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	try accessing the file again later. If the file you are trying to
	access is particularly large or is shared with many people, it may
	take up to 24 hours to be able to view or download the file. If you
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	administrator. 

You may still be able to access the file from the browser:

	 https://drive.google.com/uc?id=1zmylV7XW2dfQVCLeg1LbllfQtHD2KUon 

Task exception was never retrieved
future: <Task finished name='Task-9' coro=<Connection.run() done, defined at C:\Users\J\anaconda3\lib\site-packages\playwright\_impl\_connection.py:240> exception=NotImplementedError()>
Traceback (most recent call last):
  File "C:\Users\J\anaconda3\lib\site-packages\playwright\_impl\_connection.py", line 247, in run
    await self._transport.connect()
  File "C:\Users\J\anaconda3\lib\site-packages\playwright\_impl\_transport.py", line 132, in connect
    raise exc
  File "C:\Users\J\anaconda3\lib\site-packages\playwright\_impl\_transport.py", line 120, in connect
    self._proc = await asyncio.create_subprocess_exec(
  File "C:\Users\J\anaconda3\lib\asyncio\subprocess.py", line 236, in create_subprocess_exec
    transport, protocol = await loop.subprocess_exec(
  File "C:\Users\J\anaconda3\lib\asyncio\base_events.py", line 1676, in subprocess_exec
    transport = await self._make_subprocess_transport(
  File "C:\Users\J\anaconda3\lib\asyncio\base_events.py", line 498, in _make_subprocess_transport
    raise NotImplementedError

---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_16536\3703175856.py in <module>
----> 1 html= await get_html(url,'#content.filter')

~\AppData\Local\Temp\ipykernel_16536\3669287910.py in get_html(url, selector, sleep, retries)
      4         time.sleep(sleep * i)
      5         try:
----> 6             async with async_playwright() as p:
      7                 browser = await p.firefox.launch()
      8                 page = await browser.new_page()

~\anaconda3\lib\site-packages\playwright\async_api\_context_manager.py in __aenter__(self)
     44         if not playwright_future.done():
     45             playwright_future.cancel()
---> 46         playwright = AsyncPlaywright(next(iter(done)).result())
     47         playwright.stop = self.__aexit__  # type: ignore
     48         return playwright

~\anaconda3\lib\site-packages\playwright\_impl\_connection.py in run(self)
    245             self.playwright_future.set_result(await self._root_object.initialize())
    246 
--> 247         await self._transport.connect()
    248         self._init_task = self._loop.create_task(init())
    249         await self._transport.run()

~\anaconda3\lib\site-packages\playwright\_impl\_transport.py in connect(self)
    130         except Exception as exc:
    131             self.on_error_future.set_exception(exc)
--> 132             raise exc
    133 
    134         self._output = self._proc.stdin

~\anaconda3\lib\site-packages\playwright\_impl\_transport.py in connect(self)
    118                 env.setdefault("PLAYWRIGHT_BROWSERS_PATH", "0")
    119 
--> 120             self._proc = await asyncio.create_subprocess_exec(
    121                 str(self._driver_executable),
    122                 "run-driver",

~\anaconda3\lib\asyncio\subprocess.py in create_subprocess_exec(program, stdin, stdout, stderr, loop, limit, *args, **kwds)
    234     protocol_factory = lambda: SubprocessStreamProtocol(limit=limit,
    235                                                         loop=loop)
--> 236     transport, protocol = await loop.subprocess_exec(
    237         protocol_factory,
    238         program, *args,

~\anaconda3\lib\asyncio\base_events.py in subprocess_exec(self, protocol_factory, program, stdin, stdout, stderr, universal_newlines, shell, bufsize, encoding, errors, text, *args, **kwargs)
   1674             debug_log = f'execute program {program!r}'
   1675             self._log_subprocess(debug_log, stdin, stdout, stderr)
-> 1676         transport = await self._make_subprocess_transport(
   1677             protocol, popen_args, False, stdin, stdout, stderr,
   1678             bufsize, **kwargs)

~\anaconda3\lib\asyncio\base_events.py in _make_subprocess_transport(self, protocol, args, shell, stdin, stdout, stderr, bufsize, extra, **kwargs)
    496                                          extra=None, **kwargs):
    497         """Create subprocess transport."""
--> 498         raise NotImplementedError
    499 
    500     def _write_to_self(self):

NotImplementedError: 

from sklearn.metrics import precision_score
preds = model.predict(test[predictors])
preds = pd.Series(preds, index=test.index)
precision_score(test["Target"], preds)

/home/tony/anaconda3/envs/prophet/lib/python3.9/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but RandomForestClassifier was fitted with feature names
  warnings.warn(
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In [90], line 2
      1 from sklearn.metrics import precision_score
----> 2 preds = model.predict(test[predictors])
      3 preds = pd.Series(preds, index=test.index)
      4 precision_score(test["Target"], preds)

File ~/anaconda3/envs/prophet/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:832, in ForestClassifier.predict(self, X)
    811 def predict(self, X):
    812     """
    813     Predict class for X.
    814 
   (...)
    830         The predicted classes.
    831     """
--> 832     proba = self.predict_proba(X)
    834     if self.n_outputs_ == 1:
    835         return self.classes_.take(np.argmax(proba, axis=1), axis=0)

File ~/anaconda3/envs/prophet/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:874, in ForestClassifier.predict_proba(self, X)
    872 check_is_fitted(self)
    873 # Check data
--> 874 X = self._validate_X_predict(X)
    876 # Assign chunk of trees to jobs
    877 n_jobs, _, _ = _partition_estimators(self.n_estimators, self.n_jobs)

File ~/anaconda3/envs/prophet/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:605, in BaseForest._validate_X_predict(self, X)
    602 """
    603 Validate X whenever one tries to predict, apply, predict_proba."""
    604 check_is_fitted(self)
--> 605 X = self._validate_data(X, dtype=DTYPE, accept_sparse="csr", reset=False)
    606 if issparse(X) and (X.indices.dtype != np.intc or X.indptr.dtype != np.intc):
    607     raise ValueError("No support for np.int64 index based sparse matrices")

File ~/anaconda3/envs/prophet/lib/python3.9/site-packages/sklearn/base.py:577, in BaseEstimator._validate_data(self, X, y, reset, validate_separately, **check_params)
    575     raise ValueError("Validation should be done on X, y or both.")
    576 elif not no_val_X and no_val_y:
--> 577     X = check_array(X, input_name="X", **check_params)
    578     out = X
    579 elif no_val_X and not no_val_y:

File ~/anaconda3/envs/prophet/lib/python3.9/site-packages/sklearn/utils/validation.py:879, in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)
    877     # If input is 1D raise error
    878     if array.ndim == 1:
--> 879         raise ValueError(
    880             "Expected 2D array, got 1D array instead:\narray={}.\n"
    881             "Reshape your data either using array.reshape(-1, 1) if "
    882             "your data has a single feature or array.reshape(1, -1) "
    883             "if it contains a single sample.".format(array)
    884         )
    886 if dtype_numeric and array.dtype.kind in "USV":
    887     raise ValueError(
    888         "dtype='numeric' is not compatible with arrays of bytes/strings."
    889         "Convert your data to numeric values explicitly instead."
    890     )

ValueError: Expected 2D array, got 1D array instead:
array=[3.82533e+03 4.04695e+09 3.78100e+03 3.82982e+03 3.75210e+03].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

~$ cat /etc/os-release
NAME="Ubuntu"
VERSION="20.04.5 LTS (Focal Fossa)"


conda 22.9.0
ipython                   8.6.0 
ipython_genutils          0.2.0
numpy                     1.23.4
numpy-base                1.23.4
pandas                    1.5.1
python                    3.9.15
python-dateutil           2.8.2
python-fastjsonschema     2.16.2
scikit-learn              1.1.3
yfinance                  0.1.87