Merge branch 'dev' into features/#377-grid-separation

.pre-commit-config.yaml

@@ -1,25 +1,25 @@
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.3.0
+  rev: v4.4.0
   hooks:
   -   id: check-yaml
   -   id: end-of-file-fixer
   -   id: trailing-whitespace
 - repo: https://github.com/psf/black
-  rev: 22.10.0
+  rev: 23.3.0
   hooks:
     - id: black
 - repo: https://github.com/pycqa/flake8
-  rev: 5.0.4
+  rev: 6.0.0
   hooks:
     - id: flake8
 - repo: https://github.com/pycqa/isort
-  rev: 5.10.1
+  rev: 5.12.0
   hooks:
     - id: isort
       name: isort (python)
 - repo: https://github.com/asottile/pyupgrade
-  rev: v3.2.0
+  rev: v3.4.0
   hooks:
     - id: pyupgrade
 #- repo: https://github.com/pycqa/pylint

doc/whatsnew/v0-3-0.rst

@@ -20,5 +20,6 @@ Changes
 * Added method to scale timeseries `#353 <https://github.com/openego/eDisGo/pull/353>`_
 * Added method to iteratively reinforce a grid in case the power flow analysis does not always converge `#353 <https://github.com/openego/eDisGo/pull/353>`_
 * Added method to aggregate LV grid buses to station bus secondary side `#353 <https://github.com/openego/eDisGo/pull/353>`_
+* Adapted codebase to work with pandas 2.0 `#373 <https://github.com/openego/eDisGo/pull/373>`_
 * Added option to run reinforcement with reduced number of time steps `#379 <https://github.com/openego/eDisGo/pull/379>`_
 * Added a new reinforcement method that separate lv grids when the overloading is very high `#380 <https://github.com/openego/eDisGo/pull/380>`_

eDisGo_env.yml

@@ -5,7 +5,7 @@ channels:
 dependencies:
   - python >= 3.8, < 3.10
   - pip
-  - pandas >= 1.2
+  - pandas >= 1.4
   - conda-forge::fiona
   - conda-forge::geopy
   - conda-forge::geopandas

eDisGo_env_dev.yml

@@ -5,7 +5,7 @@ channels:
 dependencies:
   - python >= 3.8, < 3.10
   - pip
-  - pandas >= 1.2
+  - pandas >= 1.4
   - conda-forge::fiona
   - conda-forge::geopy
   - conda-forge::geopandas

edisgo/flex_opt/check_tech_constraints.py

@@ -949,7 +949,6 @@ def allowed_voltage_limits(edisgo_obj, buses=None, split_voltage_band=True):
         buses = edisgo_obj.results.v_res.columns
 
     if split_voltage_band:
-
         # MV limits
         mv_buses = edisgo_obj.topology.mv_grid.buses_df.index
         mv_upper, mv_lower = _mv_allowed_voltage_limits(edisgo_obj)
@@ -1078,7 +1077,6 @@ def _lv_allowed_voltage_limits(edisgo_obj, lv_grids=None, mode=None):
     buses_in_pfa = voltages_pfa.columns
 
     if mode == "stations":
-
         config_string = "mv_lv_station"
 
         # get base voltage (voltage at primary side) for each station
@@ -1107,14 +1105,15 @@ def _lv_allowed_voltage_limits(edisgo_obj, lv_grids=None, mode=None):
 
         # get all secondary sides and buses in grids
         buses_dict = {}
-        secondary_sides = pd.Series()
+        secondary_sides_dict = {}
         for grid in lv_grids:
             secondary_side = grid.station.index[0]
             if secondary_side in buses_in_pfa:
-                secondary_sides[grid] = secondary_side
+                secondary_sides_dict[grid] = secondary_side
                 buses_dict[grid.station.index[0]] = grid.buses_df.index.drop(
                     grid.station.index[0]
                 )
+        secondary_sides = pd.Series(secondary_sides_dict)
 
         voltage_base = voltages_pfa.loc[:, secondary_sides.values]
 
@@ -1132,14 +1131,14 @@ def _lv_allowed_voltage_limits(edisgo_obj, lv_grids=None, mode=None):
         )
 
         # rename columns to secondary side
-        for colname, values in upper_limits_df_tmp.iteritems():
+        for colname, values in upper_limits_df_tmp.items():
             tmp = pd.DataFrame(
                 data=np.tile(values, (len(buses_dict[colname]), 1)).T,
                 columns=buses_dict[colname],
                 index=values.index,
             )
             upper_limits_df = pd.concat([upper_limits_df, tmp], axis=1)
-        for colname, values in lower_limits_df_tmp.iteritems():
+        for colname, values in lower_limits_df_tmp.items():
             tmp = pd.DataFrame(
                 data=np.tile(values, (len(buses_dict[colname]), 1)).T,
                 columns=buses_dict[colname],

edisgo/network/timeseries.py

@@ -47,7 +47,6 @@ class TimeSeries:
     """
 
     def __init__(self, **kwargs):
-
         self._timeindex = kwargs.get("timeindex", pd.DatetimeIndex([]))
         self.time_series_raw = TimeSeriesRaw()
 
@@ -657,9 +656,14 @@ def _overwrite_time_series(p, q, comp_type):
                     periods=len(worst_cases),
                     freq="H",
                 )
-                self.timeindex_worst_cases = self.timeindex_worst_cases.append(
-                    pd.Series(time_stamps, index=worst_cases)
+
+                self.timeindex_worst_cases = pd.concat(
+                    [
+                        self.timeindex_worst_cases,
+                        pd.Series(data=time_stamps, index=worst_cases),
+                    ]
                 )
+
                 self.timeindex = self.timeindex.append(time_stamps)
 
         if generators_names is None:
@@ -789,7 +793,7 @@ def _worst_case_generators(self, cases, df, configs):
         # get power scaling factors for different technologies, voltage levels and
         # feed-in/load case
         types = ["pv", "wind", "other"]
-        power_scaling = pd.DataFrame(columns=types)
+        power_scaling = pd.DataFrame(columns=types, dtype=float)
         for t in types:
             for case in cases:
                 power_scaling.at[f"{case}_mv", t] = worst_case_scale_factors[
@@ -2153,8 +2157,8 @@ def _check_if_components_exist(
                 f"concerns the following components: {comps_not_in_network}."
             )
 
-            return set(component_names) - set(comps_not_in_network)
-        return component_names
+            return list(set(component_names) - set(comps_not_in_network))
+        return list(component_names)
 
     def resample(self, method: str = "ffill", freq: str | pd.Timedelta = "15min"):
         """

edisgo/tools/geopandas_helper.py

@@ -203,6 +203,10 @@ def to_geopandas(grid_obj: Grid):
             ),
             crs=f"EPSG:{srid}",
         )
+        if components_dict[component.replace("_df", "_gdf")].empty:
+            components_dict[component.replace("_df", "_gdf")].index = components_dict[
+                component.replace("_df", "_gdf")
+            ].index.astype(object)
 
     # convert lines_df
     lines_df = grid_obj.lines_df

edisgo/tools/plots.py

@@ -32,7 +32,6 @@
     from edisgo.network.grids import Grid
 
 if "READTHEDOCS" not in os.environ:
-
     import geopandas as gpd
 
     from egoio.db_tables.grid import EgoDpMvGriddistrict
@@ -189,7 +188,6 @@ def get_grid_district_polygon(config, subst_id=None, projection=4326):
     with session_scope() as session:
         # get polygon from versioned schema
         if config["data_source"]["oedb_data_source"] == "versioned":
-
             version = config["versioned"]["version"]
             query = session.query(
                 EgoDpMvGriddistrict.subst_id, EgoDpMvGriddistrict.geom
@@ -1155,7 +1153,6 @@ def plot_line_text():
         return [middle_node_scatter]
 
     def plot_lines():
-
         showscale = True
 
         if line_color == "loading":
@@ -1181,7 +1178,6 @@ def plot_lines():
 
         data_line_plot = []
         for edge in G.edges(data=True):
-
             x0, y0, x1, y1 = get_coordinates_for_edge(edge)
             edge_x = [x0 - x_root, x1 - x_root, None]
             edge_y = [y0 - y_root, y1 - y_root, None]
@@ -1207,7 +1203,6 @@ def plot_lines():
                     .isin([branch_name])
                     .any()
                 ):
-
                     color = "red"
                 else:
                     color = "black"

edisgo/tools/spatial_complexity_reduction.py

@@ -156,7 +156,6 @@ def rename_virtual_buses(
                     partial_busmap_df.loc[nodes_to_add_a_virtual, "new_bus"]
                     != transformer_node
                 ):
-
                     partial_busmap_df.loc[nodes_to_add_a_virtual, "new_bus"] = (
                         "virtual_"
                         + partial_busmap_df.loc[feeder_non_virtual, "new_bus"]
@@ -528,14 +527,14 @@ def rename_new_buses(series):
                 ] = int(n)
 
             dijkstra_distances_df = pd.DataFrame(
-                index=buses_df.index, columns=medoid_bus_name
+                index=buses_df.index, columns=medoid_bus_name, dtype=float
             )
 
             for bus in medoid_bus_name:
                 path_series = pd.Series(
                     nx.single_source_dijkstra_path_length(graph, bus, weight="length")
                 )
-                dijkstra_distances_df.loc[:, bus] = path_series
+                dijkstra_distances_df[bus] = path_series
 
             buses_df.loc[:, "medoid"] = dijkstra_distances_df.idxmin(axis=1)
             partial_busmap_df = pd.DataFrame(index=buses_df.index)
@@ -813,9 +812,9 @@ def transform_coordinates_back(ser):
                         )
                         dijkstra_distances_df.loc[:, bus] = path_series
 
-                    feeder_buses_df.loc[:, "medoid"] = dijkstra_distances_df.idxmin(
-                        axis=1
-                    )
+                    feeder_buses_df.loc[:, "medoid"] = dijkstra_distances_df.apply(
+                        pd.to_numeric
+                    ).idxmin(axis=1)
 
                     for index in feeder_buses_df.index.tolist():
                         partial_busmap_df.loc[index, "new_bus"] = make_name(

examples/edisgo_simple_example.ipynb

@@ -892,7 +892,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.5"
   },
   "toc": {
    "base_numbering": 1,

examples/electromobility_example.ipynb

@@ -605,9 +605,9 @@
     "charging_parks_with_charging_demand = (\n",
     "    edisgo.electromobility.charging_processes_df.charging_park_id.unique()\n",
     ")\n",
-    "charging_parks_not_integrated = set(charging_parks_with_charging_demand) - set(\n",
+    "charging_parks_not_integrated = list(set(charging_parks_with_charging_demand) - set(\n",
     "    edisgo.electromobility.integrated_charging_parks_df.index\n",
-    ")\n",
+    "))\n",
     "\n",
     "edisgo.electromobility.potential_charging_parks_gdf.loc[\n",
     "    charging_parks_not_integrated\n",
@@ -737,7 +737,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "20d98ca8",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots(1, 1, figsize=(9, 5))\n",
@@ -774,7 +776,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.5"
   },
   "toc": {
    "base_numbering": 1,

rtd_requirements.txt

@@ -8,7 +8,7 @@ jupyter_dash
 matplotlib >= 3.3.0
 multiprocess
 networkx >= 2.5.0
-pandas >= 1.2.0, < 2.0.0
+pandas >= 1.4.0
 plotly
 pyomo >= 6.0
 pypower

setup.py

@@ -45,7 +45,7 @@ def read(fname):
     "matplotlib >= 3.3.0",
     "multiprocess",
     "networkx >= 2.5.0",
-    "pandas >= 1.2.0, < 2.0.0",
+    "pandas >= 1.4.0",
     "plotly",
     "pydot",
     "pygeos",