title: merging two dataframes based on two columns of values
body: <p>I am doing a machine learning project, and I am now on the data processing part. Anyway, I have two dataframes as shown - </p>
  
  <pre><code>   Final_Lat   Final_Lot  Label
  0   37.23140    -121.75853  1.0
  1   37.34883    -121.88834  1.0
  2   37.31835    -121.85878  1.0
  3   37.26027    -121.87655  1.0
  4   37.30793    -121.79955  1.0
  5   37.24895    -121.87519  1.0
  
  
     TestLat      TestLot
  0   37.20000    -122.00000
  1   37.20000    -121.99999
  2   37.20000    -121.99998
  3   37.20000    -121.99997
  4   37.20000    -121.99996
  5   37.20000    -121.99995
  6   37.20000    -121.99994
  7   37.20000    -121.99993
  </code></pre>
  
  <p>What I want is to move labels of 1 to the coordinate that has appeared in the same list which will look something like this. and It should also contains the information from the second data frame. </p>
  
  <pre><code>Final_Lat   Final_Lot  Label
  0   37.23140    -121.75853  1.0
  1   37.34883    -121.88834  1.0
  2   37.31835    -121.85878  1.0
  3   37.20000    -122.00000  nan
  4   37.20000    -121.99999  nan
  2   37.20000    -121.99998  nan
  </code></pre>
  
  <p>I have tired </p>
  
  <pre><code>left = pd.DataFrame({'Final_Lat': Trian['Lat'].apply(float), 
                       'Final_Lot': Trian['Lot'].apply(float),
                       'Label': Trian['L'].apply(float),})
  
  right = pd.DataFrame({'Final_Lat': Fullcoordinate['TestLat'].apply(float), 
                        'Final_Lot': Fullcoordinate['TestLot'].apply(float)})
  
  Final_result = pd.merge(left, right, how='right',on=['Final_Lot','Final_Lat'])
  </code></pre>
  
  <p>And it didn't work. I would appreciate any help!</p>
  
  <pre><code>right = pd.DataFrame({'Final_Lat': Fullcoordinate['TestLat'](lambda x: pd.to_numeric(x, errors='coerce')).mul(1000).fillna(0).astype(int) , 
                        'Final_Lot': Fullcoordinate['TestLot'](lambda x: pd.to_numeric(x, errors='coerce')).mul(1000).fillna(0).astype(int) })
  </code></pre>