title: Split Pandas Column of type String using fixed width (similar to Excel text-to-columns functionality with fixed width)
body: <p>I have a dataframe of CCYPair and corresponding spot values similar to the below:</p>
  <p><strong>Current Dateframe:</strong></p>
  <pre><code>d = {'CCYPair': ['EURUSD', 'USDJPY'], 'Spot': [1.2, 109]}
  df = pd.DataFrame(data=d)
  </code></pre>
  <p>I am looking to split the CCYPair column into CCY1 and CCY2. This would be easily achieved in Excel using Text-to-columns or through Left and Right functions. However, even after searching for a while, I am finding it quite tricky to achieve the same result in a pandas dataframe.</p>
  <p>I could only find pandas.read_fwf but that is for reading from a file. I already have a dataframe and am looking to split one of the columns based on fixed width.</p>
  <p>I am sure I am missing something basic here - just can't figure out what.</p>
  <p>I have tried <code>df['CCY1'] = df['CCYPair'][0:3]</code> But that applies the [0:3] on the column and not each entry within the column. So I end up getting the first three CCYPair values and then NaNs.</p>
  <p><strong>Expected outcome:</strong></p>
  <pre><code>d = {'CCY1': ['EUR', 'USD'], 'CCY2': ['USD', 'JPY'], 'Spot': [1.2, 109]}
  df = pd.DataFrame(data=d)
  </code></pre>