title: pandas rename multiple columns using regex pattern
body: <p>I have a dataframe like as shown below</p>
  <pre><code>ID,US-Test1,US-Test2,US-Test3
  1,11,12,13
  2,13,16,18
  3,15,19,21
  </code></pre>
  <p>I would like to remove the keyword <code>US - </code> from all my column names</p>
  <p>I tried the below but there should be better way to do this</p>
  <pre><code>newNames = {
      'US-Test1':'Test1',
      'US-Test2':'Test2'
  }
  df.rename(columns=newNames,inplace=True)
  </code></pre>
  <p>But my real data has 70 plus columns and this is not efficient.</p>
  <p>Any regex approach to rename columns based on regex to exclude the pattern and retain only what I want?</p>
  <p>I expect my output to be like as shown below</p>
  <pre><code>ID,Test1,Test2,Test3
  1,11,12,13
  2,13,16,18
  3,15,19,21
  </code></pre>