H2OValueError Traceback (most recent call last)Cell In[23], line 1----> 1 df=pd.DataFrame(data)File ~\anaconda3\Lib\site-packages\pandas\core\frame.py:737, in DataFrame.__init__(self, data, index, columns, dtype, copy) 734 manager = _get_option("mode.data_manager", silent=True) 736 is_pandas_object = isinstance(data, (Series, Index, ExtensionArray))--> 737 data_dtype = getattr(data, "dtype", None) 738 original_dtype = dtype 740 # GH47215File ~\anaconda3\Lib\site-packages\h2o\frame.py:387, in H2OFrame.dtype(self) 379 """ 380 Returns the numpy.dtype of the first column of this data frame. 381 Works only for single-column data frames. (...) 384 :returns: Numpy dtype of the first column 385 """ 386 if not len(self.columns) == 1:--> 387 raise H2OValueError("dtype is only supported for one column frames") 388 if not can_use_numpy(): 389 raise ImportError("H2OFrame.dtype function requires numpy to be installed")H2OValueError: dtype is only supported for one column frames

TypeError Traceback (most recent call last)Cell In[27], line 1----> 1 aml=H2OAutoML(max_model=10,seed=1) 2 aml.train(x=x,y=y,training_frame=train)File ~\anaconda3\Lib\site-packages\h2o\automl\_estimator.py:307, in H2OAutoML.__init__(self, nfolds, balance_classes, class_sampling_factors, max_after_balance_size, max_runtime_secs, max_runtime_secs_per_model, max_models, distribution, stopping_metric, stopping_tolerance, stopping_rounds, seed, project_name, exclude_algos, include_algos, exploitation_ratio, modeling_plan, preprocessing, monotone_constraints, keep_cross_validation_predictions, keep_cross_validation_models, keep_cross_validation_fold_assignment, sort_metric, custom_metric_func, export_checkpoints_dir, verbosity, **kwargs) 305 algo_parameters = kwargs[k] or {} 306 else:--> 307 raise TypeError("H2OAutoML got an unexpected keyword argument '%s'" % k) 309 # Check if H2O jar contains AutoML 310 try:TypeError: H2OAutoML got an unexpected keyword a

C:\Users\Pooja\anaconda3\Lib\site-packages\h2o\frame.py:1981: H2ODependencyWarning: Converting H2O frame to pandas dataframe using single-thread. For faster conversion using multi-thread, install polars and pyarrow and use it as pandas_df = h2o_df.as_data_frame(use_multi_thread=True) warnings.warn("Converting H2O frame to pandas dataframe using single-thread. For faster conversion using"---------------------------------------------------------------------------AttributeError Traceback (most recent call last)~\AppData\Local\Temp\ipykernel_312\1050489596.py in ?() 1 test_df=test.as_data_frame()----> 2 preds_df=pred_df.as_data_frame()~\anaconda3\Lib\site-packages\pandas\core\generic.py in ?(self, name) 6295 and name not in self._accessors 6296 and self._info_axis._can_hold_identifiers_and_holds_name(name) 6297 ): 6298 return self[name]-> 6299 return object.__getattribute__(self, name)AttributeError: 'DataFrame' object has no attribute 'as_data_frame'

UnicodeDecodeError Traceback (most recent call last)Cell In[2], line 1----> 1 df = pd.read_csv('zomato.csv')File ~\anaconda3\Lib\site-packages\pandas\io\parsers\readers.py:912, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 899 kwds_defaults = _refine_defaults_read( 900 dialect, 901 delimiter, (...) 908 dtype_backend=dtype_backend, 909 ) 910 kwds.update(kwds_defaults)--> 912 return _read(filepath_or_buffer, kwds)File ~\anaconda3\Lib\site-packages\pandas\io\parsers\readers.py:577, in _read(filepath_or_buffer, kwds) 574 _validate_names(kwds.get("names", None)) 576 # Create the parser.--> 577 parser = TextFileReader(filepath_or_buffer, **kwds) 579 if chunksize or iterator: 580 return parserFile ~\anaconda3\Lib\site-packages\pandas\io\parsers\readers.py:1407, in TextFileReader.__init__(self, f, engine, **kwds) 1404 self.options["has_index_names"] = kwds["has_index_names"] 1406 self.handles: IOHandles | None = None-> 1407 self._engine = self._make_engine(f, self.engine)File ~\anaconda3\Lib\site-packages\pandas\io\parsers\readers.py:1679, in TextFileReader._make_engine(self, f, engine) 1676 raise ValueError(msg) 1678 try:-> 1679 return mapping[engine](f, **self.options) 1680 except Exception: 1681 if self.handles is not None:File ~\anaconda3\Lib\site-packages\pandas\io\parsers\c_parser_wrapper.py:93, in CParserWrapper.__init__(self, src, **kwds) 90 if kwds["dtype_backend"] == "pyarrow": 91 # Fail here loudly instead of in cython after reading 92 import_optional_dependency("pyarrow")---> 93 self._reader = parsers.TextReader(src, **kwds) 95 self.unnamed_cols = self._reader.unnamed_cols 97 # error: Cannot determine type of 'names'File ~\anaconda3\Lib\site-packages\pandas\_libs\parsers.pyx:550, in pandas._libs.parsers.TextReader.__cinit__()File ~\anaconda3\Lib\site-packages\pandas\_libs\parsers.pyx:639, in pandas._libs.parsers.TextReader._get_header()File ~\anaconda3\Lib\site-packages\pandas\_libs\parsers.pyx:850, in pandas._libs.parsers.TextReader._tokenize_rows()File ~\anaconda3\Lib\site-packages\pandas\_libs\parsers.pyx:861, in pandas._libs.parsers.TextReader._check_tokenize_status()File ~\anaconda3\Lib\site-packages\pandas\_libs\parsers.pyx:2021, in pandas._libs.parsers.raise_parser_error()UnicodeDecodeError: 'utf-8' codec can't decode byte 0xed in position 7044: invalid continuation byteIn [ ]:​

ValueError Traceback (most recent call last)~\AppData\Local\Temp\ipykernel_4264\3063209376.py in <module> 1 # Change the index of 'fruits' to match the index of DataFrame 'df'----> 2 fruits.index = df.index 3 print(fruits) 4 5 ~\anaconda3\lib\site-packages\pandas\core\generic.py in __setattr__(self, name, value) 5586 try: 5587 object.__getattribute__(self, name)-> 5588 return object.__setattr__(self, name, value) 5589 except AttributeError: 5590 pass~\anaconda3\lib\site-packages\pandas\_libs\properties.pyx in pandas._libs.properties.AxisProperty.__set__()~\anaconda3\lib\site-packages\pandas\core\series.py in _set_axis(self, axis, labels, fastpath) 570 if not fastpath: 571 # The ensure_index call above ensures we have an Index object--> 572 self._mgr.set_axis(axis, labels) 573 574 # ndarray compatibility~\anaconda3\lib\site-packages\pandas\core\internals\managers.py in set_axis(self, axis, new_labels) 212 def set_axis(self, axis: int, new_labels: Index) -> None: 213 # Caller is responsible for ensuring we have an Index object.--> 214 self._validate_set_axis(axis, new_labels) 215 self.axes[axis] = new_labels 216 ~\anaconda3\lib\site-packages\pandas\core\internals\base.py in _validate_set_axis(self, axis, new_labels) 67 68 elif new_len != old_len:---> 69 raise ValueError( 70 f"Length mismatch: Expected axis has {old_len} elements, new " 71 f"values have {new_len} elements"ValueError: Length mismatch: Expected axis has 3 elements, new values have 4 elements

ValueError Traceback (most recent call last)Cell In[176], line 6 4 # Standardize features 5 scaler = StandardScaler()----> 6 X_train = scaler.fit_transform(X_train) 7 X_test = scaler.transform(X_test) 9 # Train Random Forest RegressorFile ~\anaconda3\lib\site-packages\sklearn\utils\_set_output.py:313, in _wrap_method_output.<locals>.wrapped(self, X, *args, **kwargs) 311 @wraps(f) 312 def wrapped(self, X, *args, **kwargs):--> 313 data_to_wrap = f(self, X, *args, **kwargs) 314 if isinstance(data_to_wrap, tuple): 315 # only wrap the first output for cross decomposition 316 return_tuple = ( 317 _wrap_data_with_container(method, data_to_wrap[0], X, self), 318 *data_to_wrap[1:], 319 )File ~\anaconda3\lib\site-packages\sklearn\base.py:1098, in TransformerMixin.fit_transform(self, X, y, **fit_params) 1083 warnings.warn( 1084 ( 1085 f"This object ({self.__class__.__name__}) has a `transform`" (...) 1093 UserWarning, 1094 ) 1096 if y is None: 1097 # fit method of arity 1 (unsupervised transformation)-> 1098 return self.fit(X, **fit_params).transform(X) 1099 else: 1100 # fit method of arity 2 (supervised transformation) 1101 return self.fit(X, y, **fit_params).transform(X)File ~\anaconda3\lib\site-packages\sklearn\preprocessing\_data.py:878, in StandardScaler.fit(self, X, y, sample_weight) 876 # Reset internal state before fitting 877 self._reset()--> 878 return self.partial_fit(X, y, sample_weight)File ~\anaconda3\lib\site-packages\sklearn\base.py:1473, in _fit_context.<locals>.decorator.<locals>.wrapper(estimator, *args, **kwargs) 1466 estimator._validate_params() 1468 with config_context( 1469 skip_parameter_validation=( 1470 prefer_skip_nested_validation or global_skip_validation 1471 ) 1472 ):-> 1473 return fit_method(estimator, *args, **kwargs)File ~\anaconda3\lib\site-packages\sklearn\preprocessing\_data.py:914, in StandardScaler.partial_fit(self, X, y, sample_weight) 882 """Online computation of mean and std on X for later scaling. 883 884 All of X is processed as a single batch. This is intended for cases (...)