def build_chart(self):
mun_data = models.MunData.objects.get(pk=self.kwargs['pk'])
hh = round((mun_data.dem_th_energy_hh * 1000 / mun_data.pop_2017))
rca = round((mun_data.dem_th_energy_rca * 1000 / mun_data.pop_2017))
data = pd.DataFrame({
'name': ['Haushalte', 'GHD und Landw.'],
'y': [hh, rca]
})
data.set_index('name', inplace=True)
# convert data to appropriate format for pie chart
data = data.reset_index().to_dict(orient='records')
setup_labels = {
'title': {'text': 'Wärmebedarf'},
'subtitle': {'text': 'je EinwohnerIn nach Verbrauchergruppe'},
'plotOptions': {
'pie': {
'dataLabels': {
'format': '<b>{point.name}</b>: {point.y} KWh<br>({point.percentage:.1f} %)',
}
}
},
'tooltip': {
'pointFormat': '<b>{point.name}</b>: {point.y} KWh<br>({point.percentage:.1f} %)'
}
}
chart = visualizations.HCPiechart(
data=data,
setup_labels=setup_labels,
style='display: inline-block'
)
return chart
def build_chart(self):
mun_data = models.MunData.objects.get(pk=self.kwargs['pk'])
wind = round((mun_data.gen_el_energy_wind / mun_data.pop_2017), 1)
pv_roof = round((mun_data.gen_el_energy_pv_roof / mun_data.pop_2017), 1)
pv_ground = round((mun_data.gen_el_energy_pv_ground / mun_data.pop_2017), 1)
hydro = round((mun_data.gen_el_energy_hydro / mun_data.pop_2017), 1)
data = pd.DataFrame({
'name': ['Wind', 'PV Dach', 'PV Freifläche', 'Hydro'],
'y': [wind, pv_roof, pv_ground, hydro]
})
data.set_index('name', inplace=True)
# convert data to appropriate format for pie chart
data = data.reset_index().to_dict(orient='records')
setup_labels = {
'title': {'text': 'Gewonnene Energie aus EE'},
'subtitle': {'text': 'je EinwohnerIn'},
'plotOptions': {
'pie': {
'dataLabels': {
'format': '<b>{point.name}</b>: {point.y} MWh<br>({point.percentage:.1f} %)',
}
}
},
'tooltip': {
'pointFormat': '<b>{point.name}</b>: {point.y} MWh<br>({point.percentage:.1f} %)'
}
}
chart = visualizations.HCPiechart(
data=data,
setup_labels=setup_labels,
style='display: inline-block'
)
return chart
def build_chart(self):
mun_data = models.MunData.objects.get(pk=self.kwargs['pk'])
wind = round((mun_data.gen_capacity_wind / mun_data.area), 2)
pv_roof = round((mun_data.gen_capacity_pv_roof_large / mun_data.area), 2)
pv_ground = round((mun_data.gen_capacity_pv_ground / mun_data.area), 2)
hydro = round((mun_data.gen_capacity_hydro / mun_data.area), 2)
bio = round((mun_data.gen_capacity_bio / mun_data.area), 2)
data = pd.DataFrame({
'name': ['Wind', 'PV Dach, groß', 'PV Freifläche', 'Hydro', 'Bio'],
'y': [wind, pv_roof, pv_ground, hydro, bio]
})
data.set_index('name', inplace=True)
# convert data to appropriate format for pie chart
data = data.reset_index().to_dict(orient='records')
setup_labels = {
'title': {'text': 'Installierte Leistung EE'},
'subtitle': {'text': 'je km²'},
'plotOptions': {
'pie': {
'dataLabels': {
'format': '<b>{point.name}</b>: {point.y} MW<br>({point.percentage:.1f} %)',
}
}
},
'tooltip': {
'pointFormat': '<b>{point.name}</b>: {point.y} MW<br>({point.percentage:.1f} %)'
}
}
chart = visualizations.HCPiechart(
data=data,
setup_labels=setup_labels,
style='display: inline-block'
)
return chart
def visualize(self):
if self.type == 'line':
visualization = visualizations.HCTimeseries(
data=self.data,
setup_labels=self.setup_labels,
style='display: inline-block')
elif self.type == 'pie':
# temp data
data = pd.DataFrame({'name': ['a', 'b', 'c'], 'y': [100, 30, 20]})
data.set_index('name', inplace=True)
# convert data to appropriate format for pie chart
data = data.reset_index().to_dict(orient='records')
visualization = visualizations.HCPiechart(
data=data,
setup_labels=self.setup_labels,
style='display: inline-block')
elif self.type == 'column':
visualization = visualizations.HCStackedColumn(
data=self.data,
setup_labels=self.setup_labels,
style='display: inline-block')
else:
raise ValueError
return visualization