def create(self, **kwargs):
area = kwargs['area']
features = Gewerbeanteile.features().filter(id_teilflaeche=area.id)
df = features.to_pandas()
basedata = ProjectManager().basedata
df_branchen = basedata.get_table('Gewerbe_Branchen',
'Definition_Projekt').to_pandas()
colors = plt.cm.Accent(np.linspace(0, 1, len(df)))
idx = df['anteil_branche'] > 0
df = df[idx]
colors = colors[idx]
df_branchen.rename(columns={'ID_Branche_ProjektCheck': 'id_branche'},
inplace=True)
joined = df.merge(df_branchen, on='id_branche')
figure = plt.figure()
subplot = figure.add_subplot(111)
ax = joined['anteil_branche'].plot(
kind='pie',
labels=[''] * len(df),
autopct='%.0f%%',
figsize=(8, 8),
title=' ',
#shadow=True,
#explode=[0.1] * len(table_df),
colors=colors,
ax=subplot)
#title = ax.set_title(self.title)
#title.set_position((.5, 1.0))
plt.figtext(.5,
.92,
self.title,
horizontalalignment='center',
fontsize=12) #, fontweight='bold')
ax.set_ylabel('')
ax.set_xlabel('')
ax.legend(joined['Name_Branche_ProjektCheck'],
loc='upper center',
bbox_to_anchor=(0.5, 0.05))
# didn't find a way to pass custom colors directly
for color, handle in zip(colors, ax.get_legend().legendHandles):
handle.set_linewidth(2.0)
handle.set_color(color)
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.y0 * 0.5, box.width, box.height])
figure.tight_layout()
figure.subplots_adjust(bottom=0.2)
return figure
def next_working_day(min_days_infront=2):
'''
get the next working day in germany (no holidays, no saturdays, no sundays
in all federal states)
requires the basetable "Feriendichte" to hold days infront of today
Parameters
----------
min_days_infront : int (default: 2)
returned day will be at least n days infront
Returns
-------
datetime.date
the next day without holidays,
if day is out of range of basetable: today + min_days_infront
'''
today = np.datetime64(date.today())
basedata = ProjectManager().basedata
day = today + np.timedelta64(min_days_infront,'D')
# get working days (excl. holidays)
where = ("Wochentag <> 'Samstag' and "
"Wochentag <> 'Sonntag' and "
"Anteil_Ferien_Bevoelkerung = 0")
table = basedata.get_table('Feriendichte', 'Basisdaten_deutschland')
table.where = where
df_density = table.to_pandas()
# can't compare directly because datetime64 has no length
dates = pd.to_datetime(df_density['Datum'], format='%Y/%m/%d %H:%M:%S.%f')
df_density['Datum'] = dates.dt.tz_convert(None)
df_density.sort_values('Datum', inplace=True)
infront = np.where(df_density['Datum'] >= day)[0]
if len(infront) > 0:
# get the first day matching all conditions
day = df_density.iloc[infront[0]]['Datum']
return pd.Timestamp(day).date()