def _sqlalchemy_type(self, col):

        dtype = self.dtype or {}
        if dtype in col.name:
            return self.dtype[col.name]

        col_type = self._get_notnull_col_dtype(col)

        from sqlalchemy.types import (BigInteger, Integer, Float,
                                      Text, Boolean,
                                      DateTime, Date, Time)

        if col_type == 'datetime64' or col_type == 'datetime':
            try:
                tz = col.tzinfo  # noqa
                return DateTime(timezone=True)
            except:
                return DateTime
        if col_type == 'timedelta64':
            warnings.warn("the 'timedelta' type is not supported, and will be "
                          "written as integer values (ns frequency) to the "
                          "database.", UserWarning, stacklevel=8)
            return BigInteger
        elif col_type == 'floating':
            if col.dtype == 'float32':
                return Float(precision=23)
            else:
                return Float(precision=53)
        elif col_type == 'integer':
            if col.dtype == 'int32':
                return Integer
            else:
                return BigInteger
        elif col_type == 'boolean':
            return Boolean
        elif col_type == 'date':
            return Date
        elif col_type == 'time':
            return Time
        elif col_type == 'complex':
            raise ValueError('Complex datatypes not supported')

        return Text
dataset/ETHPy150Open pydata/pandas/pandas/io/sql.py/SQLTable._sqlalchemy_type/swapped operands of `in`