far.create_full_tear_sheet 报错

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TypeError Traceback (most recent call last)
in
11 far.create_full_tear_sheet(
12 demeaned=False, group_adjust=False, by_group=False,
---> 13 turnover_periods=None, avgretplot=(5, 2), std_bar=False
14 )

D:\Anoconda\app\Lib\site-packages\jqfactor_analyzer\analyze.py in create_full_tear_sheet(self, demeaned, group_adjust, by_group, turnover_periods, avgretplot, std_bar)
1461 self.plot_quantile_returns_bar(by_group=False,
1462 demeaned=demeaned,
-> 1463 group_adjust=group_adjust)
1464 pl.plt.show()
1465 self.plot_cumulative_returns(period=None, demeaned=demeaned, group_adjust=group_adjust)

D:\Anoconda\app\Lib\site-packages\jqfactor_analyzer\analyze.py in plot_quantile_returns_bar(self, by_group, demeaned, group_adjust)
1038
1039 pl.plot_quantile_returns_bar(
-> 1040 mean_return_by_quantile, by_group=by_group, ylim_percentiles=None
1041 )
1042

D:\Anoconda\app\Lib\site-packages\jqfactor_analyzer\plot_utils.py in call_w_context(*args, **kwargs)
23 with plotting_context(), axes_style():
24 sns.despine(left=True)
---> 25 return func(*args, **kwargs)
26 else:
27 return func(*args, **kwargs)

D:\Anoconda\app\Lib\site-packages\jqfactor_analyzer\plotting.py in plot_quantile_returns_bar(mean_ret_by_q, by_group, ylim_percentiles, ax)
286
287 mean_ret_by_q.multiply(DECIMAL_TO_BPS).plot(
--> 288 kind='bar', title=QRETURNBAR.get("TITLE"), ax=ax
289 )
290 ax.set(xlabel="", ylabel=QRETURNBAR.get("YLABEL"), ylim=(ymin, ymax))

D:\Anoconda\app\Lib\site-packages\pandas\plotting_core.py in call(self, *args, **kwargs)
792 data.columns = label_name
793
--> 794 return plot_backend.plot(data, kind=kind, **kwargs)
795
796 def line(self, x=None, y=None, **kwargs):

D:\Anoconda\app\Lib\site-packages\pandas\plotting_matplotlib_init_.py in plot(data, kind, **kwargs)
60 kwargs["ax"] = getattr(ax, "left_ax", ax)
61 plot_obj = PLOT_CLASSES[kind](data, **kwargs)
---> 62 plot_obj.generate()
63 plot_obj.draw()
64 return plot_obj.result

D:\Anoconda\app\Lib\site-packages\pandas\plotting_matplotlib\core.py in generate(self)
277 def generate(self):
278 self._args_adjust()
--> 279 self._compute_plot_data()
280 self._setup_subplots()
281 self._make_plot()

D:\Anoconda\app\Lib\site-packages\pandas\plotting_matplotlib\core.py in _compute_plot_data(self)
402 data = data._convert(datetime=True, timedelta=True)
403 numeric_data = data.select_dtypes(
--> 404 include=[np.number, "datetime", "datetimetz", "timedelta"]
405 )
406

D:\Anoconda\app\Lib\site-packages\pandas\core\frame.py in select_dtypes(self, include, exclude)
3440 # the "union" of the logic of case 1 and case 2:
3441 # we get the included and excluded, and return their logical and
-> 3442 include_these = Series(not bool(include), index=self.columns)
3443 exclude_these = Series(not bool(exclude), index=self.columns)
3444

D:\Anoconda\app\Lib\site-packages\pandas\core\series.py in init(self, data, index, dtype, name, copy, fastpath)
312 data = data.copy()
313 else:
--> 314 data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
315
316 data = SingleBlockManager(data, index, fastpath=True)

D:\Anoconda\app\Lib\site-packages\pandas\core\internals\construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
710 value = maybe_cast_to_datetime(value, dtype)
711
--> 712 subarr = construct_1d_arraylike_from_scalar(value, len(index), dtype)
713
714 else:

D:\Anoconda\app\Lib\site-packages\pandas\core\dtypes\cast.py in construct_1d_arraylike_from_scalar(value, length, dtype)
1231 value = ensure_str(value)
1232
-> 1233 subarr = np.empty(length, dtype=dtype)
1234 subarr.fill(value)
1235

TypeError: Cannot interpret '<attribute 'dtype' of 'numpy.generic' objects>' as a data type