title: Inserting a Pandas Series into a DataFrame makes all values Nan
body: <p>As the title implies I have converted two dictionaries into series like so and I tried to insert them into the data frame df. </p>
  
  <pre><code>first_series = pd.Series(first_dict, name='State Names')
  second_series = pd.Series(second_dict, name='City Names')
  column_loc=list(df.columns.values).index("ipAddr")
  df.insert(column_loc+1, 'State Names', first_series)
  df.insert(column_loc+2, 'City Names', second_series)
  </code></pre>
  
  <p>When I run this however I get</p>
  
  <pre><code>              ipAddr State Names City Names    ...       
  respID                                         ...        
  10018         ***.**.**.**  NaN        NaN     ...        
  10025         **.**.**.**   NaN        NaN     ...       
  </code></pre>
  
  <p>the series are as follows</p>
  
  <pre><code>10018       Bedford
  10025     Vancouver
          ...    
  10267        Lompoc
  10280    Pikesville
  Name: State Names, dtype: object
  --------------------------------------------------------
  10018          Ohio
  10025    Washington
          ...    
  10267    California
  10280      Maryland
  Name: City Names, dtype: object
  </code></pre>
  
  <p>I've checked that both the dictionaries and the resulting series are populated so I don't understand why this is occurring. </p>
  
  <p>Thank you.  </p>
  
  <p>edit: A similar question got asked here but wasn't answered <a href="https://stackoverflow.com/questions/28934992/when-i-insert-pandas-series-into-dataframe-all-values-become-nan">When I insert pandas Series into dataframe, all values become NaN</a> </p>