code: def count_in_category(x='call_type', filter_dict=None, model=DEFAULT_MODEL, app=DEFAULT_APP, sort=True, limit=1000):
      
      sort = sort_prefix(sort)
      model = get_model(model, app)
      filter_dict = filter_dict or {}
  
      x = fuzzy.extractOne(str(x), model._meta.get_all_field_names())[0]    
  
      objects = model.objects.filter(**filter_dict)
      objects = objects.values(x)
      objects = objects.annotate(y=djmodels.Count(x))
      if sort is not None:
          objects = objects.order_by(sort + 'y')
      objects = objects.all()
      if limit:
          objects = objects[:int(limit)]
      objects = normalize_choices(util.sod_transposed(objects), field_name=x, app=app, human_readable=True)
      if not objects:
          return None
      objects = consolidated_counts(objects, field_name=x, count_name='y')
      if sort is not None:
          objects = sorted_dict_of_lists(objects, field_names=['y', x], reverse=bool(sort))
      return objects[x], objects['y']
docs: Count the number of records for each discrete (categorical) value of a field and return a dict of two lists, the field values and the counts.
  
      >>> x, y = count_in_category(x='call_type', filter_dict={'model__startswith': 'LC60'}, limit=5, sort=1)
      >>> len(x) == len(y) == 5
      True
      >>> y[1] >= y[0]
      True