add add column to df

Author: heckstrahler

pandapower/build_branch.py

@@ -1603,7 +1603,7 @@ def _calculate_3w_tap_changers(t3, t2, sides):
     at_star_point = t3.tap_at_star_point.values
     any_at_star_point = at_star_point.any()
     for side in sides:
-        if 'tap_side' not in t3:
+        if 'tap_side' not in t3: # TODO: add column wont work here
             t3['tap_side'] = pd.NA
         tap_mask = (t3.tap_side.fillna("") == side).to_numpy()
         for var in tap_variables:

pandapower/build_gen.py

@@ -7,6 +7,7 @@
 import numpy as np
 import pandas as pd
 
+from pandapower.create._utils import add_column_to_df
 from pandapower.pf.ppci_variables import bustypes
 from pandapower.pypower.bustypes import bustypes_dc
 from pandapower.pypower.idx_bus import PV, REF, VA, VM, BUS_TYPE, NONE, VMAX, VMIN, SL_FAC as SL_FAC_BUS
@@ -530,8 +531,7 @@ def _calculate_qmin_qmax_from_q_capability_characteristics(net, element):
         return None
 
     # Filter rows with True 'reactive_capability_curve'
-    if 'reactive_capability_curve' not in net[element]:
-        net[element]['reactive_capability_curve'] = pd.NA
+    add_column_to_df(net, element, 'reactive_capability_curve')
     element_data = net[element].loc[net[element]['reactive_capability_curve'].fillna(False)]
 
     if element_data.empty:

pandapower/contingency/contingency.py

@@ -8,7 +8,7 @@
 import pandas as pd
 import warnings
 from packaging.version import Version
-
+from pandapower.create._utils import add_column_to_df
 import logging
 
 logger = logging.getLogger(__name__)
@@ -164,11 +164,8 @@ def run_contingency_ls2g(net, nminus1_cases, contingency_evaluation_function=run
     if not lightsim2grid_installed:
         raise UserWarning("lightsim2grid package not installed. "
                           "Install lightsim2grid e.g. by running 'pip install lightsim2grid' in command prompt.")
-    if "min_q_mvar" not in net["gen"].columns:
-        net["gen"]["min_q_mvar"] = float("nan")
-    if "max_q_mvar" not in net["gen"].columns:
-        net["gen"]["max_q_mvar"] = float("nan")
-
+    add_column_to_df(net, "gen", "min_q_mvar")
+    add_column_to_df(net, "gen", 'max_q_mvar')
     # check for continuous bus index starting with 0:
     n_bus = len(net.bus)
     last_bus = net.bus.index[-1]

pandapower/plotting/geo.py

@@ -281,7 +281,7 @@ def update_props(r: pd.Series) -> None:
         if element:
             props: dict = {}
             for table in [name, f"res_{name}"]:
-                if table not in net.keys():
+                if table not in net:
                     continue
 
                 tempdf = net[table].copy(deep=True)

pandapower/protection/utility_functions.py

@@ -4,7 +4,6 @@
 from typing import List, Tuple
 
 from matplotlib.collections import PatchCollection
-from typing_extensions import deprecated
 
 import geojson
 import math
@@ -17,6 +16,7 @@
 
 from pandapower.auxiliary import pandapowerNet
 from pandapower.topology.create_graph import create_nxgraph
+from pandapower.create._utils import add_column_to_df
 from pandapower.create import create_bus, create_line_from_parameters
 from pandapower.plotting.collections import create_annotation_collection, create_line_collection, \
     create_bus_collection, create_line_switch_collection, draw_collections, create_trafo_collection, \
@@ -88,12 +88,15 @@ def create_sc_bus(net_copy, sc_line_id, sc_fraction):
     # sim bench grids
     if 's_sc_max_mva' not in net.ext_grid:
         print('input s_sc_max_mva or taking 1000')
+        add_column_to_df(net, "ext_grid", "s_sc_max_mva")
         net.ext_grid['s_sc_max_mva'] = 1000
     if 'rx_max' not in net.ext_grid:
         print('input rx_max or taking 0.1')
+        add_column_to_df(net, "ext_grid", "rx_max")
         net.ext_grid['rx_max'] = 0.1
     if 'k' not in net.sgen and len(net.sgen) != 0:
         print('input  Ratio of nominal current to short circuit current- k or  taking k=1')
+        add_column_to_df(net, "sgen", "k")
         net.sgen['k'] = 1
 
     # set new lines

pandapower/test/control/test_stactrl.py

@@ -8,6 +8,7 @@
 import logging
 
 from pandapower.control.controller.station_control import BinarySearchControl, DroopControl
+from pandapower.create._utils import add_column_to_df
 from pandapower.create import create_empty_network, create_bus, create_buses, create_ext_grid, create_transformer, \
     create_load, create_line, create_sgen, create_impedance
 from pandapower.run import runpp
@@ -186,8 +187,7 @@ def test_qlimits_with_capability_curve():
                 'p_mw': [-2.0, -1.0, 0.0, 1.0, 2.0],
                 'q_min_mvar': [-0.1, -0.1, -0.1, -0.1, -0.1],
                 'q_max_mvar': [0.1, 0.1, 0.1, 0.1, 0.1]})
-            if 'id_q_capability_characteristic' not in net.sgen:
-                net.sgen['id_q_capability_characteristic'] = pd.NA
+            add_column_to_df(net, "sgen", "id_q_capability_characteristic")
             net.sgen.at[0, "id_q_capability_characteristic"] = 0
             net.sgen['curve_style'] = "straightLineYValues"
             create_q_capability_characteristics_object(net)

pandapower/test/control/test_tap_dependent_impedance.py

@@ -6,6 +6,7 @@
 import pytest
 import numpy as np
 
+from pandapower.create._utils import add_column_to_df
 from pandapower.control import Characteristic, SplineCharacteristic, TapDependentImpedance, \
     trafo_characteristic_table_diagnostic
 from pandapower.control.util.diagnostic import shunt_characteristic_table_diagnostic
@@ -136,10 +137,8 @@ def test_trafo_characteristic_table_diagnostic():
          'vkr_percent': [1.3, 1.4, 1.44, 1.5, 1.6], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan,
          'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan})
     # populate id_characteristic_table parameter
-    if 'id_characteristic_table' not in net.trafo:
-        net.trafo.at[0, 'id_characteristic_table'] = pd.NA
-    if 'tap_dependency_table' not in net.trafo:
-        net.trafo.at[0, 'tap_dependency_table'] = pd.NA
+    add_column_to_df(net, "trafo", "id_characteristic_table")
+    add_column_to_df(net, "trafo", 'tap_dependency_table')
     net.trafo['id_characteristic_table'].at[0] = 0
     net.trafo['tap_dependency_table'].at[0] = False
     with pytest.warns(UserWarning):

pandapower/test/grid_equivalents/test_get_equivalent.py

@@ -8,6 +8,7 @@
 from pandapower import pp_dir
 from pandapower.control import ConstControl
 from pandapower.control.util.auxiliary import create_trafo_characteristic_object
+from pandapower.create._utils import add_column_to_df
 from pandapower.create import create_empty_network, create_buses, create_ext_grid, create_poly_cost, create_line, \
     create_load, create_sgen, create_pwl_cost, create_bus, create_switch, create_motor
 from pandapower.grid_equivalents.auxiliary import replace_motor_by_load, _runpp_except_voltage_angles
@@ -483,9 +484,9 @@ def test_characteristic():
          'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [2, 3, 4, 5, 6],
          'vkr_percent': [1.323, 1.324, 1.325, 1.326, 1.327], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan,
          'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan})
-    net.trafo['id_characteristic_table'] = pd.NA
+    add_column_to_df(net, "trafo", "id_characteristic_table")
+    add_column_to_df(net, "trafo", 'tap_dependency_table')
     net.trafo.at[1, 'id_characteristic_table'] = 0
-    net.trafo['tap_dependency_table'] = pd.NA
     net.trafo.at[1, 'tap_dependency_table'] = True
     # add spline characteristics for one transformer based on trafo_characteristic_table
     create_trafo_characteristic_object(net)

pandapower/test/loadflow/test_runpp.py

@@ -14,6 +14,7 @@
 
 from pandapower import pp_dir
 from pandapower.auxiliary import _check_connectivity, _add_ppc_options, lightsim2grid_available
+from pandapower.create._utils import add_column_to_df
 from pandapower.create import create_bus, create_empty_network, create_ext_grid, create_dcline, create_load, \
     create_sgen, create_switch, create_transformer, create_xward, create_transformer3w, create_gen, create_shunt, \
     create_line_from_parameters, create_line, create_impedance, create_storage, create_buses, \
@@ -1395,11 +1396,8 @@ def test_tap_dependent_impedance():
          'angle_deg': [0, 0, 0, 0, 0], 'vk_percent': [5.5, 5.8, 6, 6.2, 6.5],
          'vkr_percent': [1.4, 1.42, 1.44, 1.46, 1.48], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan,
          'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan})
-    if 'id_characteristic_table' not in net.trafo:
-        net.trafo['id_characteristic_table'] = pd.NA
-    net.trafo.at[0, 'id_characteristic_table'] = 0
-    if 'tap_dependency_table' not in net.trafo:
-        net.trafo['tap_dependency_table'] = pd.NA
+    add_column_to_df(net, "trafo", "id_characteristic_table")
+    add_column_to_df(net, "trafo", 'tap_dependency_table')
     net.trafo.at[0, 'tap_dependency_table'] = True
     net.trafo.at[1, 'tap_dependency_table'] = False
 
@@ -1410,10 +1408,8 @@ def test_tap_dependent_impedance():
          'vkr_mv_percent': [0.3, 0.3, 0.3, 0.3, 0.3], 'vk_lv_percent': [1, 1, 1, 1, 1],
          'vkr_lv_percent': [0.3, 0.3, 0.3, 0.3, 0.3]})
     net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_rows], ignore_index=True)
-    if 'id_characteristic_table' not in net.trafo3w:
-        net.trafo3w['id_characteristic_table'] = pd.NA
-    if 'tap_dependency_table' not in net.trafo3w:
-        net.trafo3w['tap_dependency_table'] = pd.NA
+    add_column_to_df(net, "trafo3w", "id_characteristic_table")
+    add_column_to_df(net, "trafo33w", 'tap_dependency_table')
     net.trafo3w.at[0, 'id_characteristic_table'] = 1
     net.trafo3w.at[0, 'tap_dependency_table'] = True
 
@@ -1462,10 +1458,8 @@ def test_tap_table_order():
          'vk_hv_percent': [0.95, 0.98, 1, 1.02, 1.05], 'vkr_hv_percent': [0.3, 0.3, 0.3, 0.3, 0.3],
          'vk_mv_percent': [1, 1, 1, 1, 1], 'vkr_mv_percent': [0.3, 0.3, 0.3, 0.3, 0.3],
          'vk_lv_percent': [1, 1, 1, 1, 1], 'vkr_lv_percent': [0.3, 0.3, 0.3, 0.3, 0.3]})
-    if 'id_characteristic_table' not in net.trafo3w:
-        net.trafo3w['id_characteristic_table'] = pd.NA
-    if 'tap_dependency_table' not in net.trafo3w:
-        net.trafo3w['tap_dependency_table'] = pd.NA
+    add_column_to_df(net, "trafo3w", "id_characteristic_table")
+    add_column_to_df(net, "trafo3w", 'tap_dependency_table')
     net.trafo3w.at[0, 'id_characteristic_table'] = 0
     net.trafo3w.at[0, 'tap_dependency_table'] = True
 
@@ -1476,10 +1470,8 @@ def test_tap_table_order():
          'vkr_percent': [1.4, 1.42, 1.44, 1.46, 1.48, 1.4, 1.42, 1.44, 1.46, 1.48], 'vk_hv_percent': np.nan, 'vkr_hv_percent': np.nan,
          'vk_mv_percent': np.nan, 'vkr_mv_percent': np.nan, 'vk_lv_percent': np.nan, 'vkr_lv_percent': np.nan})
     net["trafo_characteristic_table"] = pd.concat([net["trafo_characteristic_table"], new_rows], ignore_index=True)
-    if 'id_characteristic_table' not in net.trafo:
-        net.trafo['id_characteristic_table'] = pd.NA
-    if 'tap_dependency_table' not in net.trafo:
-        net.trafo['tap_dependency_table'] = pd.NA
+    add_column_to_df(net, "trafo", "id_characteristic_table")
+    add_column_to_df(net, "trafo", 'tap_dependency_table')
     net.trafo.at[0, 'id_characteristic_table'] = 2
     net.trafo.at[1, 'id_characteristic_table'] = 1
     net.trafo.at[0, 'tap_dependency_table'] = True
@@ -1682,9 +1674,7 @@ def test_q_capability_curve():
                         0, -265.01001, -134.00999, -0.01000],
          'q_max_mvar': [0.01000, 134.00999,  228.00999, 257.01001, 261.01001, 261.01001, 261.01001, 257.01001, 30, 40,
                         134.0099, 0.01]})
-
-    if 'id_q_capability_characteristic' not in net.gen:
-        net.gen["id_q_capability_characteristic"] = pd.NA
+    add_column_to_df(net, "gen", "id_q_capability_characteristic")
     net.gen.at[0, "id_q_capability_characteristic"] = 0
     net.gen['curve_style'] = "straightLineYValues"
 
@@ -1733,8 +1723,7 @@ def test_q_capability_curve_for_sgen():
                         -265.01001, -134.00999, -0.01000],
          'q_max_mvar': [0.01000, 134.00999,  228.00999, 257.01001, 261.01001, 261.01001, 261.01001, 257.01001, 218.0099945068,
                         134.0099, 0.01]})
-    if 'id_q_capability_characteristic' not in net.sgen:
-        net.sgen["id_q_capability_characteristic"] = pd.NA
+    add_column_to_df(net, "sgen", "id_q_capability_characteristic")
     net.sgen.at[0, "id_q_capability_characteristic"] = 0
     net.sgen['curve_style'] = "straightLineYValues"
     create_q_capability_characteristics_object(net)