docs: def read_data_by_variable(self, mask=True):
          """Reads and masks (if desired) the data and converts it in one dataframe per variable."""
          def print_elapsed_time(start, last_stopped, prefix):
              # print(f"{prefix} - Elapsed time [s] since start / last stopped: \
              #     {(int(time.time() - start_time))} / {(int(time.time() - last_stopped))}")
              return time.time()
          start_time = time.time()
          last_stopped = time.time()
          last_stopped = print_elapsed_time(start_time, last_stopped, "Starting chunk function")
  
          verbose = False
  
          self.read_data()
          last_stopped = print_elapsed_time(start_time, last_stopped, "Data read")
  
          # 2.
          sc_chunk = self.convert_data_to_dataframe()
          last_stopped = print_elapsed_time(start_time, last_stopped, "Data converted to df")
  
  
          # 3.B.
          if mask:
              # 3.A.
              ilocs_qa = np.where((self.df_layers["band"] == self.qa).values)[0]
              df_qa = self.data.iloc[:, ilocs_qa]
              df_qa.columns = self.df_layers["date"].iloc[ilocs_qa]
              df_clearsky = df_qa.isin(self.qa_valid)
              last_stopped = print_elapsed_time(start_time, last_stopped, "Clearsky df created")
  
              return_bands = self.variables
          else:
              return_bands = self.variables + [self.qa]
  
          dfs_variables = {}
          for var in return_bands:
              if verbose:
                  print("VARIABLE:", var)
              ilocs_var = np.where((self.df_layers["band"] == var).values)[0]
              df_var = self.data.iloc[:, ilocs_var]
              df_var.columns = self.df_layers["date"].iloc[ilocs_var]
              if mask:
                  df_var = df_var.where(df_clearsky, other=np.nan)
              dfs_variables[var] = df_var
          last_stopped = print_elapsed_time(start_time, last_stopped, "Clearsky df created")
          self._data = dfs_variables
          return self