title: List vs Dictionary vs Class vs DataFrame in Python Data Formatting
body: <p>I have a Python list made up of strings that contain property addresses and multiple attributes of each property.</p>
  
  <pre><code>'Date of Sale', 'January 1, 2017', 'Phone Number', '111-344-2343', 'Color', 'Brown', 'Garage Size', '2', 'Date Listed', 'September 23, 2016', 'Loan From', 'Example Mortgage Services', 'Street Address', '751 Example Drive', 'City', 'Chicago', 'Number of Windows', 'Attorney', 'Shaping LLP', 'Township', 'Dundee', 'Zip Code', '99999', 'List Price', '$83,301.87', 'Bid Amount', '$110,199.00', 'Miscellaneous', 'Long Driveway', 'Date of Sale', ...
  </code></pre>
  
  <p>This is one "entry". The list continues in the same pattern through the rest of the properties (each starts with 'Date of Sale'), though if fields are left empty they are skipped completely. For example, if a bid was not made 'Bid Amounts' is followed directly by 'Miscellaneous', rather than the amount.</p>
  
  <p>The goal is to be able to easily parse the information. For example, I would like to list all of the properties that I have not bid on.</p>
  
  <p>The primary question is what data format to use (<code>class</code>, list, dictionary, or dataframe):</p>
  
  <pre><code>class Property(object):
      def __init__(self,dateOfSale,phoneNumber...):
          self.dateOfSale = 'dateOfSale'
          self.phoneNumber = 'phoneNumber'
          ...
  </code></pre>
  
  <p>but I'm unsure how I would utilize this to get information on multiple properties.</p>
  
  <p>OR</p>
  
  <p>Combine all information about each property into one <code>list</code> item. I'm not sure how you would look through this info though.</p>
  
  <p>OR</p>
  
  <p>Use a <code>dictionary</code> by the Address the key, and all the other information the value, though that doesn't seem easily iterated upon either.</p>
  
  <p>OR</p>
  
  <p>Utilize a Pandas <code>dataframe</code>. I will have to do more research, but it seems like "spreadsheetable" data works well in that format.</p>