title: pandas dataframes merge with same column names, give priority to one
body: <p>When merging and using the following MWE:</p>
  
  <pre><code>import pandas as pd
  df1 = pd.DataFrame(data={'A': [1, 1], 'B': [2, 22]})
  df2 = pd.DataFrame(data={'A': [1, 1], 'D': [4, 44]})
  df3 = pd.DataFrame(data={'A': [1, 1], 'F': [6, 66]})
  df = pd.concat([df1, df2, df3], axis=1, join='inner')
  </code></pre>
  
  <p>Output is:</p>
  
  <pre><code>    A   B   A   D   A   F
  0   1   2   1   4   1   6
  1   1  22   1  44   1  66
  </code></pre>
  
  <p>Any idea how it could be converted with cat or merge or some other function (without having to manually "drop" the common columns before or after the merge, and merge must be still inner) into the following output (assumes "priority" is given to <code>df1['A']</code>)?</p>
  
  <pre><code>    A   B   D   F
  0   1   2   4   6
  1   1  22  44  66
  </code></pre>