title: creating Dataframe from a lot of lists
body: <p>I want to create dataframe from my data. What I do is essentially a grid search over different parameters for my algorithm. Do you have any idea how can this be done better, because right now if I need to add two more parameters in my grid, or add more data on which I perform my analysis — I need to manually add a lot of lists, then append to it some values, and then in Dataframe dict add another column. IS there another way? Because right now it looks really ugly.</p>
  <pre><code>type_preds = []
  type_models = []
  type_lens = []
  type_smalls = []
  lfc1s = []
  lfc2s = []
  lfc3s = []
  lv2s = []
  sfp1s = []
  len_small_fils = []
  ratio_small_fills = []
  ratio_big_fils = []
  for path_to_config in path_to_results.iterdir():
      try:
          type_pred, type_model, type_len, type_small, len_small_fil, ratio_big_fil, ratio_small_fill = path_to_config.name[:-4].split('__')
      except:
          print(path_to_config)
          continue
      path_to_trackings = sorted([str(el) for el in list(path_to_config.iterdir())])[::-1]
  
      sfp1, lv2, lfc3, lfc2, lfc1 = display_metrics(path_to_gts, path_to_trackings)
      type_preds.append(type_pred)
      type_models.append(type_model)
      type_lens.append(type_len)
      type_smalls.append(type_small)
      len_small_fils.append(len_small_fil)
      ratio_big_fils.append(ratio_big_fil)
      ratio_small_fills.append(ratio_small_fill)
      lfc1s.append(lfc1)
      lfc2s.append(lfc2)
      lfc3s.append(lfc3)
      lv2s.append(lv2)
      sfp1s.append(sfp1)
  
  df = pd.DataFrame({
      'type_pred': type_preds,
      'type_model': type_models,
      'type_len': type_lens,
      'type_small': type_smalls,
      'len_small_fil': len_small_fils,
      'ratio_small_fill': ratio_small_fills,
      'ratio_big_fill': ratio_big_fils,
      'lfc3': lfc3s,
      'lfc2': lfc2s,
      'lfc1': lfc1s,
      'lv2': lv2s,
      'sfp1': sfp1s
  })
  </code></pre>