code: def vcf_to_dataframe(input,
                       fields=None,
                       exclude_fields=None,
                       types=None,
                       numbers=None,
                       alt_number=DEFAULT_ALT_NUMBER,
                       fills=None,
                       region=None,
                       tabix='tabix',
                       transformers=None,
                       buffer_size=DEFAULT_BUFFER_SIZE,
                       chunk_length=DEFAULT_CHUNK_LENGTH,
                       log=None):
      
  
      import pandas
  
      # samples requested?
      # noinspection PyTypeChecker
      _, fields = _prep_fields_param(fields)
  
      # setup
      fields, _, _, it = iter_vcf_chunks(
          input=input, fields=fields, exclude_fields=exclude_fields, types=types,
          numbers=numbers, alt_number=alt_number, buffer_size=buffer_size,
          chunk_length=chunk_length, fills=fills, region=region, tabix=tabix, samples=[],
          transformers=transformers
      )
  
      # setup progress logging
      if log is not None:
          it = _chunk_iter_progress(it, log, prefix='[vcf_to_dataframe]')
  
      # read all chunks into a list
      chunks = [d[0] for d in it]
  
      # setup output
      output = None
  
      if chunks:
  
          # concatenate chunks
          output = pandas.concat([_chunk_to_dataframe(fields, chunk)
                                  for chunk in chunks])
  
      return output
docs: Read data from a VCF file into a pandas DataFrame.
  
      Parameters
      ----------
      input : string
          {input}
      fields : list of strings, optional
          {fields}
      exclude_fields : list of strings, optional
          {exclude_fields}
      types : dict, optional
          {types}
      numbers : dict, optional
          {numbers}
      alt_number : int, optional
          {alt_number}
      fills : dict, optional
          {fills}
      region : string, optional
          {region}
      tabix : string, optional
          {tabix}
      transformers : list of transformer objects, optional
          {transformers}
      buffer_size : int, optional
          {buffer_size}
      chunk_length : int, optional
          {chunk_length}
      log : file-like, optional
          {log}
  
      Returns
      -------
      df : pandas.DataFrame