def to_pandas(self) -> pd.DataFrame:
    "\n        Return a pandas DataFrame.\n\n        .. note:: This method should only be used if the resulting pandas DataFrame is expected\n            to be small, as all the data is loaded into the driver's memory.\n\n        Examples\n        --------\n        >>> df = ps.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)],\n        ...                   columns=['dogs', 'cats'])\n        >>> df.to_pandas()\n           dogs  cats\n        0   0.2   0.3\n        1   0.0   0.6\n        2   0.6   0.0\n        3   0.2   0.1\n        "
    log_advice("`to_pandas` loads all data into the driver's memory. It should only be used if the resulting pandas DataFrame is expected to be small.")
    return self._to_pandas()
Return a pandas DataFrame.

.. note:: This method should only be used if the resulting pandas DataFrame is expected
    to be small, as all the data is loaded into the driver's memory.

Examples
--------
>>> df = ps.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)],
...                   columns=['dogs', 'cats'])
>>> df.to_pandas()
   dogs  cats
0   0.2   0.3
1   0.0   0.6
2   0.6   0.0
3   0.2   0.1
def to_pandas(self) -> pd.DataFrame:
    "\n        Return a pandas DataFrame.\n\n        .. note:: This method should only be used if the resulting pandas DataFrame is expected\n            to be small, as all the data is loaded into the driver's memory.\n\n        Examples\n        --------\n        >>> df = ps.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)],\n        ...                   columns=['dogs', 'cats'])\n        >>> df.to_pandas()\n           dogs  cats\n        0   0.2   0.3\n        1   0.0   0.6\n        2   0.6   0.0\n        3   0.2   0.1\n        "
    log_advice("`to_pandas` loads all data into the driver's memory. It should only be used if the resulting pandas DataFrame is expected to be small.")
    return self._to_pandas()