When I use the alphalens.tears.create_event_returns_tear_sheet, it shows one error: unsupported operand type(s) for -: 'slice' and 'int', besides other functions work well. Looking forwards someone could help me. Thank you.
Please provide a minimal, self-contained, and reproducible example:
[Paste code here]
**alphalens.tears.create_event_returns_tear_sheet(data,
returns,
avgretplot=(5, 15),
long_short=True,
group_neutral=False,
std_bar=True,
by_group=False)**
**Please provide the full traceback:**
```python
[Paste traceback here]
```---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
D:\Anaconda\lib\site-packages\pandas\core\groupby\groupby.py in apply(self, func, *args, **kwargs)
734 try:
--> 735 result = self._python_apply_general(f)
736 except TypeError:
D:\Anaconda\lib\site-packages\pandas\core\groupby\groupby.py in _python_apply_general(self, f)
750 def _python_apply_general(self, f):
--> 751 keys, values, mutated = self.grouper.apply(f, self._selected_obj, self.axis)
752
D:\Anaconda\lib\site-packages\pandas\core\groupby\ops.py in apply(self, f, data, axis)
205 group_axes = group.axes
--> 206 res = f(group)
207 if not _is_indexed_like(res, group_axes):
D:\Anaconda\lib\site-packages\pandas\core\groupby\groupby.py in f(g)
718 with np.errstate(all="ignore"):
--> 719 return func(g, *args, **kwargs)
720
D:\Anaconda\lib\site-packages\alphalens\performance.py in average_cumulative_return(q_fact, demean_by)
802 def average_cumulative_return(q_fact, demean_by):
--> 803 q_returns = cumulative_return_around_event(q_fact, demean_by)
804 q_returns.replace([np.inf, -np.inf], np.nan, inplace=True)
D:\Anaconda\lib\site-packages\alphalens\performance.py in cumulative_return_around_event(q_fact, demean_by)
798 mean_by_date=True,
--> 799 demean_by=demean_by,
800 )
D:\Anaconda\lib\site-packages\alphalens\performance.py in common_start_returns(factor, returns, before, after, cumulative, mean_by_date, demean_by)
701
--> 702 starting_index = max(day_zero_index - before, 0)
703 ending_index = min(day_zero_index + after + 1,
TypeError: unsupported operand type(s) for -: 'slice' and 'int'
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
<ipython-input-46-6fc348201897> in <module>
5 group_neutral=False,
6 std_bar=True,
----> 7 by_group=False)
D:\Anaconda\lib\site-packages\alphalens\plotting.py in call_w_context(*args, **kwargs)
43 with plotting_context(), axes_style(), color_palette:
44 sns.despine(left=True)
---> 45 return func(*args, **kwargs)
46 else:
47 return func(*args, **kwargs)
D:\Anaconda\lib\site-packages\alphalens\tears.py in create_event_returns_tear_sheet(factor_data, returns, avgretplot, long_short, group_neutral, std_bar, by_group)
573 periods_after=after,
574 demeaned=long_short,
--> 575 group_adjust=group_neutral,
576 )
577
D:\Anaconda\lib\site-packages\alphalens\performance.py in average_cumulative_return_by_quantile(factor_data, returns, periods_before, periods_after, demeaned, group_adjust, by_group)
858 elif demeaned:
859 fq = factor_data['factor_quantile']
--> 860 return fq.groupby(fq).apply(average_cumulative_return, fq)
861 else:
862 fq = factor_data['factor_quantile']
D:\Anaconda\lib\site-packages\pandas\core\groupby\generic.py in apply(self, func, *args, **kwargs)
222 )
223 def apply(self, func, *args, **kwargs):
--> 224 return super().apply(func, *args, **kwargs)
225
226 @Substitution(
D:\Anaconda\lib\site-packages\pandas\core\groupby\groupby.py in apply(self, func, *args, **kwargs)
744
745 with _group_selection_context(self):
--> 746 return self._python_apply_general(f)
747
748 return result
D:\Anaconda\lib\site-packages\pandas\core\groupby\groupby.py in _python_apply_general(self, f)
749
750 def _python_apply_general(self, f):
--> 751 keys, values, mutated = self.grouper.apply(f, self._selected_obj, self.axis)
752
753 return self._wrap_applied_output(
D:\Anaconda\lib\site-packages\pandas\core\groupby\ops.py in apply(self, f, data, axis)
204 # group might be modified
205 group_axes = group.axes
--> 206 res = f(group)
207 if not _is_indexed_like(res, group_axes):
208 mutated = True
D:\Anaconda\lib\site-packages\pandas\core\groupby\groupby.py in f(g)
717 def f(g):
718 with np.errstate(all="ignore"):
--> 719 return func(g, *args, **kwargs)
720
721 elif hasattr(nanops, "nan" + func):
D:\Anaconda\lib\site-packages\alphalens\performance.py in average_cumulative_return(q_fact, demean_by)
801
802 def average_cumulative_return(q_fact, demean_by):
--> 803 q_returns = cumulative_return_around_event(q_fact, demean_by)
804 q_returns.replace([np.inf, -np.inf], np.nan, inplace=True)
805
D:\Anaconda\lib\site-packages\alphalens\performance.py in cumulative_return_around_event(q_fact, demean_by)
797 cumulative=True,
798 mean_by_date=True,
--> 799 demean_by=demean_by,
800 )
801
D:\Anaconda\lib\site-packages\alphalens\performance.py in common_start_returns(factor, returns, before, after, cumulative, mean_by_date, demean_by)
700 continue
701
--> 702 starting_index = max(day_zero_index - before, 0)
703 ending_index = min(day_zero_index + after + 1,
704 len(returns.index))
TypeError: unsupported operand type(s) for -: 'slice' and 'int'
<Figure size 432x288 with 0 Axes>
**Please provide any additional information below:**
## Versions
* Alphalens version: 0.4.0
* Python version: 3.7.6
* Pandas version: 1.0.1
* Matplotlib version: 3.1.3
Problem Description
When I use the alphalens.tears.create_event_returns_tear_sheet, it shows one error: unsupported operand type(s) for -: 'slice' and 'int', besides other functions work well. Looking forwards someone could help me. Thank you.
Please provide a minimal, self-contained, and reproducible example: