title: SAWarning when querying with SQLAlchemy into pandas df
body: <p>I'm querying my SQLAlchemy-mapped star schema directly into a <code>pandas DataFrame</code> and am getting an annoying SAWarning from <code>pandas</code> that I'd like to address.  Here's a simplified version.</p>
  
  <pre><code>class School(Base):
  __tablename__ = 'DimSchool'
  
  id = Column('SchoolKey', Integer, primary_key=True)
  name = Column('SchoolName', String)
  district = Column('SchoolDistrict', String)
  
  
  class StudentScore(Base):
  __tablename__ = 'FactStudentScore'
  
  StudentKey = Column('StudentKey', Integer,    ForeignKey('DimStudent.StudentKey'), primary_key = True)
  SchoolKey = Column('SchoolKey', Integer, ForeignKey('DimSchool.SchoolKey'), primary_key = True)
  PointsPossible = Column('PointsPossible', Integer)
  PointsReceived = Column('PointsReceived', Integer)
  
  student = relationship("Student", backref='studentscore')
  school = relationship("School", backref='studentscore')
  </code></pre>
  
  <p>I query the date with statements like this:</p>
  
  <pre><code>standard = session.query(StudentdScore, School).\
  join(School).filter(School.name.like('%Dever%'))
  
  testdf = pd.read_sql(sch.statement, sch.session.bind)   
  </code></pre>
  
  <p>And then get this warning:</p>
  
  <pre><code>SAWarning: Column 'SchoolKey' on table &lt;sqlalchemy.sql.selectable.Select at 0x1ab7abe0; Select object&gt; being replaced by Column('SchoolKey', Integer(), table=&lt;Select object&gt;, primary_key=True, nullable=False), which has the same key.  Consider use_labels for select() statements.
  </code></pre>
  
  <p>I get this error for every additional table (class) included in my join.  The message always refers to the foreign key.</p>
  
  <p>Anyone else encounter this error and determine root cause?  Or have ya'll just been ignoring it as well?</p>
  
  <p>EDIT/UPDATE:</p>
  
  <p><a href="https://stackoverflow.com/questions/22115819/handling-duplicate-columns-in-pandas-dataframe-constructor-from-sqlalchemy-join">Handling Duplicate Columns in Pandas DataFrame constructor from SQLAlchemy Join</a></p>
  
  <p>These guys seem to be talking about a related issue, but they use a different pandas method to bring the dataframe in and want to keep duplicates, not drop them.  Anyone have thoughts on how to implement a similar styled function, but drop the duplicates as the query comes back?</p>