title: Merge several dataframes together
body: <p>I have got multiple (n) dataframes with variable row lengths and 3 columns each. I just want the first column of each dataframe, so i dropped the others using df.drop.<br>
  I want to merge them into one dataframe with n columns. 
  I used pd.concat for merging.</p>
  
  <pre><code>    df1.drop(columns=['col2' ,'col3']).to_csv('df1.csv', sep=';')
  
      df2.drop(columns=['col2', 'col3']).to_csv('df2.csv', sep=';')
  
  pd.concat([pd.concat([df1.drop(columns=['col2','col3']),
                        df2.drop(columns=['col2','col3'])] ,axis=1)])\
                          .to_csv('merged.csv', sep=';')
  </code></pre>
  
  <p>It gives me following Output as csv File:</p>
  
  <pre><code>    col1 (df1)  col1 (df1)
  0   0.0 
  1   0.055   
  2   0.096   
  3   0.131   
  2074        70.997
  2075        71.002
  2076        71.065
  2077        71.101
  </code></pre>
  
  <p>So u see it just adds the columns as rows. While for example row 3 is in column 2 empty. and row 2074 in colum 1 empty.
  I thought axis = 1 would fix this but it doesnt. </p>
  
  <p>Expected Output: </p>
  
  <pre><code>col1 (df1)        col1 (df1)
  0   0.0             70.997
  1   0.055           71.002
  2   0.096           71.065
  3   0.131           71.101
  </code></pre>
  
  <p>If I try <code>axis = 1, ignoreIndex=True</code> my column names changes to 0 and 1. </p>