Fix installed capacities plot function

CHANGELOG.rst

@@ -225,6 +225,8 @@ Added
   `#868 <https://github.com/openego/eGon-data/issues/868>`_
 * Write simBEV metadata to DB table
   `PR #978 <https://github.com/openego/eGon-data/pull/978>`_
+* Add plotting function for installed capacities
+  `#763 <https://github.com/openego/eGon-data/issues/763>`_  
 
 .. _PR #159: https://github.com/openego/eGon-data/pull/159
 .. _PR #703: https://github.com/openego/eGon-data/pull/703

src/egon/data/datasets/plotdatascn.py

@@ -0,0 +1,109 @@
+"""
+Created on Tue May 24 14:42:05 2022
+Plotdatascn.py defines functions to plot to provide a better context of the different parameters part of
+scenarios eGon2035 and eGon100RE .
+@author: Alonso
+
+"""
+import logging
+import os
+
+from matplotlib import pyplot as plt
+import geopandas as gpd
+import matplotlib as mpl
+import pandas as pd
+
+from egon.data import db
+
+logger = logging.getLogger(__name__)
+
+if "READTHEDOCS" not in os.environ:
+    from geoalchemy2.shape import to_shape
+
+__copyright__ = (
+    "Flensburg University of Applied Sciences, "
+    "Europa-Universität Flensburg, "
+    "Centre for Sustainable Energy Systems, "
+    "DLR-Institute for Networked Energy Systems"
+)
+__license__ = ""
+__author__ = ""
+
+
+def plot_installedcapacity(carrier, scenario="eGon2035"):
+    """
+    Plots color maps according to the capacity of different generators
+    of the two existing scenarios (eGon2035 and eGon100RE)
+
+
+    Parameters
+    ----------
+    carrier : generators
+    The list of generators: biomass, central_biomass_CHP, central_biomass_CHP_heat,
+    industrial_biomass_CHP, solar, solar_rooftop, wind_offshore, wind_onshore.
+
+    scenario: eGon2035, eGon100RE
+
+    Returns
+    ----------
+    """
+
+    # This function must be called while in the folder
+    # that contains the file egon-data.configuration.yaml.
+    con = db.engine()
+    # imports buses of Germany
+    SQLBus = (
+        "SELECT bus_id, country FROM grid.egon_etrago_bus WHERE country='DE'"
+    )
+    busDE = pd.read_sql(SQLBus, con)
+    busDE = busDE.rename({"bus_id": "bus"}, axis=1)
+    # Imports grid districs
+    sql = "SELECT bus_id, geom FROM grid.egon_mv_grid_district"
+    distr = gpd.GeoDataFrame.from_postgis(sql, con)
+    distr = distr.rename({"bus_id": "bus"}, axis=1)
+    distr = distr.set_index("bus")
+    # merges grid districts with buses
+    distr = pd.merge(busDE, distr, on="bus")
+    # Imports generator
+    sqlCarrier = "SELECT carrier, p_nom, bus FROM grid.egon_etrago_generator"
+    sqlCarrier = "SELECT * FROM grid.egon_etrago_generator"
+    Carriers = pd.read_sql(sqlCarrier, con)
+    Carriers = Carriers.loc[Carriers["scn_name"] == scenario]
+    Carriers = Carriers.set_index("bus")
+
+    CarrierGen = Carriers.loc[Carriers["carrier"] == carrier]
+    # merges districts with generators
+    Merge = pd.merge(CarrierGen, distr, on="bus", how="outer")
+
+    Merge.loc[Merge["carrier"] != carrier, "p_nom"] = 0
+    Merge.loc[Merge["country"] != "DE", "p_nom"] = 0
+
+    gdf = gpd.GeoDataFrame(Merge, geometry="geom")
+    pnom = gdf["p_nom"]  #
+    # 0.95 quantile is used to filter values that are too high and make noise in the plots.
+    max_pnom = pnom.quantile(0.95)
+    gdf = gdf.to_crs(epsg=3857)
+
+    fig, ax = plt.subplots(1, 1)
+
+    ax.set_axis_off()
+    plt.title(f" {carrier} installed capacity in MW , {scenario}")
+    cmap = mpl.cm.coolwarm
+
+    norm = mpl.colors.Normalize(vmin=0, vmax=max_pnom)
+    gdf.plot(
+        column="p_nom",
+        ax=ax,
+        legend=False,
+        legend_kwds={"label": "p_nom(MW)", "orientation": "vertical"},
+        cmap=cmap,
+        norm=norm,
+        edgecolor="black",
+        linewidth=0.1,
+        zorder=2,
+    )
+    scatter = ax.collections[0]
+    cbar = plt.colorbar(scatter, ax=ax, extend="max")
+    cbar.set_label("p_nom(MW)", rotation=90)
+
+    return