title: Python Pandas - Creating a timeseries from a csv file
body: <p>I would like to create a timeseries 'aapl' by reading a csv file and set the first column as DatetimeIndex.</p>
  
  <p>Here some lines from the csv file:</p>
  
  <pre><code>2000-01-03, 111.937502
  2000-01-04, 102.500003
  2000-01-05, 103.999997
  2000-01-06,  94.999998
  2000-01-07,  99.500001
  </code></pre>
  
  <p>The result show be like:</p>
  
  <pre><code>In [1]: aapl.head()
  Out[1]: 
  Date
  2000-01-03    111.937502
  2000-01-04    102.500003
  2000-01-05    103.999997
  2000-01-06     94.999998
  2000-01-07     99.500001
  Name: AAPL, dtype: float64
  
  In [2]: type(aapl)
  Out[2]: pandas.core.series.Series
  
  In [3]: type(aapl.index)
  Out[3]: pandas.tseries.index.DatetimeIndex
  </code></pre>
  
  <p>I tried:</p>
  
  <pre><code>aapl = pd.read_csv('aapl.csv', header=None)
  aapl[0] = pd.to_datetime(aapl[0])
  aapl.set_index(0, inplace=True)
  aapl.index.name = 'Date'
  print(type(aapl))
  print(type(aapl.index))
  print(aapl.head())
  </code></pre>
  
  <p>But that leaves me with:</p>
  
  <pre><code>&lt;class 'pandas.core.frame.DataFrame'&gt;
  &lt;class 'pandas.core.indexes.datetimes.DatetimeIndex'&gt;
                       1
  Date                  
  2000-01-03  111.937502
  2000-01-04  102.500003
  2000-01-05  103.999997
  2000-01-06   94.999998
  2000-01-07   99.500001
  </code></pre>
  
  <p>It's still a dataframe, not a series. And column with the values still has a column name.</p>
  
  <p>All suggestions are welcome!</p>