code: def number_of_items(pronac, dt):
      
      df = data.items_by_project
      project = df.loc[df['PRONAC'] == pronac]
      seg = project.iloc[0]["idSegmento"]
      info = data.items_by_project_agg.to_dict(orient="index")[seg]
      mean, std = info.values()
      threshold = mean + 1.5 * std
      project_items_count = project.shape[0]
      is_outlier = project_items_count > threshold
      return {
         'is_outlier': is_outlier,
         'valor': project_items_count,
         'maximo_esperado': mean,
         'desvio_padrao': std,
      }
docs: This metric calculates the project number of declared number of items
      and compare it to projects in the same segment
      output:
              is_outlier: True if projects number of items is not compatible
                          to others projects in the same segment
              valor: absolute number of items
              maximo_esperado: mean number of items of segment
              desvio_padrao: standard deviation of number of items in project segment