def get_county_choropleth(start_datetime, end_datetime, output='json'):
data = d.get_traffic_accident_by_date(start_datetime, end_datetime)['countyId']
county_names = d.get_county()
data = data.value_counts()
data.index = data.index.map(lambda p: county_names.loc[p]['name'])
zeroes = pd.Series(data=0, index=county_names.name)
data = data + zeroes
data = data.fillna(0)
data = data.sort_values()
df = pd.DataFrame(dict(county=data.index, count=data.values))
geojson_file = os.path.join(os.path.dirname(__file__), 'regions_epsg_4326.geojson.txt')
with open(geojson_file, encoding='utf-8') as file:
geo_counties = json.loads(file.read())
fig = px.choropleth(data_frame=df, geojson=geo_counties, featureidkey='properties.NM4', locations='county', color='count',
color_continuous_scale='tealrose',
range_color=(0, df['count'].mean()*2),
projection='sinusoidal',
labels={'count':'Počet nehôd'},
hover_data={'county':False},
hover_name=df['county'])
fig.update_geos(fitbounds="locations", visible=False)
fig.update_layout(
margin={"r":0,"t":0,"l":0,"b":0},
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
geo=dict(bgcolor= 'rgba(0,0,0,0)'),
coloraxis_showscale=False,
)
return plots.encode_plot(fig, output)
def get_plot_total_accidents_by_county(start_datetime,
end_datetime,
output='json'):
acc = d.get_traffic_accident_by_date(start_datetime,
end_datetime)['countyId']
acc = acc.value_counts()
data = d.get_county()
data['count'] = 0
data['count'] += acc
data['count'] = data['count'].fillna(0)
data.sort_values(by='count', inplace=True)
fig = px.bar(
data,
x='name',
y='count',
custom_data=[data.index],
labels={
'count': 'Počet nehôd',
'name': 'Kraj'
},
)
fig.update_layout(
xaxis=dict(
title_text='Kraj',
titlefont=dict(size=20),
),
height=600,
yaxis=dict(
title_text='Celkový počet nehôd',
gridcolor='rgb(140,140,140)',
titlefont=dict(size=20),
),
dragmode=False,
margin={
"r": 0,
"t": 0,
"l": 0,
"b": 0
},
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(size=14, ),
)
return encode_plot(fig, output)
def get_plot_accident_trend_in_county(county_id,
start_datetime=None,
end_datetime=None):
data = d.get_traffic_accident_by_date(get_start_datetime(start_datetime),
get_end_datetime(end_datetime))
data = data.loc[data.countyId == county_id]['overallStartTime']
data = data.map(lambda p: p.date())
data = data.value_counts().sort_index()
sns.set_style("whitegrid")
fig = plt.figure(figsize=(25, 15))
plt.title("Vývoj nehôd v čase pre " +
d.get_county().loc[county_id]['name'],
fontsize=30,
pad=20)
plt.subplots_adjust(left=0.07, right=0.99)
g = sns.lineplot(x=data.index, y=data.values)
#g.set_xlabel("Deň",fontsize=30, labelpad=15)
g.set_ylabel("Počet nehôd", fontsize=30, labelpad=20)
#g.set_xticklabels(get_date_xtickslabels(data.index), rotation=90, fontsize=20)
g.tick_params(axis='x', labelsize=25, rotation=45)
g.tick_params(axis='y', labelsize=25)
return encode_plot(fig)
def get_districts_in_groups_by_county(num_in_one_group):
df = d.get_county()
retval = []
for i, row in df.iterrows():
retval.append([row['name'], get_districts_in_groups(i, 4)])
return retval
def get_counties_in_groups(num_in_one_group):
return form_groups(d.get_county(), 4)
def get_county_name(county_id):
names = d.get_county()
return names.loc[county_id]['name']
def get_county_xticklabels(index):
retval = []
counties = d.get_county()
for i in index:
retval.append(counties.loc[i]['name'])
return retval