title: How to transform a single column dataframe to a single row dataframe in Pandas?
body: <p>I got the following dataframe:</p>
  
  <pre><code>                        0
  0                  Aachen
  1                       1
  2                   Valid
  3                      L5
  4                      21
  5                    Fell
  6  01/01/1880 12:00:00 AM
  7                  50.775
  8                 6.08333
  9   (50.775000, 6.083330)
  </code></pre>
  
  <p>And I want it to look like:</p>
  
  <pre><code>name    id  nametype    recclass    mass (g)    fall    year    reclat  reclong GeoLocation
  Aachen  1   Valid   L5  21  Fell    1-1-1880 12:00:00 AM    50.775000   6.083330    (50.775000, 6.083330)
  </code></pre>
  
  <p>I tried using pivot() an pivot_table() in pandas, but I always get a KeyError:</p>
  
  <pre><code>pv_df = df.pivot_table(index=None, columns='0')
  
  Traceback (most recent call last):
    File "/home/alaaeddine/PycharmProjects/test/expectations.py", line 18, in &lt;module&gt;
      pv_df = df.pivot_table(index=None, columns='0')
    File "/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py", line 5303, in pivot_table
      margins_name=margins_name)
    File "/usr/local/lib/python3.6/dist-packages/pandas/core/reshape/pivot.py", line 86, in pivot_table
      grouped = data.groupby(keys, observed=False)
    File "/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py", line 6665, in groupby
      observed=observed, **kwargs)
    File "/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/groupby.py", line 2152, in groupby
      return klass(obj, by, **kwds)
    File "/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/groupby.py", line 599, in __init__
      mutated=self.mutated)
    File "/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/groupby.py", line 3291, in _get_grouper
      raise KeyError(gpr)
  KeyError: '0'
  </code></pre>
  
  <p>Also tried to set the index and stack/unstack but it does not seem to work.</p>
  
  <p>Any clues on what I am might be missing/doing worng?</p>
  
  <p>Thanks!</p>