title: Drop columns by name that appear in multiple pandas dataframes
body: <p>Let's say I have multiple dataframes and each has the same column names, although the contents of those columns is not necessarily the same. </p>
  
  <p>I tried to loop over the columns of each dataframe and remove the column by name but this did not work. If I try the same method on each dataframe individually it works</p>
  
  <p>I have the following dataframes:</p>
  
  <pre><code>import pandas as pd
  df1 = pd.DataFrame({'user': ['John', 'Joe', 'Alice'], 
                     'income': [40000, 50000, 42000],
                     'Unnamed: 0': [1, 2, 3]})
  df2 = pd.DataFrame({'user': ['Luke', 'Paul', 'Jane'], 
                     'income': [40000, 50000, 42000],
                     'Unnamed: 0': [1, 2, 3]})
  
  df3 = pd.DataFrame({'user': ['Sue', 'Haley', 'Erica'], 
                     'income': [40000, 50000, 42000],
                     'Unnamed: 0': [1, 2, 3]})
  </code></pre>
  
  <p>I tried this, without success:</p>
  
  <pre><code>dataframes = [df1, df2, df3]
  for df in dataframes:
      for column in df.columns:
          if "Unnamed" in column:
              df = df.drop(column, axis = 1)
  </code></pre>
  
  <p>This did not change any of the items in <code>dataframes</code>.</p>
  
  <p>However, if I say:</p>
  
  <p><code>df3 = df3.drop("Unnamed: 0", axis = 1)</code></p>
  
  <p>It returns:</p>
  
  <pre><code>pd.DataFrame({'user': ['Sue', 'Haley', 'Erica'], 
                     'income': [40000, 50000, 42000]})
  </code></pre>
  
  <p>Note, this also works for df1 and df2, not just df3.</p>
  
  <p>Can anyone help drop the unwanted column from all of the dataframes in the list without writing one line for each?</p>