title: Unpacking an OrderedDict of data frames into many data frames in python
body: <p>I want to read and prepare data from a excel spreadsheet containing many sheets with data. </p>
  
  <p>I first read the data from the excel file using <code>pd.read_excel</code> with <code>sheetname=None</code> so that all the sheets can be written into the price_data object.</p>
  
  <pre><code>price_data = pd.read_excel('price_data.xlsx', sheetname=None)
  </code></pre>
  
  <p>This gives me an OrderedDict object with 5 dataframes.
  Afterwards I need to obtain the different dataframes which compose the object <code>price_data</code>. I thought of using a for iteration for this, which gives me the opportunity to do other needed iterative operations such as setting the index of the dataframes.
  This is the approach I tried</p>
  
  <pre><code>for key, df in price_data.items(): 
      df.set_index('DeliveryStart', inplace=True)
      key = df
  </code></pre>
  
  <p>With this code I would expect that each dataframe would be written into an object named by the <code>key</code> iterator, and at the end I would have as many dataframes as those inside my original <code>data_price</code> object. However I end up with two identical dataframes, one named key and one named value.</p>
  
  <p>Suggestions?</p>