          198          NaN
90747  91658        0           1       0:04:25          198          NaN
90748  91659        0           1           NaN          198          NaN
90749  91660        0           1           NaN          198          NaN
90750  91661        0           1           NaN          198          NaN
90751  91662        0           1           NaN          198          NaN
90752  91663        0           1           NaN          198          NaN
90753  91664        0           1           NaN          198          NaN
90897  91808        0           1           NaN          198      0:04:14
91024  91935        0           1           NaN          198      0:21:43
91151  92062        0           1           NaN          198      0:42:07
91278  92189        0           1           NaN          198      0:16:36
91500  92411        0           1           NaN          198      0:07:12
91532  92443        0           1           NaN          198          NaN
91659  92570        0           1           NaN          198      0:53:03
91786  92697        0           1           NaN          198          NaN
91913  92824        0           1           NaN          198          NaN
92040  92951        0           1           NaN          198          NaN
92121  93032        0           1       4:22:35          198          NaN
92420  93331        0           1           NaN          198          NaN
92421  93332        0           1           NaN          198      3:51:15

        log_date log_in_time log_out_time over_time           remarks  \
90724 2015-11-15       No In       No Out       NaN          [Absent]
90725 2015-10-18    10:00:00     17:40:00       NaN               NaN
90726 2015-10-19     9:20:00     17:10:00       NaN               NaN
90727 2015-10-25     9:30:00     17:25:00       NaN               NaN
90728 2015-10-26     9:34:00     17:05:00       NaN               NaN
90729 2015-10-27    10:00:00     17:15:00       NaN               NaN
90730 2015-10-28     9:55:00     17:30:00       NaN               NaN
90731 2015-10-29     9:40:00     17:30:00       NaN               NaN
90732 2015-10-30     9:00:00     17:30:00   0:30:00               NaN
90733 2015-10-20       No In       No Out       NaN          [Absent]
90734 2015-10-21       No In       No Out       NaN    [Maha Asthami]
90735 2015-10-22       No In       No Out       NaN  [Nawami/Dashami]
90736 2015-10-23       No In       No Out       NaN          [Absent]
90737 2015-10-24       No In       No Out       NaN             [Off]
90738 2015-11-01     9:15:00     17:30:00   0:15:00               NaN
90739 2015-11-02     9:50:00     17:30:00       NaN               NaN
90740 2015-11-03     9:30:00     17:30:00       NaN               NaN
90741 2015-11-04     9:40:00     17:30:00       NaN               NaN
90742 2015-11-05     9:38:00     17:30:00       NaN               NaN
90743 2015-11-06     9:30:00     17:30:00       NaN               NaN
90744 2015-11-08     9:30:00     17:30:00       NaN               NaN
90745 2015-11-09     9:30:00     17:30:00       NaN               NaN
90746 2015-11-10     9:30:00     16:00:00       NaN               NaN
90747 2015-11-16     9:30:00     17:25:35       NaN               NaN
90748 2015-11-07       No In       No Out       NaN             [Off]
90749 2015-11-11       No In       No Out       NaN      [Laxmi Puja]
90750 2015-11-12       No In       No Out       NaN  [Govardhan Puja]
90751 2015-11-13       No In       No Out       NaN       [Bhai Tika]
90752 2015-11-14       No In       No Out       NaN             [Off]
90753 2015-10-31       No In       No Out       NaN             [Off]
90897 2015-11-17     9:44:14     17:35:01       NaN               NaN
91024 2015-11-18    10:01:43     17:36:29       NaN               NaN
91151 2015-11-19    10:22:07     17:43:47       NaN               NaN
91278 2015-11-20     9:56:36     17:37:00       NaN               NaN
91500 2015-11-22     9:47:12     17:46:44       NaN               NaN
91532 2015-11-21       No In       No Out       NaN             [Off]
91659 2015-11-23    10:33:03     17:30:00       NaN               NaN
91786 2015-11-24     9:34:11     17:32:24       NaN               NaN
91913 2015-11-25     9:36:05     17:35:00       NaN               NaN
92040 2015-11-26     9:35:39     17:58:05   0:22:26               NaN
92121 2015-11-27     9:08:45     13:07:25       NaN               NaN
92420 2015-11-28       No In       No Out       NaN             [Off]
92421 2015-11-29    13:31:15     17:34:44       NaN               NaN

      shift_in_time shift_out_time work_time under_time
90724       9:30:00       17:30:00       NaN        NaN
90725       9:30:00       17:30:00   7:40:00    0:20:00
90726       9:30:00       17:30:00   7:50:00    0:10:00
90727       9:30:00       17:30:00   7:55:00    0:05:00
90728       9:30:00       17:30:00   7:31:00    0:29:00
90729       9:30:00       17:30:00   7:15:00    0:45:00
90730       9:30:00       17:30:00   7:35:00    0:25:00
90731       9:30:00       17:30:00   7:50:00    0:10:00
90732       9:30:00       17:30:00   8:30:00        NaN
90733       9:30:00       17:30:00       NaN        NaN
90734       9:30:00       17:30:00       NaN        NaN
90735       9:30:00       17:30:00       NaN        NaN
90736       9:30:00       17:30:00       NaN        NaN
90737       9:30:00       17:30:00       NaN        NaN
90738       9:30:00       17:30:00   8:15:00        NaN
90739       9:30:00       17:30:00   7:40:00    0:20:00
90740       9:30:00       17:30:00   8:00:00        NaN
90741       9:30:00       17:30:00   7:50:00    0:10:00
90742       9:30:00       17:30:00   7:52:00    0:08:00
90743       9:30:00       17:30:00   8:00:00        NaN
90744       9:30:00       17:30:00   8:00:00        NaN
90745       9:30:00       17:30:00   8:00:00        NaN
90746       9:30:00       17:30:00   6:30:00    1:30:00
90747       9:30:00       17:30:00   7:55:35    0:04:25
90748       9:30:00       17:30:00       NaN        NaN
90749       9:30:00       17:30:00       NaN        NaN
90750       9:30:00       17:30:00       NaN        NaN
90751       9:30:00       17:30:00       NaN        NaN
90752       9:30:00       17:30:00       NaN        NaN
90753       9:30:00       17:30:00       NaN        NaN
90897       9:30:00       17:30:00   7:50:47    0:09:13
91024       9:30:00       17:30:00   7:34:46    0:25:14
91151       9:30:00       17:30:00   7:21:40    0:38:20
91278       9:30:00       17:30:00   7:40:24    0:19:36
91500       9:30:00       17:30:00   7:59:32    0:00:28
91532       9:30:00       17:30:00       NaN        NaN
91659       9:30:00       17:30:00   6:56:57    1:03:03
91786       9:30:00       17:30:00   7:58:13    0:01:47
91913       9:30:00       17:30:00   7:58:55    0:01:05
92040       9:30:00       17:30:00   8:22:26        NaN
92121       9:30:00       17:30:00   3:58:40    4:01:20
92420       9:30:00       17:30:00       NaN        NaN
92421       9:30:00       17:30:00   4:03:29    3:56:31
>>> employee_198['id'].plot()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 3497, in __call__
    **kwds)
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 2587, in plot_series
    **kwds)
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 2384, in _plot
    plot_obj.generate()
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 987, in generate
    self._make_plot()
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 1664, in _make_plot
    **kwds)
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 1678, in _plot
    lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)
  File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 1300, in _plot
    return ax.plot(*args, **kwds)
  File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 1811, in inner
    return func(ax, *args, **kwargs)
  File "C:\Python27\lib\site-packages\matplotlib\axes\_axes.py", line 1427, in plot
    for line in self._get_lines(*args, **kwargs):
  File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 386, in _grab_next_args
    for seg in self._plot_args(remaining, kwargs):
  File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 374, in _plot_args
    seg = func(x[:, j % ncx], y[:, j % ncy], kw, kwargs)
  File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 280, in _makeline
    seg = mlines.Line2D(x, y, **kw)
  File "C:\Python27\lib\site-packages\matplotlib\lines.py", line 366, in __init__
    self.update(kwargs)
  File "C:\Python27\lib\site-packages\matplotlib\artist.py", line 856, in update
    raise AttributeError('Unknown property %s' % k)
AttributeError: Unknown property color_cycle
>>>
like image 651
mailtosumitrai Avatar asked Nov 30 '15 09:11

mailtosumitrai


1 Answers

There's currently a bug in Pandas 0.17.1 with Matplotlib 1.5.0

print pandas.__version__
print matplotlib.__version__

Instead of using

import pandas as pd
pd.set_option('display.mpl_style', 'default')

Use:

import matplotlib
matplotlib.style.use('ggplot')
like image 147
rhinoinrepose Avatar answered Oct 25 '22 08:10

rhinoinrepose