def select(self, crit, axis=0):
    '\n        Return data corresponding to axis labels matching criteria.\n\n        .. deprecated:: 0.21.0\n            Use df.loc[df.index.map(crit)] to select via labels\n\n        Parameters\n        ----------\n        crit : function\n            To be called on each index (label). Should return True or False\n        axis : int\n\n        Returns\n        -------\n        selection : same type as caller\n        '
    warnings.warn("'select' is deprecated and will be removed in a future release. You can use .loc[labels.map(crit)] as a replacement", FutureWarning, stacklevel=2)
    axis = self._get_axis_number(axis)
    axis_name = self._get_axis_name(axis)
    axis_values = self._get_axis(axis)
    if (len(axis_values) > 0):
        new_axis = axis_values[np.asarray([bool(crit(label)) for label in axis_values])]
    else:
        new_axis = axis_values
    return self.reindex(**{axis_name: new_axis})
Return data corresponding to axis labels matching criteria.

.. deprecated:: 0.21.0
    Use df.loc[df.index.map(crit)] to select via labels

Parameters
----------
crit : function
    To be called on each index (label). Should return True or False
axis : int

Returns
-------
selection : same type as caller
def select(self, crit, axis=0):
    '\n        Return data corresponding to axis labels matching criteria.\n\n        .. deprecated:: 0.21.0\n            Use df.loc[df.index.map(crit)] to select via labels\n\n        Parameters\n        ----------\n        crit : function\n            To be called on each index (label). Should return True or False\n        axis : int\n\n        Returns\n        -------\n        selection : same type as caller\n        '
    warnings.warn("'select' is deprecated and will be removed in a future release. You can use .loc[labels.map(crit)] as a replacement", FutureWarning, stacklevel=2)
    axis = self._get_axis_number(axis)
    axis_name = self._get_axis_name(axis)
    axis_values = self._get_axis(axis)
    if (len(axis_values) > 0):
        new_axis = axis_values[np.asarray([bool(crit(label)) for label in axis_values])]
    else:
        new_axis = axis_values
    return self.reindex(**{axis_name: new_axis})