<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def drop(self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise'):
 """ Drop specified labels from rows or columns. Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names. When using a multi-index, labels on different levels can be removed by specifying the level. Parameters labels : single label or list-like Index or column labels to drop. axis : {0 or 'index', 1 or 'columns'}, default 0 Whether to drop labels from the index (0 or 'index') or columns (1 or 'columns'). index : single label or list-like Alternative to specifying axis (``labels, axis=0`` is equivalent to ``index=labels``). .. versionadded:: 0.21.0 columns : single label or list-like Alternative to specifying axis (``labels, axis=1`` is equivalent to ``columns=labels``). .. versionadded:: 0.21.0 level : int or level name, optional For MultiIndex, level from which the labels will be removed. inplace : bool, default False If True, do operation inplace and return None. errors : {'ignore', 'raise'}, default 'raise' If 'ignore', suppress error and only existing labels are dropped. Returns ------- DataFrame DataFrame without the removed index or column labels. Raises ------ KeyError If any of the labels is not found in the selected axis. See Also -------- DataFrame.loc : Label-location based indexer for selection by label. DataFrame.dropna : Return DataFrame with labels on given axis omitted where (all or any) data are missing. DataFrame.drop_duplicates : Return DataFrame with duplicate rows removed, optionally only considering certain columns. Series.drop : Return Series with specified index labels removed. Examples -------- A B C D 0 0 1 2 3 1 4 5 6 7 2 8 9 10 11 Drop columns A D 0 0 3 1 4 7 2 8 11 A D 0 0 3 1 4 7 2 8 11 Drop a row by index A B C D 2 8 9 10 11 Drop columns and/or rows of MultiIndex DataFrame big small lama speed 45.0 30.0 weight 200.0 100.0 length 1.5 1.0 cow speed 30.0 20.0 weight 250.0 150.0 length 1.5 0.8 falcon speed 320.0 250.0 weight 1.0 0.8 length 0.3 0.2 big lama speed 45.0 weight 200.0 length 1.5 falcon speed 320.0 weight 1.0 length 0.3 big small lama speed 45.0 30.0 weight 200.0 100.0 cow speed 30.0 20.0 weight 250.0 150.0 falcon speed 320.0 250.0 weight 1.0 0.8 """

        return super().drop(labels=labels, axis=axis, index=index,
                            columns=columns, level=level, inplace=inplace,
                            errors=errors)