ValueError: If using all scalar values, you must pass an index

[nPokemon]

ValueError Traceback (most recent call last)
in <cell line: 5>()
3
4 # Run ensemble strategy and store the result
----> 5 result = ensemble_agent.run_ensemble_strategy(A2C_model_kwargs,
6 PPO_model_kwargs,
7 DDPG_model_kwargs,

5 frames
/usr/local/lib/python3.10/site-packages/pandas/core/internals/construction.py in _extract_index(data)
643
644 if not indexes and not raw_lengths:
--> 645 raise ValueError("If using all scalar values, you must pass an index")
646
647 if have_series:

ValueError: If using all scalar values, you must pass an index

I have try many way to fix it, but no luck, any one have any idea ?

[Sotokama]

Also facing the same error

[Omar-ALkhateeb]

same issue

[rendezvoush]

Yeah, the same issue after "pip install stable-baselines3==2.0.0a5"

======DDPG Validation from: 2021-10-04 to 2022-01-03
======Best Model Retraining from: 2010-01-01 to 2022-01-03
======Trading from: 2022-01-03 to 2022-04-04

Then the following error raised:

---

ValueError Traceback (most recent call last)
d:\Projects\Python\DQN\FinRL_Ensemble_StockTrading_ICAIF_2020.ipynb Cell 36 in ()
----> 1 df_summary = ensemble_agent.run_ensemble_strategy(A2C_model_kwargs,
2 PPO_model_kwargs,
3 DDPG_model_kwargs,
4 timesteps_dict)

File d:\ProgramData\Anaconda3\envs\develop\lib\site-packages\finrl\agents\stablebaselines3\models.py:668, in DRLEnsembleAgent.run_ensemble_strategy(self, A2C_model_kwargs, PPO_model_kwargs, DDPG_model_kwargs, timesteps_dict)
661 print(
662 "======Trading from: ",
663 self.unique_trade_date[i - self.rebalance_window],
664 "to ",
665 self.unique_trade_date[i],
666 )
667 # print("Used Model: ", model_ensemble)
--> 668 last_state_ensemble = self.DRL_prediction(
669 model=model_ensemble,
670 name="ensemble",
671 last_state=last_state_ensemble,
672 iter_num=i,
673 turbulence_threshold=turbulence_threshold,
674 initial=initial,
675 )
676 ############## Trading ends ##############
678 end = time.time()

File d:\ProgramData\Anaconda3\envs\develop\lib\site-packages\finrl\agents\stablebaselines3\models.py:321, in DRLEnsembleAgent.DRL_prediction(self, model, name, last_state, iter_num, turbulence_threshold, initial)
317 if i == (len(trade_data.index.unique()) - 2):
318 # print(env_test.render())
319 last_state = trade_env.render()
--> 321 df_last_state = pd.DataFrame({"last_state": last_state})
322 df_last_state.to_csv(f"results/last_state_{name}_{i}.csv", index=False)
323 return last_state

File d:\ProgramData\Anaconda3\envs\develop\lib\site-packages\pandas\core\frame.py:636, in DataFrame.init(self, data, index, columns, dtype, copy)
630 mgr = self._init_mgr(
631 data, axes={"index": index, "columns": columns}, dtype=dtype, copy=copy
632 )
634 elif isinstance(data, dict):
635 # GH#38939 de facto copy defaults to False only in non-dict cases
--> 636 mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
637 elif isinstance(data, ma.MaskedArray):
638 import numpy.ma.mrecords as mrecords

File d:\ProgramData\Anaconda3\envs\develop\lib\site-packages\pandas\core\internals\construction.py:502, in dict_to_mgr(data, index, columns, dtype, typ, copy)
494 arrays = [
495 x
496 if not hasattr(x, "dtype") or not isinstance(x.dtype, ExtensionDtype)
497 else x.copy()
498 for x in arrays
499 ]
500 # TODO: can we get rid of the dt64tz special case above?
--> 502 return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)

File d:\ProgramData\Anaconda3\envs\develop\lib\site-packages\pandas\core\internals\construction.py:120, in arrays_to_mgr(arrays, columns, index, dtype, verify_integrity, typ, consolidate)
117 if verify_integrity:
118 # figure out the index, if necessary
119 if index is None:
--> 120 index = _extract_index(arrays)
121 else:
122 index = ensure_index(index)

File d:\ProgramData\Anaconda3\envs\develop\lib\site-packages\pandas\core\internals\construction.py:664, in _extract_index(data)
661 raise ValueError("Per-column arrays must each be 1-dimensional")
663 if not indexes and not raw_lengths:
--> 664 raise ValueError("If using all scalar values, you must pass an index")
666 elif have_series:
667 index = union_indexes(indexes)

ValueError: If using all scalar values, you must pass an index

[Aashish-1008]

Yeah, the same issue after "pip install stable-baselines3==2.0.0a5"

======DDPG Validation from: 2021-10-04 to 2022-01-03
======Best Model Retraining from: 2010-01-01 to 2022-01-03
======Trading from: 2022-01-03 to 2022-04-04

Then the following error raised:

[kilmern]

Likewise. Same problem after the suggested fix in #1022

[AkashKarnatak]

This commit by stable-baseline3 is the cause of above error. Changing line 319 of finrl/agents/stablebaselines3/models.py from,

last_state = trade_env.render()

to

last_state = trade_env.envs[0].render()

fixes the error.

[MariamaB]

ValueError: operands could not be broadcast together with shapes (30,) (29,)

Facing the following error when running:

df_summary = ensemble_agent.run_ensemble_strategy(A2C_model_kwargs,
PPO_model_kwargs,
DDPG_model_kwargs,
timesteps_dict)

Does anyone know how to fix it?

==================================================================================

Full Error:

ValueError Traceback (most recent call last)
in <cell line: 1>()
----> 1 df_summary = ensemble_agent.run_ensemble_strategy(A2C_model_kwargs,
2 PPO_model_kwargs,
3 DDPG_model_kwargs,
4 timesteps_dict)

5 frames
/usr/local/lib/python3.10/dist-packages/finrl/agents/stablebaselines3/models.py in run_ensemble_strategy(self, A2C_model_kwargs, PPO_model_kwargs, DDPG_model_kwargs, timesteps_dict)
424 ],
425 )
--> 426 self.train_env = DummyVecEnv(
427 [
428 lambda: StockTradingEnv(

/usr/local/lib/python3.10/dist-packages/stable_baselines3/common/vec_env/dummy_vec_env.py in init(self, env_fns)
28
29 def init(self, env_fns: List[Callable[[], gym.Env]]):
---> 30 self.envs = [_patch_env(fn()) for fn in env_fns]
31 if len(set([id(env.unwrapped) for env in self.envs])) != len(self.envs):
32 raise ValueError(

/usr/local/lib/python3.10/dist-packages/stable_baselines3/common/vec_env/dummy_vec_env.py in (.0)
28
29 def init(self, env_fns: List[Callable[[], gym.Env]]):
---> 30 self.envs = [_patch_env(fn()) for fn in env_fns]
31 if len(set([id(env.unwrapped) for env in self.envs])) != len(self.envs):
32 raise ValueError(

/usr/local/lib/python3.10/dist-packages/finrl/agents/stablebaselines3/models.py in ()
426 self.train_env = DummyVecEnv(
427 [
--> 428 lambda: StockTradingEnv(
429 df=train,
430 stock_dim=self.stock_dim,

/usr/local/lib/python3.10/dist-packages/finrl/meta/env_stock_trading/env_stocktrading.py in init(self, df, stock_dim, hmax, initial_amount, num_stock_shares, buy_cost_pct, sell_cost_pct, reward_scaling, state_space, action_space, tech_indicator_list, turbulence_threshold, risk_indicator_col, make_plots, print_verbosity, day, initial, previous_state, model_name, mode, iteration)
74 self.iteration = iteration
75 # initalize state
---> 76 self.state = self._initiate_state()
77
78 # initialize reward

/usr/local/lib/python3.10/dist-packages/finrl/meta/env_stock_trading/env_stocktrading.py in _initiate_state(self)
401 # for multiple stock
402 state = (
--> 403 [self.initial_amount]
404 + self.data.close.values.tolist()
405 + self.num_stock_shares

ValueError: operands could not be broadcast together with shapes (30,) (29,)