title: Create a pandas DataFrame from multiple dicts
body: <p>I'm new to pandas and that's my first question on stackoverflow, I'm trying to do some analytics with pandas.</p>
  
  <p>I have some text files with data records that I want to process. Each line of the file match to a record which fields are in a fixed place and have a length of a fixed number of characters. There are different kinds of records on the same file, all records share the first field that are two characters depending of the type of record. As an example:</p>
  
  <pre><code>Some file:
  01Jhon      Smith     555-1234                                        
  03Cow            Bos primigenius taurus        00401                  
  01Jannette  Jhonson           00100000000                             
  ...
  
  
  field    start  length   
  type         1       2   *common to all records, example: 01 = person, 03 = animal
  name         3      10
  surname     13      10
  phone       23       8
  credit      31      11
  fill of spaces
  </code></pre>
  
  <p>I'm writing some code to convert one record to a dictionary:</p>
  
  <pre><code>person1 = {'type': 01, 'name': = 'Jhon', 'surname': = 'Smith', 'phone': '555-1234'}
  person2 = {'type': 01, 'name': 'Jannette', 'surname': 'Jhonson', 'credit': 1000000.00}
  animal1 = {'type': 03, 'cname': 'cow', 'sciname': 'Bos....', 'legs': 4, 'tails': 1 }
  </code></pre>
  
  <p>If a field is empty (filled with spaces) there will not be in the dictionary).</p>
  
  <p>With all records of one kind I want to create a pandas DataFrame with the dicts keys as columns names, I've try with pandas.DataFrame.from_dict() without success. </p>
  
  <p>And here comes my question: Is any way to do this with pandas so dict keys become column names? Are any other standard method to deal with this kind of files?</p>