def convert(self, data):
    'Convert fetched data.\n\n        This method takes data fetched by :meth:`fetch` and\n        pre-process them before passing them to models.\n        The default behaviour is converting each column into an ndarray.\n        This behaviour can be overridden by :meth:`with_converter`.\n        If the dataset is constructed by :meth:`concat` or :meth:`join`,\n        the converter of the first dataset is used.\n\n        Args:\n            data (tuple or dict): Data from :meth:`fetch`.\n\n        Returns:\n            A tuple or dict.\n            Each value is an ndarray.\n        '
    if isinstance(data, tuple):
        return tuple((_as_array(d) for d in data))
    elif isinstance(data, dict):
        return {k: _as_array(v) for (k, v) in data.items()}
    else:
        return _as_array(data)
Convert fetched data.

This method takes data fetched by :meth:`fetch` and
pre-process them before passing them to models.
The default behaviour is converting each column into an ndarray.
This behaviour can be overridden by :meth:`with_converter`.
If the dataset is constructed by :meth:`concat` or :meth:`join`,
the converter of the first dataset is used.

Args:
    data (tuple or dict): Data from :meth:`fetch`.

Returns:
    A tuple or dict.
    Each value is an ndarray.
def convert(self, data):
    'Convert fetched data.\n\n        This method takes data fetched by :meth:`fetch` and\n        pre-process them before passing them to models.\n        The default behaviour is converting each column into an ndarray.\n        This behaviour can be overridden by :meth:`with_converter`.\n        If the dataset is constructed by :meth:`concat` or :meth:`join`,\n        the converter of the first dataset is used.\n\n        Args:\n            data (tuple or dict): Data from :meth:`fetch`.\n\n        Returns:\n            A tuple or dict.\n            Each value is an ndarray.\n        '
    if isinstance(data, tuple):
        return tuple((_as_array(d) for d in data))
    elif isinstance(data, dict):
        return {k: _as_array(v) for (k, v) in data.items()}
    else:
        return _as_array(data)