title: rename multiple columns of pandas dataframe based on condition
body: <p>I have a df in which I need to rename 40 column names to empty string. this can be achieved by using <code>.rename()</code>, but I need to provide all the column names in dict, which needs to be renamed. I was searching for some better way to rename columns by some pattern matching. wherever it finds NULL/UNNAMED in column name, replace that with empty string.</p>
  
  <p>df1: original df (In actual df, i have around 20 columns as NULL1-NULL20 and 20 columns as UNNAMED1-UNNAMED20)</p>
  
  <pre><code>    NULL1   NULL2   C1  C2  UNNAMED1    UNNAMED2
  0   1   11  21  31  41  51
  1   2   22  22  32  42  52
  2   3   33  23  33  43  53
  3   4   44  24  34  44  54
  
  </code></pre>
  
  <p>desired output df:</p>
  
  <pre><code>            C1  C2      
  0   1   11  21  31  41  51
  1   2   22  22  32  42  52
  2   3   33  23  33  43  53
  3   4   44  24  34  44  54
  </code></pre>
  
  <p>This can be achieved by </p>
  
  <pre><code>df.rename(columns={'NULL1':'', 'NULL2':'', 'UNNAMED1':'', 'UNNAMED2':''}, inplace=True)
  </code></pre>
  
  <p>But I dont want to create the long dictionary of 40 elements</p>