docs: def to_pypsa(network, mode, timesteps):
      """
      Translate graph based grid representation to PyPSA Network
  
      For details from a user perspective see API documentation of
      :meth:`~.grid.network.EDisGo.analyze` of the API class
      :class:`~.grid.network.EDisGo`.
  
      Translating eDisGo's grid topology to PyPSA representation is structured
      into tranlating the topology and adding time series for components of the
      grid. In both cases translation of MV grid only (`mode='mv'`), LV grid only
      (`mode='lv'`), MV and LV (`mode=None`) share some code. The
      code is organized as follows
  
      * Medium-voltage only (`mode='mv'`): All medium-voltage grid components are
        exported by :func:`mv_to_pypsa` including the LV station. LV grid load
        and generation is considered using :func:`add_aggregated_lv_components`.
        Time series are collected by `_pypsa_load_timeseries` (as example
        for loads, generators and buses) specifying `mode='mv'`). Timeseries
        for aggregated load/generation at substations are determined individually.
      * Low-voltage only (`mode='lv'`): LV grid topology including the MV-LV
        transformer is exported. The slack is defind at primary side of the MV-LV
        transformer.
      * Both level MV+LV (`mode=None`): The entire grid topology is translated to
        PyPSA in order to perform a complete power flow analysis in both levels
        together. First, both grid levels are translated seperately using
        :func:`mv_to_pypsa` and :func:`lv_to_pypsa`. Those are merge by
        :func:`combine_mv_and_lv`. Time series are obtained at once for both grid
        levels.
  
      This PyPSA interface is aware of translation errors and performs so checks
      on integrity of data converted to PyPSA grid representation
  
      * Sub-graphs/ Sub-networks: It is ensured the grid has no islanded parts
      * Completeness of time series: It is ensured each component has a time
        series
      * Buses available: Each component (load, generator, line, transformer) is
        connected to a bus. The PyPSA representation is check for completeness of
        buses.
      * Duplicate labels in components DataFrames and components' time series
        DataFrames
  
      Parameters
      ----------
      network : Network
          eDisGo grid container
      mode : str
          Determines grid levels that are translated to
          `PyPSA grid representation
          <https://www.pypsa.org/doc/components.html#network>`_. Specify
  
          * None to export MV and LV grid levels. None is the default.
          * ('mv' to export MV grid level only. This includes cumulative load and
            generation from underlying LV grid aggregated at respective LV
            station. This option is implemented, though the rest of edisgo does
            not handle it yet.)
          * ('lv' to export LV grid level only. This option is not yet
             implemented)
      timesteps : :pandas:`pandas.DatetimeIndex<datetimeindex>` or :pandas:`pandas.Timestamp<timestamp>`
          Timesteps specifies which time steps to export to pypsa representation
          and use in power flow analysis.
  
      Returns
      -------
          PyPSA Network
  
      """
  
      # check if timesteps is array-like, otherwise convert to list (necessary
      # to obtain a dataframe when using .loc in time series functions)
      if not hasattr(timesteps, "__len__"):
          timesteps = [timesteps]
  
      # get topology and time series data
      if mode is None:
          mv_components = mv_to_pypsa(network)
          lv_components = lv_to_pypsa(network)
          components = combine_mv_and_lv(mv_components, lv_components)
  
          if list(components['Load'].index.values):
              timeseries_load_p_set = _pypsa_load_timeseries(
                  network, mode=mode, timesteps=timesteps)
  
          if len(list(components['Generator'].index.values)) > 1:
              timeseries_gen_p_min, timeseries_gen_p_max = \
                  _pypsa_generator_timeseries(
                      network, mode=mode, timesteps=timesteps)
              timeseries_storage_p_min, timeseries_storage_p_max = \
                  _pypsa_storage_timeseries(
                      network, mode=mode, timesteps=timesteps)
  
          if list(components['Bus'].index.values):
              timeseries_bus_v_set = _pypsa_bus_timeseries(
                  network, components['Bus'].index.tolist(), timesteps=timesteps)
      else:
          raise ValueError("Provide proper mode or leave it empty to export "
                           "entire grid topology.")
  
      # check topology
      _check_topology(components)
  
      # create power flow problem
      pypsa_network = PyPSANetwork()
      pypsa_network.edisgo_mode = mode
      pypsa_network.set_snapshots(timesteps)
  
      # import grid topology to PyPSA network
      # buses are created first to avoid warnings
      pypsa_network.import_components_from_dataframe(components['Bus'], 'Bus')
  
      for k, comps in components.items():
          if k is not 'Bus' and not comps.empty:
              pypsa_network.import_components_from_dataframe(comps, k)
  
      # import time series to PyPSA network
      if len(list(components['Generator'].index.values)) > 1:
          import_series_from_dataframe(pypsa_network, timeseries_gen_p_min,
                                       'Generator', 'p_min_pu')
          import_series_from_dataframe(pypsa_network, timeseries_gen_p_max,
                                       'Generator', 'p_max_pu')
          import_series_from_dataframe(pypsa_network, timeseries_storage_p_min,
                                       'Generator', 'p_min_pu')
          import_series_from_dataframe(pypsa_network, timeseries_storage_p_max,
                                       'Generator', 'p_max_pu')
  
      if list(components['Load'].index.values):
          import_series_from_dataframe(pypsa_network, timeseries_load_p_set,
                                       'Load', 'p_set')
  
      if list(components['Bus'].index.values):
          import_series_from_dataframe(pypsa_network, timeseries_bus_v_set,
                                       'Bus', 'v_mag_pu_set')
  
      _check_integrity_of_pypsa(pypsa_network)
  
      return pypsa_network