title: Splitting a pandas dataframe column by delimiter
body: <p>i have a small sample data:</p>
  <pre><code>import pandas as pd
  
  df = {'ID': [3009, 129, 119, 120, 121, 122, 130, 3014, 266, 849, 174, 844],
    'V': ['IGHV7-B*01', 'IGHV7-B*01', 'IGHV6-A*01', 'GHV6-A*01', 'IGHV6-A*01',
          'IGHV6-A*01', 'IGHV4-L*03', 'IGHV4-L*03', 'IGHV5-A*01', 'IGHV5-A*04',
          'IGHV6-A*02','IGHV6-A*02'],
    'Prob': [1, 1, 0.8, 0.8056, 0.9, 0.805, 1, 1, 0.997, 0.401, 1, 1]}
  
  df = pd.DataFrame(df)
  </code></pre>
  <p>looks like</p>
  <pre><code>df    
  
  Out[25]: 
        ID    Prob           V
  0    3009  1.0000  IGHV7-B*01
  1     129  1.0000  IGHV7-B*01
  2     119  0.8000  IGHV6-A*01
  3     120  0.8056  IGHV6-A*01
  4     121  0.9000  IGHV6-A*01
  5     122  0.8050  IGHV6-A*01
  6     130  1.0000  IGHV4-L*03
  7    3014  1.0000  IGHV4-L*03
  8     266  0.9970  IGHV5-A*01
  9     849  0.4010  IGHV5-A*04
  10    174  1.0000  IGHV6-A*02
  11    844  1.0000  IGHV6-A*02
  </code></pre>
  <p><strong>I want to split the column 'V' by the '-' delimiter and move it to another column named 'allele'</strong></p>
  <pre><code>    Out[25]: 
        ID    Prob      V    allele
  0    3009  1.0000  IGHV7    B*01
  1     129  1.0000  IGHV7    B*01
  2     119  0.8000  IGHV6    A*01
  3     120  0.8056  IGHV6    A*01
  4     121  0.9000  IGHV6    A*01
  5     122  0.8050  IGHV6    A*01
  6     130  1.0000  IGHV4    L*03
  7    3014  1.0000  IGHV4    L*03
  8     266  0.9970  IGHV5    A*01
  9     849  0.4010  IGHV5    A*04
  10    174  1.0000  IGHV6    A*02
  11    844  1.0000  IGHV6    A*02
  </code></pre>
  <p>the code i have tried so far is incomplete and didn't work:</p>
  <pre><code>df1 = pd.DataFrame()
  df1[['V']] = pd.DataFrame([ x.split('-') for x in df['V'].tolist() ])
  </code></pre>
  <p>or</p>
  <pre><code>df.add(Series, axis='columns', level = None, fill_value = None)
  newdata = df.DataFrame({'V':df['V'].iloc[::2].values, 
                          'Allele': df['V'].iloc[1::2].values})
  </code></pre>