ValueError: cannot convert float NaN to integer

[athenawisdoms]

Hi, I think that when there is no drawdown, we will get the error:

ValueError: cannot convert float NaN to integer

This problem was previously closed without being completely fixed #2

Here's the error traceback:

Traceback (most recent call last):
  File "test.py", line 269, in <module>
    qs.reports.html(returns['net_worth'], benchmark, output=os.path.join(projectDir, 'report.html'))
  File "/home/athena/anaconda3/envs/unicorn/lib/python3.8/site-packages/quantstats/reports.py", line 58, in html
    mtrx = metrics(returns=returns, benchmark=benchmark,
  File "/home/athena/anaconda3/envs/unicorn/lib/python3.8/site-packages/quantstats/reports.py", line 299, in metrics
    dd = _calc_dd(df, display=(display or "internal" in kwargs))
  File "/home/athena/anaconda3/envs/unicorn/lib/python3.8/site-packages/quantstats/reports.py", line 587, in _calc_dd
    'Longest DD Days': str(round(bench_dd.sort_values(
ValueError: cannot convert float NaN to integer

Using quantstats 0.0.25, pandas 1.0.3

Thanks!

[lorrp1]

@ranaroussi qs.stats.sharpe() works fine but i cant make a full report probably due to "drawdown"

ValueError                                Traceback (most recent call last)
<ipython-input-76-d9a4a8ed1010> in <module>
      5 returns = net_worth.pct_change().iloc[1:]
      6 returns.iloc[3] = -0.01
----> 7 qs.reports.full(returns)
      8 qs.reports.html(returns, output='a2c_quantstats.html')

~/.local/lib/python3.6/site-packages/quantstats/reports.py in full(returns, benchmark, rf, grayscale, figsize, display, compounded)
    212 
    213     dd = _stats.to_drawdown_series(returns)
--> 214     dd_info = _stats.drawdown_details(dd).sort_values(
    215         by='max drawdown', ascending=True)[:5]
    216 

~/.local/lib/python3.6/site-packages/quantstats/stats.py in drawdown_details(drawdown)
    558         return _pd.concat(_dfs, axis=1)
    559 
--> 560     return _drawdown_details(drawdown)
    561 
    562 

~/.local/lib/python3.6/site-packages/quantstats/stats.py in _drawdown_details(drawdown)
    534             dd = drawdown[starts[i]:ends[i]]
    535             clean_dd = -remove_outliers(-dd, .99)
--> 536             data.append((starts[i], dd.idxmin(), ends[i],
    537                          (ends[i] - starts[i]).days,
    538                          dd.min() * 100, clean_dd.min() * 100))

~/.local/lib/python3.6/site-packages/pandas/core/series.py in idxmin(self, axis, skipna, *args, **kwargs)
   2037         """
   2038         skipna = nv.validate_argmin_with_skipna(skipna, args, kwargs)
-> 2039         i = nanops.nanargmin(com.values_from_object(self), skipna=skipna)
   2040         if i == -1:
   2041             return np.nan

~/.local/lib/python3.6/site-packages/pandas/core/nanops.py in _f(*args, **kwargs)
     67             try:
     68                 with np.errstate(invalid="ignore"):
---> 69                     return f(*args, **kwargs)
     70             except ValueError as e:
     71                 # we want to transform an object array

~/.local/lib/python3.6/site-packages/pandas/core/nanops.py in nanargmin(values, axis, skipna, mask)
    904         values, True, fill_value_typ="+inf", mask=mask
    905     )
--> 906     result = values.argmin(axis)
    907     result = _maybe_arg_null_out(result, axis, mask, skipna)
    908     return result

ValueError: attempt to get argmin of an empty sequence

[Karlheinzniebuhr]

Similar issue

qs.reports.full(returns=returns)
Output exceeds the [size limit](command:workbench.action.openSettings?[). Open the full output data [in a text editor](command:workbench.action.openLargeOutput?9def156d-e85f-4c2e-9aff-66aa19d6ca90)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
c:\dev\Python\Mastermind\mastermind\training\Reinforcement_learning\Reinforcement_Learning_with_gym_anytrading.ipynb Cell 27 in <cell line: 6>()
      [3](vscode-notebook-cell:/c%3A/dev/Python/Mastermind/mastermind/training/Reinforcement_learning/Reinforcement_Learning_with_gym_anytrading.ipynb#X50sZmlsZQ%3D%3D?line=2) net_worth = pd.Series(multi_env.history['total_profit'], index=df.index[test_frame_bound[0]+1:test_frame_bound[1]], name='Net Worth')
      [4](vscode-notebook-cell:/c%3A/dev/Python/Mastermind/mastermind/training/Reinforcement_learning/Reinforcement_Learning_with_gym_anytrading.ipynb#X50sZmlsZQ%3D%3D?line=3) returns = net_worth.pct_change().dropna()
----> [6](vscode-notebook-cell:/c%3A/dev/Python/Mastermind/mastermind/training/Reinforcement_learning/Reinforcement_Learning_with_gym_anytrading.ipynb#X50sZmlsZQ%3D%3D?line=5) qs.reports.full(returns=returns)

File c:\ProgramData\Anaconda3\lib\site-packages\quantstats\reports.py:278, in full(returns, benchmark, rf, grayscale, figsize, display, compounded, periods_per_year, match_dates)
    275         returns, benchmark = _match_dates(returns, benchmark)
    277 dd = _stats.to_drawdown_series(returns)
--> 278 col = _stats.drawdown_details(dd).columns[4]
    279 dd_info = _stats.drawdown_details(dd).sort_values(by = col,
    280                                                    ascending = True)[:5]
    282 if not dd_info.empty:

File c:\ProgramData\Anaconda3\lib\site-packages\quantstats\stats.py:820, in drawdown_details(drawdown)
    817         _dfs[col] = _drawdown_details(drawdown[col])
    818     return _pd.concat(_dfs, axis=1)
--> 820 return _drawdown_details(drawdown)

File c:\ProgramData\Anaconda3\lib\site-packages\quantstats\stats.py:796, in drawdown_details.<locals>._drawdown_details(drawdown)
    794     dd = drawdown[starts[i]:ends[i]]
    795     clean_dd = -remove_outliers(-dd, .99)
--> 796     data.append((starts[i], dd.idxmin(), ends[i],
    797                  (ends[i] - starts[i]).days,
...
-> 1142 result = values.argmin(axis)  # type: ignore[var-annotated]
   1143 result = _maybe_arg_null_out(result, axis, mask, skipna)
   1144 return result

ValueError: attempt to get argmin of an empty sequence