gurudesh/pytracebugs huggingface dataset:
# Buggy code
def _dt_prop_map(property_name):
    """
    Create a function that call property of property `dt` of the series.

    Parameters
    ----------
    property_name
        The property of `dt`, which will be applied.

    Returns
    -------
        A callable function to be applied in the partitions

    Notes
    -----
    This applies non-callable properties of `Series.dt`.
    """

    def dt_op_builder(df, *args, **kwargs):
        prop_val = getattr(df.squeeze().dt, property_name)
        if isinstance(prop_val, pandas.Series):
            return prop_val.to_frame()
        else:
            return pandas.DataFrame([prop_val])

    return dt_op_builder


# Traceback (Exception)
'Traceback (most recent call last):\n
File "/home/adrian.arroyo/.vscode-server/extensions/ms-python.python-2020.5.80290/pythonFiles/lib/python/debugpy/no_wheels/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_resolver.py", line 193, in _get_py_dictionary\n
attr = getattr(var, name)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/base.py", line 3381, in __getattribute__\n
method = object.__getattribute__(self, item)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/series.py", line 349, in values\n
return super(Series, self).to_numpy().flatten()\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/base.py", line 2981, in to_numpy\n
arr = self._query_compiler.to_numpy()\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 182, in to_numpy\n
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/error_message.py", line 53, in catch_bugs_and_request_email\n
" caused this error.\\n{}".format(extra_log)\n
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.\n\n'

# Fixed code
def _dt_prop_map(property_name):
    """
    Create a function that call property of property `dt` of the series.

    Parameters
    ----------
    property_name
        The property of `dt`, which will be applied.

    Returns
    -------
        A callable function to be applied in the partitions

    Notes
    -----
    This applies non-callable properties of `Series.dt`.
    """

    def dt_op_builder(df, *args, **kwargs):
        prop_val = getattr(df.squeeze().dt, property_name)
        if isinstance(prop_val, pandas.Series):
            return prop_val.to_frame()
        elif isinstance(prop_val, pandas.DataFrame):
            return prop_val
        else:
            return pandas.DataFrame([prop_val])

    return dt_op_builder
# Buggy code
def dt_op_builder(df, *args, **kwargs):
    prop_val = getattr(df.squeeze().dt, property_name)
    if isinstance(prop_val, pandas.Series):
        return prop_val.to_frame()
    else:
        return pandas.DataFrame([prop_val])


# Traceback (Exception)
'Traceback (most recent call last):\n
File "/home/adrian.arroyo/.vscode-server/extensions/ms-python.python-2020.5.80290/pythonFiles/lib/python/debugpy/no_wheels/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_resolver.py", line 193, in _get_py_dictionary\n
attr = getattr(var, name)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/base.py", line 3381, in __getattribute__\n
method = object.__getattribute__(self, item)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/series.py", line 349, in values\n
return super(Series, self).to_numpy().flatten()\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/base.py", line 2981, in to_numpy\n
arr = self._query_compiler.to_numpy()\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 182, in to_numpy\n
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/error_message.py", line 53, in catch_bugs_and_request_email\n
" caused this error.\\n{}".format(extra_log)\n
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.\n\n'

# Fixed code
def dt_op_builder(df, *args, **kwargs):
    prop_val = getattr(df.squeeze().dt, property_name)
    if isinstance(prop_val, pandas.Series):
        return prop_val.to_frame()
    elif isinstance(prop_val, pandas.DataFrame):
        return prop_val
    else:
        return pandas.DataFrame([prop_val])
# Buggy code
def to_timestamp(self, freq=None, how="start", copy=True):
    return self._default_to_pandas("to_timestamp", freq=freq, how=how, copy=copy)


# Traceback (Exception)
'Traceback (most recent call last):\n
File "/home/adrian.arroyo/.vscode-server/extensions/ms-python.python-2020.5.80290/pythonFiles/lib/python/debugpy/no_wheels/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_resolver.py", line 193, in _get_py_dictionary\n
attr = getattr(var, name)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/base.py", line 3381, in __getattribute__\n
method = object.__getattribute__(self, item)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/series.py", line 349, in values\n
return super(Series, self).to_numpy().flatten()\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/pandas/base.py", line 2981, in to_numpy\n
arr = self._query_compiler.to_numpy()\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 182, in to_numpy\n
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)\n
File "/home/adrian.arroyo/.local/lib/python3.6/site-packages/modin/error_message.py", line 53, in catch_bugs_and_request_email\n
" caused this error.\\n{}".format(extra_log)\n
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.\n\n'

# Fixed code
def to_timestamp(self, *args, **kwargs):
    return Series(query_compiler=self._query_compiler.dt_to_timestamp(*args, **kwargs))
# Buggy code
def __getitem__(self, key):
    kwargs = self._kwargs.copy()
    if self._drop:
        if not isinstance(key, list):
            key = [key]
            kwargs["squeeze"] = True
    # When `as_index` is False, pandas will always convert to a `DataFrame`, we
    # convert to a list here so that the result will be a `DataFrame`.
    elif not self._as_index and not isinstance(key, list):
        key = [key]
    if isinstance(key, list):
        return DataFrameGroupBy(
            self._df[key],
            self._by,
            self._axis,
            idx_name=self._idx_name,
            drop=self._drop,
            **kwargs,
        )
    return SeriesGroupBy(
        self._df[key],
        self._by,
        self._axis,
        idx_name=self._idx_name,
        drop=False,
        **kwargs,
    )


# Traceback (IndexError)
Traceback (most recent call last):
File "groupby_test.py", line 8, in <module>
df1 = df.groupby('max_speed')['max_speed'].count()
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 452, in count
return self._groupby_reduce(
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 519, in _groupby_reduce
query_compiler=groupby_qc.groupby_reduce(
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 1169, in groupby_reduce
first_column = qc.columns[0]
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 3929, in __getitem__
return getitem(key)
IndexError: index 0 is out of bounds for axis 0 with size 0

# Fixed code
def __getitem__(self, key):
    kwargs = self._kwargs.copy()
    # Most of time indexing DataFrameGroupBy results in another DataFrameGroupBy object unless circumstances are
    # special in which case SeriesGroupBy has to be returned. Such circumstances are when key equals to a single
    # column name and is not a list of column names or list of one column name.
    make_dataframe = True
    if self._drop:
        if not isinstance(key, list):
            key = [key]
            kwargs["squeeze"] = True
            make_dataframe = False
    # When `as_index` is False, pandas will always convert to a `DataFrame`, we
    # convert to a list here so that the result will be a `DataFrame`.
    elif not self._as_index and not isinstance(key, list):
        key = [key]
    if isinstance(key, list) and (make_dataframe or not self._as_index):
        return DataFrameGroupBy(
            self._df[key],
            self._by,
            self._axis,
            idx_name=self._idx_name,
            drop=self._drop,
            **kwargs,
        )
    return SeriesGroupBy(
        self._df[key],
        self._by,
        self._axis,
        idx_name=self._idx_name,
        drop=False,
        **kwargs,
    )
# Buggy code
def read_gbq(
    cls,
    query,
    project_id=None,
    index_col=None,
    col_order=None,
    reauth=False,
    auth_local_webserver=False,
    dialect=None,
    location=None,
    configuration=None,
    credentials=None,
    private_key=None,
    verbose=None,
):
    ErrorMessage.default_to_pandas("`read_gbq`")
    return cls.from_pandas(
        pandas.read_gbq(
            query,
            project_id=project_id,
            index_col=index_col,
            col_order=col_order,
            reauth=reauth,
            auth_local_webserver=auth_local_webserver,
            dialect=dialect,
            location=location,
            configuration=configuration,
            credentials=credentials,
            private_key=private_key,
            verbose=verbose,
        )
    )


# Traceback (TypeError)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/app/modin-project-modin-05754d9/modin/pandas/io.py", line 186, in read_gbq
return DataFrame(query_compiler=BaseFactory.read_gbq(**kwargs))
File "/app/modin-project-modin-05754d9/modin/data_management/factories.py", line 81, in read_gbq
return cls._determine_engine()._read_gbq(**kwargs)
File "/app/modin-project-modin-05754d9/modin/data_management/factories.py", line 87, in _read_gbq
return cls.io_cls.read_gbq(**kwargs)
TypeError: read_gbq() got an unexpected keyword argument 'progress_bar_type'

# Fixed code
def read_gbq(
    cls,
    query: str,
    project_id=None,
    index_col=None,
    col_order=None,
    reauth=False,
    auth_local_webserver=False,
    dialect=None,
    location=None,
    configuration=None,
    credentials=None,
    use_bqstorage_api=None,
    private_key=None,
    verbose=None,
    progress_bar_type=None,
):
    ErrorMessage.default_to_pandas("`read_gbq`")
    return cls.from_pandas(
        pandas.read_gbq(
            query,
            project_id=project_id,
            index_col=index_col,
            col_order=col_order,
            reauth=reauth,
            auth_local_webserver=auth_local_webserver,
            dialect=dialect,
            location=location,
            configuration=configuration,
            credentials=credentials,
            use_bqstorage_api=use_bqstorage_api,
            private_key=private_key,
            verbose=verbose,
            progress_bar_type=progress_bar_type,
        )
    )
# Buggy code
def transpose(self, *args, **kwargs):
    """Transposes this DataManager.

    Returns:
        Transposed new DataManager.
    """
    new_data = self.data.transpose(*args, **kwargs)
    # Switch the index and columns and transpose the
    new_manager = self.__constructor__(
        new_data, self.columns, self.index, is_transposed=self._is_transposed ^ 1
    )
    return new_manager


# Traceback (Exception)
Traceback (most recent call last):
File "modin_operations.py", line 39, in <module>
measure_operations(args.mode)
File "modin_operations.py", line 31, in measure_operations
measure_time(read_operation, pd, filename)
File "modin_operations.py", line 7, in measure_time
ret_val = func(*args)
File "modin_operations.py", line 15, in read_operation
print(df.memory_usage())
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 3263, in __str__
return repr(self)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/series.py", line 213, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 61, in _build_repr_df
head_front = head.to_pandas()
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 487, in to_pandas
len(df.index) != len(self.index) or len(df.columns) != len(self.columns)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/error_message.py", line 38, in catch_bugs_and_request_email
"Internal Error. "
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def transpose(self, *args, **kwargs):
    """Transposes this DataManager.

    Returns:
        Transposed new DataManager.
    """
    new_data = self.data.transpose(*args, **kwargs)
    # Switch the index and columns and transpose the data within the blocks.
    new_manager = self.__constructor__(
        new_data, self.columns, self.index, is_transposed=self._is_transposed ^ 1
    )
    return new_manager
# Buggy code
def memory_usage(self, **kwargs):
    """Returns the memory usage of each column.

    Returns:
        A new QueryCompiler object containing the memory usage of each column.
    """

    def memory_usage_builder(df, **kwargs):
        return df.memory_usage(**kwargs)

    func = self._build_mapreduce_func(memory_usage_builder, **kwargs)
    return self._full_axis_reduce(0, func)


# Traceback (Exception)
Traceback (most recent call last):
File "modin_operations.py", line 39, in <module>
measure_operations(args.mode)
File "modin_operations.py", line 31, in measure_operations
measure_time(read_operation, pd, filename)
File "modin_operations.py", line 7, in measure_time
ret_val = func(*args)
File "modin_operations.py", line 15, in read_operation
print(df.memory_usage())
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 3263, in __str__
return repr(self)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/series.py", line 213, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 61, in _build_repr_df
head_front = head.to_pandas()
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 487, in to_pandas
len(df.index) != len(self.index) or len(df.columns) != len(self.columns)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/error_message.py", line 38, in catch_bugs_and_request_email
"Internal Error. "
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def memory_usage(self, **kwargs):
    """Returns the memory usage of each column.

    Returns:
        A new QueryCompiler object containing the memory usage of each column.
    """

    def memory_usage_builder(df, **kwargs):
        return df.memory_usage(**kwargs)

    def sum_memory_usage(df):
        return df.sum()

    map_func = self._build_mapreduce_func(memory_usage_builder, **kwargs)
    reduce_func = self._build_mapreduce_func(sum_memory_usage)
    return self._full_reduce(0, map_func, reduce_func)
# Buggy code
def _get_partitions(self):
    if (
        not self._filtered_empties
        and self._lengths_cache is not None
        and self._widths_cache is not None
    ):
        self._partitions_cache = np.array(
            [
                row
                for row in [
                    [
                        self._partitions_cache[i][j]
                        for j in range(len(self._partitions_cache[i]))
                        if self.block_lengths[i] != 0 and self.block_widths[j] != 0
                    ]
                    for i in range(len(self._partitions_cache))
                ]
                if len(row)
            ]
        )
        self._remove_empty_blocks()
        self._filtered_empties = True
    return self._partitions_cache


# Traceback (Exception)
Traceback (most recent call last):
File "modin_operations.py", line 39, in <module>
measure_operations(args.mode)
File "modin_operations.py", line 31, in measure_operations
measure_time(read_operation, pd, filename)
File "modin_operations.py", line 7, in measure_time
ret_val = func(*args)
File "modin_operations.py", line 15, in read_operation
print(df.memory_usage())
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 3263, in __str__
return repr(self)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/series.py", line 213, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 61, in _build_repr_df
head_front = head.to_pandas()
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 487, in to_pandas
len(df.index) != len(self.index) or len(df.columns) != len(self.columns)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/error_message.py", line 38, in catch_bugs_and_request_email
"Internal Error. "
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _get_partitions(self):
    if not self._filtered_empties or (
        self._lengths_cache is not None and self._widths_cache is not None
    ):
        self._partitions_cache = np.array(
            [
                row
                for row in [
                    [
                        self._partitions_cache[i][j]
                        for j in range(len(self._partitions_cache[i]))
                        if self.block_lengths[i] != 0 and self.block_widths[j] != 0
                    ]
                    for i in range(len(self._partitions_cache))
                ]
                if len(row)
            ]
        )
        self._remove_empty_blocks()
        self._filtered_empties = True
    return self._partitions_cache
# Buggy code
def __repr__(self):
    # In the future, we can have this be configurable, just like Pandas.
    num_rows = pandas.get_option("max_rows") or 60
    num_cols = pandas.get_option("max_columns") or 20
    temp_df = self._build_repr_df(num_rows, num_cols)
    if isinstance(temp_df, pandas.DataFrame):
        temp_df = temp_df.iloc[:, 0]
    temp_str = repr(temp_df)
    if self.name is not None:
        name_str = "Name: {}, ".format(str(self.name))
    else:
        name_str = ""
    if len(self.index) > num_rows:
        len_str = "Length: {}, ".format(len(self.index))
    else:
        len_str = ""
    dtype_str = "dtype: {}".format(temp_str.rsplit("dtype: ", 1)[-1])
    if len(self) == 0:
        return "Series([], {}{}".format(name_str, dtype_str)
    return temp_str.rsplit("\nName:", 1)[0] + "\n{}{}{}".format(
        name_str, len_str, dtype_str
    )


# Traceback (Exception)
Traceback (most recent call last):
File "modin_operations.py", line 39, in <module>
measure_operations(args.mode)
File "modin_operations.py", line 31, in measure_operations
measure_time(read_operation, pd, filename)
File "modin_operations.py", line 7, in measure_time
ret_val = func(*args)
File "modin_operations.py", line 15, in read_operation
print(df.memory_usage())
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 3263, in __str__
return repr(self)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/series.py", line 213, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/pandas/base.py", line 61, in _build_repr_df
head_front = head.to_pandas()
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/backends/pandas/query_compiler.py", line 487, in to_pandas
len(df.index) != len(self.index) or len(df.columns) != len(self.columns)
File "/Users/krutivanatwala/Documents/python-experiments/venv/lib/python3.6/site-packages/modin/error_message.py", line 38, in catch_bugs_and_request_email
"Internal Error. "
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def __repr__(self):
    num_rows = pandas.get_option("max_rows") or 60
    num_cols = pandas.get_option("max_columns") or 20
    temp_df = self._build_repr_df(num_rows, num_cols)
    if isinstance(temp_df, pandas.DataFrame):
        temp_df = temp_df.iloc[:, 0]
    temp_str = repr(temp_df)
    if self.name is not None:
        name_str = "Name: {}, ".format(str(self.name))
    else:
        name_str = ""
    if len(self.index) > num_rows:
        len_str = "Length: {}, ".format(len(self.index))
    else:
        len_str = ""
    dtype_str = "dtype: {}".format(temp_str.rsplit("dtype: ", 1)[-1])
    if len(self) == 0:
        return "Series([], {}{}".format(name_str, dtype_str)
    return temp_str.rsplit("\nName:", 1)[0] + "\n{}{}{}".format(
        name_str, len_str, dtype_str
    )
# Buggy code
def helper(df, internal_indices=[]):
    return pandas_func(df, **kwargs)


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-7f2184cfd6d7> in <module>
2 df = pd.DataFrame(columns=cols)
3 for col in cols:
----> 4     df[col] = np.arange(10)

~/Documents/modin/modin/pandas/dataframe.py in __setitem__(self, key, value)
4605         else:
4606             loc = self.columns.get_loc(key)
-> 4607             self.__delitem__(key)
4608             self.insert(loc=loc, column=key, value=value)
4609

~/Documents/modin/modin/pandas/dataframe.py in __delitem__(self, key)
4690         if key not in self:
4691             raise KeyError(key)
-> 4692         self._update_inplace(new_query_compiler=self._query_compiler.delitem(key))
4693
4694     def __finalize__(self, other, method=None, **kwargs):

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in delitem(self, key)
2294     # These will change the shape of the resulting data.
2295     def delitem(self, key):
-> 2296         return self.drop(columns=[key])
2297
2298     def drop(self, index=None, columns=None):

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in drop(self, index, columns)
2336             new_columns = self.columns[~self.columns.isin(columns)]
2337             new_dtypes = self.dtypes.drop(columns)
-> 2338         return self.__constructor__(new_data, new_index, new_columns, new_dtypes)
2339
2340     # END __delitem__ and drop

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __constructor__(self, block_paritions_object, index, columns, dtypes)
41     def __constructor__(self, block_paritions_object, index, columns, dtypes=None):
42         """By default, constructor method will invoke an init"""
---> 43         return type(self)(block_paritions_object, index, columns, dtypes)
44
45     # Index, columns and dtypes objects

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes)
32         dtypes=None,
33     ):
---> 34         assert isinstance(block_partitions_object, BaseBlockPartitions)
35         self.data = block_partitions_object
36         self.index = index

AssertionError:

# Fixed code
def helper(df, internal_indices=[]):
    if len(internal_indices) > 0:
        return pandas_func(df, internal_indices=internal_indices, **kwargs)
    return pandas_func(df, **kwargs)
# Buggy code
def describe_builder(df, **kwargs):
    try:
        return pandas.DataFrame.describe(df, **kwargs)
    except ValueError:
        return pandas.DataFrame(index=df.index)


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-7f2184cfd6d7> in <module>
2 df = pd.DataFrame(columns=cols)
3 for col in cols:
----> 4     df[col] = np.arange(10)

~/Documents/modin/modin/pandas/dataframe.py in __setitem__(self, key, value)
4605         else:
4606             loc = self.columns.get_loc(key)
-> 4607             self.__delitem__(key)
4608             self.insert(loc=loc, column=key, value=value)
4609

~/Documents/modin/modin/pandas/dataframe.py in __delitem__(self, key)
4690         if key not in self:
4691             raise KeyError(key)
-> 4692         self._update_inplace(new_query_compiler=self._query_compiler.delitem(key))
4693
4694     def __finalize__(self, other, method=None, **kwargs):

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in delitem(self, key)
2294     # These will change the shape of the resulting data.
2295     def delitem(self, key):
-> 2296         return self.drop(columns=[key])
2297
2298     def drop(self, index=None, columns=None):

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in drop(self, index, columns)
2336             new_columns = self.columns[~self.columns.isin(columns)]
2337             new_dtypes = self.dtypes.drop(columns)
-> 2338         return self.__constructor__(new_data, new_index, new_columns, new_dtypes)
2339
2340     # END __delitem__ and drop

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __constructor__(self, block_paritions_object, index, columns, dtypes)
41     def __constructor__(self, block_paritions_object, index, columns, dtypes=None):
42         """By default, constructor method will invoke an init"""
---> 43         return type(self)(block_paritions_object, index, columns, dtypes)
44
45     # Index, columns and dtypes objects

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes)
32         dtypes=None,
33     ):
---> 34         assert isinstance(block_partitions_object, BaseBlockPartitions)
35         self.data = block_partitions_object
36         self.index = index

AssertionError:

# Fixed code
def describe_builder(df, internal_indices=[], **kwargs):
    return df.iloc[:, internal_indices].describe(**kwargs)
# Buggy code
def __constructor__(self):
    return type(self)


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-69e2ecd84881> in <module>
----> 1 modin_df.loc[:,['col1', 'col3', 'col3']].head()

~/Documents/modin/modin/pandas/dataframe.py in head(self, n)
1793         if n >= len(self.index):
1794             return self.copy()
-> 1795         return DataFrame(query_compiler=self._query_compiler.head(n))
1796
1797     def hist(

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in head(self, n)
2132         else:
2133             result = self.__constructor__(
-> 2134                 self.data.take(0, n), self.index[:n], self.columns, self._dtype_cache
2135             )
2136         return result

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes, index_map_series, columns_map_series)
2816                 numeric index.
2817         """
-> 2818         assert index_map_series is not None
2819         assert columns_map_series is not None
2820         assert index.equals(index_map_series.index)

AssertionError:

# Fixed code
def __constructor__(self):
    raise NotImplementedError("Must be implemented in children classes")
# Buggy code
def _set_dtype(self, dtypes):
    self._dtype_cache = dtypes


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-69e2ecd84881> in <module>
----> 1 modin_df.loc[:,['col1', 'col3', 'col3']].head()

~/Documents/modin/modin/pandas/dataframe.py in head(self, n)
1793         if n >= len(self.index):
1794             return self.copy()
-> 1795         return DataFrame(query_compiler=self._query_compiler.head(n))
1796
1797     def hist(

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in head(self, n)
2132         else:
2133             result = self.__constructor__(
-> 2134                 self.data.take(0, n), self.index[:n], self.columns, self._dtype_cache
2135             )
2136         return result

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes, index_map_series, columns_map_series)
2816                 numeric index.
2817         """
-> 2818         assert index_map_series is not None
2819         assert columns_map_series is not None
2820         assert index.equals(index_map_series.index)

AssertionError:

# Fixed code
def _set_dtype(self, dtypes):
    raise NotImplementedError("Must be implemented in children classes")
# Buggy code
def _set_data(self, new_data):
    """Note this setter will be called by the
    `super(PandasDataManagerView).__init__` function
    """
    self.parent_data = new_data


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-69e2ecd84881> in <module>
----> 1 modin_df.loc[:,['col1', 'col3', 'col3']].head()

~/Documents/modin/modin/pandas/dataframe.py in head(self, n)
1793         if n >= len(self.index):
1794             return self.copy()
-> 1795         return DataFrame(query_compiler=self._query_compiler.head(n))
1796
1797     def hist(

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in head(self, n)
2132         else:
2133             result = self.__constructor__(
-> 2134                 self.data.take(0, n), self.index[:n], self.columns, self._dtype_cache
2135             )
2136         return result

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes, index_map_series, columns_map_series)
2816                 numeric index.
2817         """
-> 2818         assert index_map_series is not None
2819         assert columns_map_series is not None
2820         assert index.equals(index_map_series.index)

AssertionError:

# Fixed code
def _set_data(self, new_data):
    """Note this setter will be called by the
    `super(BaseQueryCompiler).__init__` function
    """
    raise NotImplementedError("Must be implemented in children classes")
# Buggy code
def _get_dtype(self):
    if self._dtype_cache is None:
        map_func = self._prepare_method(lambda df: df.dtypes)

        def dtype_builder(df):
            return df.apply(lambda row: find_common_type(row.values), axis=0)

        self._dtype_cache = self._full_reduce(0, map_func, dtype_builder)
        self._dtype_cache.index = self.columns
    elif not self._dtype_cache.index.equals(self.columns):
        self._dtype_cache.index = self.columns
    return self._dtype_cache


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-69e2ecd84881> in <module>
----> 1 modin_df.loc[:,['col1', 'col3', 'col3']].head()

~/Documents/modin/modin/pandas/dataframe.py in head(self, n)
1793         if n >= len(self.index):
1794             return self.copy()
-> 1795         return DataFrame(query_compiler=self._query_compiler.head(n))
1796
1797     def hist(

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in head(self, n)
2132         else:
2133             result = self.__constructor__(
-> 2134                 self.data.take(0, n), self.index[:n], self.columns, self._dtype_cache
2135             )
2136         return result

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes, index_map_series, columns_map_series)
2816                 numeric index.
2817         """
-> 2818         assert index_map_series is not None
2819         assert columns_map_series is not None
2820         assert index.equals(index_map_series.index)

AssertionError:

# Fixed code
def _get_dtype(self):
    calculate_dtype = False
    if self._dtype_cache is None:
        calculate_dtype = True
    else:
        if len(self.columns) != len(self._dtype_cache):
            if all(col in self._dtype_cache.index for col in self.columns):
                self._dtype_cache = pandas.Series(
                    {col: self._dtype_cache[col] for col in self.columns}
                )
            else:
                calculate_dtype = True
        elif not self._dtype_cache.equals(self.columns):
            self._dtype_cache.index = self.columns
    if calculate_dtype:
        map_func = self._prepare_method(lambda df: df.dtypes)

        def dtype_builder(df):
            return df.apply(lambda row: find_common_type(row.values), axis=0)

        self._dtype_cache = self._full_reduce(0, map_func, dtype_builder)
        self._dtype_cache.index = self.columns
    return self._dtype_cache
# Buggy code
def to_pandas(self):
    """Converts Modin DataFrame to Pandas DataFrame.

    Returns:
        Pandas DataFrame of the DataManager.
    """
    df = self.data.to_pandas(is_transposed=self._is_transposed)
    if df.empty:
        dtype_dict = {
            col_name: pandas.Series(dtype=self.dtypes[col_name])
            for col_name in self.columns
        }
        df = pandas.DataFrame(dtype_dict, self.index)
    else:
        ErrorMessage.catch_bugs_and_request_email(
            len(df.index) != len(self.index) or len(df.columns) != len(self.columns)
        )
        df.index = self.index
        df.columns = self.columns
    return df


# Traceback (AssertionError)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-69e2ecd84881> in <module>
----> 1 modin_df.loc[:,['col1', 'col3', 'col3']].head()

~/Documents/modin/modin/pandas/dataframe.py in head(self, n)
1793         if n >= len(self.index):
1794             return self.copy()
-> 1795         return DataFrame(query_compiler=self._query_compiler.head(n))
1796
1797     def hist(

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in head(self, n)
2132         else:
2133             result = self.__constructor__(
-> 2134                 self.data.take(0, n), self.index[:n], self.columns, self._dtype_cache
2135             )
2136         return result

~/Documents/modin/modin/data_management/query_compiler/pandas_query_compiler.py in __init__(self, block_partitions_object, index, columns, dtypes, index_map_series, columns_map_series)
2816                 numeric index.
2817         """
-> 2818         assert index_map_series is not None
2819         assert columns_map_series is not None
2820         assert index.equals(index_map_series.index)

AssertionError:

# Fixed code
def to_pandas(self):
    """Converts Modin DataFrame to Pandas DataFrame.

    Returns:
        Pandas DataFrame of the DataManager.
    """
    df = self.data.to_pandas(is_transposed=self._is_transposed)
    if df.empty:
        if len(self.columns) != 0:
            data = [
                pandas.Series(dtype=self.dtypes[col_name], name=col_name)
                for col_name in self.columns
            ]
            df = pandas.concat(data, axis=1)
        else:
            df = pandas.DataFrame(index=self.index)
    else:
        ErrorMessage.catch_bugs_and_request_email(
            len(df.index) != len(self.index) or len(df.columns) != len(self.columns)
        )
        df.index = self.index
        df.columns = self.columns
    return df
# Buggy code
def drop_duplicates(self, subset=None, keep="first", inplace=False):
    """Return DataFrame with duplicate rows removed, optionally only considering certain columns

    Args:
        subset : column label or sequence of labels, optional
            Only consider certain columns for identifying duplicates, by
            default use all of the columns
        keep : {'first', 'last', False}, default 'first'
            - ``first`` : Drop duplicates except for the first occurrence.
            - ``last`` : Drop duplicates except for the last occurrence.
            - False : Drop all duplicates.
        inplace : boolean, default False
            Whether to drop duplicates in place or to return a copy

    Returns:
        deduplicated : DataFrame
    """
    inplace = validate_bool_kwarg(inplace, "inplace")
    duplicates = self.duplicated(subset=subset, keep=keep)
    (indices,) = duplicates.nonzero()
    return self.drop(indices, inplace=inplace)


# Traceback (ValueError)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-59-b4c2776eba26> in <module>()
1 broken = pd.read_json('/Users/beckermi/Documents/modin_broken.json', orient='split')
----> 2 broken[['time', 'id']].sort_values(['id', 'time']).drop_duplicates(['id'])

~/anaconda3/envs/hsm/lib/python3.6/site-packages/modin/pandas/dataframe.py in drop_duplicates(self, subset, keep, inplace)
1279         duplicates = self.duplicated(subset=subset, keep=keep)
1280         indices, = duplicates.nonzero()
-> 1281         return self.drop(indices, inplace=inplace)
1282
1283     def duplicated(self, subset=None, keep="first"):

~/anaconda3/envs/hsm/lib/python3.6/site-packages/modin/pandas/dataframe.py in drop(self, labels, axis, index, columns, level, inplace, errors)
1225                 if len(non_existant):
1226                     raise ValueError(
-> 1227                         "labels {} not contained in axis".format(non_existant)
1228                     )
1229             else:

ValueError: labels [2] not contained in axis

# Fixed code
def drop_duplicates(self, subset=None, keep="first", inplace=False):
    """Return DataFrame with duplicate rows removed, optionally only considering certain columns

    Args:
        subset : column label or sequence of labels, optional
            Only consider certain columns for identifying duplicates, by
            default use all of the columns
        keep : {'first', 'last', False}, default 'first'
            - ``first`` : Drop duplicates except for the first occurrence.
            - ``last`` : Drop duplicates except for the last occurrence.
            - False : Drop all duplicates.
        inplace : boolean, default False
            Whether to drop duplicates in place or to return a copy

    Returns:
        deduplicated : DataFrame
    """
    inplace = validate_bool_kwarg(inplace, "inplace")
    duplicates = self.duplicated(subset=subset, keep=keep)
    (indices,) = duplicates.values.nonzero()
    return self.drop(index=self.index[indices], inplace=inplace)
# Buggy code
def cummax(self, axis=None, skipna=True, *args, **kwargs):
    """Perform a cumulative maximum across the DataFrame.

    Args:
        axis (int): The axis to take maximum on.
        skipna (bool): True to skip NA values, false otherwise.

    Returns:
        The cumulative maximum of the DataFrame.
    """
    axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
    return DataFrame(
        data_manager=self._data_manager.cummax(axis=axis, skipna=skipna, **kwargs)
    )


# Traceback (TypeError)
RayGetError: Could not get objectid ObjectID(01000000f0cc325805f5c83895ed0532827d52de). It was created by remote function modin.data_management.partitioning.axis_partition.deploy_ray_axis_func which failed with:

Remote function modin.data_management.partitioning.axis_partition.deploy_ray_axis_func failed with:

Traceback (most recent call last):
File "/Users/William/Documents/modin/modin/data_management/partitioning/axis_partition.py", line 188, in deploy_ray_axis_func
result = func(dataframe, **kwargs)
File "/Users/William/Documents/modin/modin/data_management/data_manager.py", line 158, in helper
def helper(df, internal_indices=[]):
File "/Users/William/Documents/modin/venv/lib/python3.6/site-packages/pandas/core/generic.py", line 9661, in cum_func
result = accum_func(y, axis)
File "/Users/William/Documents/modin/venv/lib/python3.6/site-packages/pandas/core/generic.py", line 8829, in <lambda>
lambda y, axis: np.maximum.accumulate(y, axis), "max",
File "pandas/_libs/tslibs/timestamps.pyx", line 170, in pandas._libs.tslibs.timestamps._Timestamp.__richcmp__
TypeError: Cannot compare type 'Timestamp' with type 'float'

# Fixed code
def cummax(self, axis=None, skipna=True, *args, **kwargs):
    """Perform a cumulative maximum across the DataFrame.

    Args:
        axis (int): The axis to take maximum on.
        skipna (bool): True to skip NA values, false otherwise.

    Returns:
        The cumulative maximum of the DataFrame.
    """
    axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
    if axis:
        self._validate_dtypes()
    return DataFrame(
        data_manager=self._data_manager.cummax(axis=axis, skipna=skipna, **kwargs)
    )
# Buggy code
def cummin(self, axis=None, skipna=True, *args, **kwargs):
    """Perform a cumulative minimum across the DataFrame.

    Args:
        axis (int): The axis to cummin on.
        skipna (bool): True to skip NA values, false otherwise.

    Returns:
        The cumulative minimum of the DataFrame.
    """
    axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
    return DataFrame(
        data_manager=self._data_manager.cummin(axis=axis, skipna=skipna, **kwargs)
    )


# Traceback (TypeError)
RayGetError: Could not get objectid ObjectID(01000000f0cc325805f5c83895ed0532827d52de). It was created by remote function modin.data_management.partitioning.axis_partition.deploy_ray_axis_func which failed with:

Remote function modin.data_management.partitioning.axis_partition.deploy_ray_axis_func failed with:

Traceback (most recent call last):
File "/Users/William/Documents/modin/modin/data_management/partitioning/axis_partition.py", line 188, in deploy_ray_axis_func
result = func(dataframe, **kwargs)
File "/Users/William/Documents/modin/modin/data_management/data_manager.py", line 158, in helper
def helper(df, internal_indices=[]):
File "/Users/William/Documents/modin/venv/lib/python3.6/site-packages/pandas/core/generic.py", line 9661, in cum_func
result = accum_func(y, axis)
File "/Users/William/Documents/modin/venv/lib/python3.6/site-packages/pandas/core/generic.py", line 8829, in <lambda>
lambda y, axis: np.maximum.accumulate(y, axis), "max",
File "pandas/_libs/tslibs/timestamps.pyx", line 170, in pandas._libs.tslibs.timestamps._Timestamp.__richcmp__
TypeError: Cannot compare type 'Timestamp' with type 'float'

# Fixed code
def cummin(self, axis=None, skipna=True, *args, **kwargs):
    """Perform a cumulative minimum across the DataFrame.

    Args:
        axis (int): The axis to cummin on.
        skipna (bool): True to skip NA values, false otherwise.

    Returns:
        The cumulative minimum of the DataFrame.
    """
    axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
    if axis:
        self._validate_dtypes()
    return DataFrame(
        data_manager=self._data_manager.cummin(axis=axis, skipna=skipna, **kwargs)
    )
# Buggy code
def cumprod(self, axis=None, skipna=True, *args, **kwargs):
    """Perform a cumulative product across the DataFrame.

    Args:
        axis (int): The axis to take product on.
        skipna (bool): True to skip NA values, false otherwise.

    Returns:
        The cumulative product of the DataFrame.
    """
    axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
    return DataFrame(
        data_manager=self._data_manager.cumprod(axis=axis, skipna=skipna, **kwargs)
    )


# Traceback (TypeError)
RayGetError: Could not get objectid ObjectID(01000000f0cc325805f5c83895ed0532827d52de). It was created by remote function modin.data_management.partitioning.axis_partition.deploy_ray_axis_func which failed with:

Remote function modin.data_management.partitioning.axis_partition.deploy_ray_axis_func failed with:

Traceback (most recent call last):
File "/Users/William/Documents/modin/modin/data_management/partitioning/axis_partition.py", line 188, in deploy_ray_axis_func
result = func(dataframe, **kwargs)
File "/Users/William/Documents/modin/modin/data_management/data_manager.py", line 158, in helper
def helper(df, internal_indices=[]):
File "/Users/William/Documents/modin/venv/lib/python3.6/site-packages/pandas/core/generic.py", line 9661, in cum_func
result = accum_func(y, axis)
File "/Users/William/Documents/modin/venv/lib/python3.6/site-packages/pandas/core/generic.py", line 8829, in <lambda>
lambda y, axis: np.maximum.accumulate(y, axis), "max",
File "pandas/_libs/tslibs/timestamps.pyx", line 170, in pandas._libs.tslibs.timestamps._Timestamp.__richcmp__
TypeError: Cannot compare type 'Timestamp' with type 'float'

# Fixed code
def cumprod(self, axis=None, skipna=True, *args, **kwargs):
    """Perform a cumulative product across the DataFrame.

    Args:
        axis (int): The axis to take product on.
        skipna (bool): True to skip NA values, false otherwise.

    Returns:
        The cumulative product of the DataFrame.
    """
    axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
    self._validate_dtypes(numeric_only=True)
    return DataFrame(
        data_manager=self._data_manager.cumprod(axis=axis, skipna=skipna, **kwargs)
    )