def initial_pie():
ts_confirmed, ts_death, ts_recovered = get_data_from_postgres()
filtered_ts_confirmed = ts_confirmed.iloc[:,-2]
filtered_ts_death = ts_death.iloc[:,-2]
filtered_ts_recovered = ts_recovered.iloc[:,-2]
active = filtered_ts_confirmed.sum() - filtered_ts_death.sum() - filtered_ts_recovered.sum()
labels = ['Recovered','Deaths','Active']
values = [filtered_ts_recovered.sum(),filtered_ts_death.sum(),active]
colors = ['#5cb85c', '#d9534f', '#f0ad4e']
fig = go.Figure(data=[go.Pie(labels=labels, values=values, hole=.3, titlefont=dict(color='white', size=20) )])
fig.update_traces(hoverinfo='label+percent+value', textinfo='none', textfont_size=20,
marker=dict(colors=colors))
fig.update_layout(
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
legend = dict(font = dict(color='white')),
transition={
'duration': 500,
'easing': 'cubic-in-out',}
)
return fig
def update_pie(unix_date, selected_nation):
ts_confirmed, ts_death, ts_recovered = get_data_from_postgres()
# ts_recovered = pd.read_csv('recovered.csv')
# ts_death = pd.read_csv('deaths.csv')
# ts_confirmed = pd.read_csv('confirmed.csv')
#unix_date=1585440000
date = unix_to_date(unix_date)
## Country Dropdown
if 'Worldwide' in selected_nation or not selected_nation:
#filtered_df = df
filtered_ts_confirmed = ts_confirmed
filtered_ts_death = ts_death
filtered_ts_recovered = ts_recovered
else:
#filtered_df = df[df['Country/Region'].isin(selected_nation)]
filtered_ts_confirmed = ts_confirmed[ts_confirmed['Country/Region'].isin(selected_nation)]
filtered_ts_death = ts_death[ts_death['Country/Region'].isin(selected_nation)]
filtered_ts_recovered = ts_recovered[ts_recovered['Country/Region'].isin(selected_nation)]
active = filtered_ts_confirmed[date].sum() - filtered_ts_death[date].sum() - filtered_ts_recovered[date].sum()
labels = ['Recovered','Deaths','Active']
values = [filtered_ts_recovered[date].sum(),filtered_ts_death[date].sum(),active]
#df = pd.DataFrame(data)
# ts_recovered[date].sum()
# ts_death[date].sum()
# ts_confirmed[date].sum()
colors = ['#5cb85c', '#d9534f', '#f0ad4e']
fig = go.Figure(data=[go.Pie(labels=labels, values=values, hole=.3, titlefont=dict(color='white', size=20) )])
fig.update_traces(hoverinfo='label+percent+value', textinfo='none', textfont_size=20,
marker=dict(colors=colors))
fig.update_layout(
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
legend = dict(font = dict(color='white')),
transition={
'duration': 500,
'easing': 'cubic-in-out',}
)
return fig
def update_map(selected_nation, selected_case, click, unix_date):
#unix_date=1585008000
#selected_nation=['Worldwide']
ts_confirmed, ts_death, ts_recovered = get_data_from_postgres()
date = unix_to_date(unix_date)
#date='3/25/20'
zoom = 3
## Country Dropdown
if 'Worldwide' in selected_nation or not selected_nation:
#filtered_df = df
filtered_ts_confirmed = ts_confirmed
filtered_ts_death = ts_death
filtered_ts_recovered = ts_recovered
zoom = 2
else:
#filtered_df = df[df['Country/Region'].isin(selected_nation)]
filtered_ts_confirmed = ts_confirmed[ts_confirmed['Country/Region'].isin(selected_nation)]
filtered_ts_death = ts_death[ts_death['Country/Region'].isin(selected_nation)]
filtered_ts_recovered = ts_recovered[ts_recovered['Country/Region'].isin(selected_nation)]
## China Checkbox
if not click:
#filtered_df = filtered_df[filtered_df['Country/Region'] != 'China']
filtered_ts_confirmed = filtered_ts_confirmed[filtered_ts_confirmed['Country/Region'] != 'China']
filtered_ts_death = filtered_ts_death[filtered_ts_death['Country/Region'] != 'China']
filtered_ts_recovered = filtered_ts_recovered[filtered_ts_recovered['Country/Region'] != 'China']
px.set_mapbox_access_token(mapbox_access_token)
## Rename columns to prettify hover data
temp_deaths_df = filtered_ts_death.rename(columns = {date:'Deaths', 'Lat':'Latitude', 'Long':'Longitude'})
temp_recovered_df = filtered_ts_recovered.rename(columns = {date:'Recovered', 'Lat':'Latitude', 'Long':'Longitude'})
temp_confirmed_df = filtered_ts_confirmed.rename(columns = {date:'Confirmed', 'Lat':'Latitude', 'Long':'Longitude'})
#Some data from JHU appears as -1 unsure why
temp_recovered_df[temp_recovered_df['Recovered'] < 0] = 0
temp_confirmed_df[temp_confirmed_df['Confirmed'] < 0] = 0
temp_deaths_df[temp_deaths_df['Deaths'] < 0] = 0
#assumes order of countries from datasets are the same
temp_all = temp_confirmed_df[['City/Country', 'Confirmed','Latitude','Longitude']]
temp_all.insert(2,'Deaths', temp_deaths_df[['Deaths']])
temp_all.insert(2,'Recovered',temp_recovered_df[['Recovered']])
if selected_case == 'Deaths':
fig = px.scatter_mapbox(temp_deaths_df, lat="Latitude", lon="Longitude", size='Deaths', size_max=100, hover_name="City/Country")
fig.update_traces(hoverinfo='text', marker=dict(sizemin=5, color='Red'))
elif selected_case == 'Recovered':
fig = px.scatter_mapbox(temp_recovered_df, lat="Latitude", lon="Longitude", size="Recovered",
size_max=100, hover_name="City/Country")
fig.update_traces(hoverinfo='text', marker=dict(sizemin=5, color='Green'))
elif selected_case == 'Confirmed':
fig = px.scatter_mapbox(temp_confirmed_df, lat="Latitude", lon="Longitude", size="Confirmed",
size_max=100, hover_name="City/Country")
fig.update_traces(hoverinfo='text', marker=dict(sizemin=5, color='Blue'))
else:
fig = px.scatter_mapbox(temp_all, lat="Latitude", lon="Longitude", color="Deaths", size="Confirmed",
#color_continuous_scale=px.colors.diverging.Picnic,
size_max=50, hover_name="City/Country",
#hover_data=["Confirmed", "Recovered", "Deaths"],
hover_data=["Confirmed", "Deaths"],
)
fig.update_traces(hoverinfo='text', marker=dict(sizemin=2),showlegend=False)
fig.update(
layout=dict(title=dict(x=0.5), paper_bgcolor=colors['background'] )
)
fig.update_layout(
autosize=True,
height=750,
#width=1500,
font={
'family': 'Courier New, monospace',
'size': 18,
'color': 'white'
},
hovermode='closest',
legend=dict(
font={'color':colors['background']},
),
mapbox=dict(
accesstoken=mapbox_access_token,
bearing=0,
style="dark",
# center=dict(
# lat=56,
# lon=324
# ),
pitch=0,
zoom=zoom
),
)
return fig
def update_graph(unix_date, selected_nation):
ts_confirmed, ts_death, ts_recovered = get_data_from_postgres()
#unix_date=1585440000
date = unix_to_date(unix_date)
## Country Dropdown
if 'Worldwide' in selected_nation or not selected_nation:
#filtered_df = df
filtered_ts_confirmed = ts_confirmed
filtered_ts_death = ts_death
filtered_ts_recovered = ts_recovered
else:
#filtered_df = df[df['Country/Region'].isin(selected_nation)]
filtered_ts_confirmed = ts_confirmed[ts_confirmed['Country/Region'].isin(selected_nation)]
filtered_ts_death = ts_death[ts_death['Country/Region'].isin(selected_nation)]
filtered_ts_recovered = ts_recovered[ts_recovered['Country/Region'].isin(selected_nation)]
listy = []
for a in getTimeScale():
listy.append(a)
#print(a +' ? '+ date)
if a == date:
#print('-------------------------')
break
#listy.insert(0,'City/Country')
#for individual countries
# filtered_ts_confirmed = ts_confirmed[listy]
# filtered_ts_death = ts_death[listy]
# filtered_ts_recovered = ts_recovered[listy]
#filtered_ts_df = ts_confirmed[['City/Country','3/3/20']]
## Total events on a given day
filtered_ts_confirmed = filtered_ts_confirmed[listy[1:]].sum()
filtered_ts_death = filtered_ts_death[listy[1:]].sum()
filtered_ts_recovered = filtered_ts_recovered[listy[1:]].sum()
trace0 = go.Scatter(x=listy[1:], y=filtered_ts_confirmed,
mode='lines',
name='Confirrmed',
line = {'color':'#0275d8'},
fill='tozeroy'
)
trace1 = go.Scatter(x=listy[1:], y=filtered_ts_death,
mode='lines',
name='Deaths',
line = {'color':'#d9534f'},
fill='tozeroy'
)
trace2 = go.Scatter(x=listy[1:], y=filtered_ts_recovered,
mode='lines',
name='Recovered',
line = {'color':'#5cb85c'},
fill='tozeroy'
)
data = [trace0, trace2, trace1]
# print(selected_nation)
# title = ' '.join([str(x) for x in selected_nation]) + ' Cases'
# print(title)
layout = go.Layout(paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font={
'family': 'Courier New, monospace',
'size': 18,
'color': 'white'
},
#title=title,
xaxis={'gridcolor':'rgb(46,47,47)','autorange': True,},
yaxis={'gridcolor':'rgb(46,47,47)','autorange': True,'title':'Number of cases'},
hovermode='closest',
transition={
'duration': 500,
'easing': 'cubic-in-out',}
)
fig = go.Figure(data=data, layout=layout)
fig.update_layout(
#title=title,
legend=dict(
x=0.01,
y=1,
traceorder="normal",
font=dict(
family="sans-serif",
size=12,
color="#f7f7f7"
),
bgcolor="#292b2c",
bordercolor="#f7f7f7",
borderwidth=2,
)
)
return fig
def initial_graph():
ts_confirmed, ts_death, ts_recovered = get_data_from_postgres()
#Recovery data gets updated late compared to datasets from JHU
x_axis = ts_recovered.columns[4:-1]
trace0 = go.Scatter(x=x_axis, y=ts_confirmed[x_axis].sum(),
mode='lines',
name='Confirrmed',
line = {'color':'#0275d8'},
fill='tozeroy'
)
trace1 = go.Scatter(x=x_axis, y=ts_death[x_axis].sum(),
mode='lines',
name='Deaths',
line = {'color':'#d9534f'},
fill='tozeroy'
)
trace2 = go.Scatter(x=x_axis, y=ts_recovered[x_axis].sum(),
mode='lines',
name='Recovered',
line = {'color':'#5cb85c'},
fill='tozeroy'
)
data = [trace0, trace2, trace1]
layout = go.Layout(paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font={
'family': 'Courier New, monospace',
'size': 18,
'color': 'white'
},
#title=title,
xaxis={'gridcolor':'rgb(46,47,47)','autorange': True,},
yaxis={'gridcolor':'rgb(46,47,47)','autorange': True,'title':'Number of cases'},
hovermode='closest',
transition={
'duration': 500,
'easing': 'cubic-in-out',}
)
fig = go.Figure(data=data, layout=layout)
fig.update_layout(
#title=title,
legend=dict(
x=0.01,
y=1,
traceorder="normal",
font=dict(
family="sans-serif",
size=12,
color="#f7f7f7"
),
bgcolor="#292b2c",
bordercolor="#f7f7f7",
borderwidth=2,
)
)
return fig
def initial_map():
ts_confirmed, ts_death, ts_recovered = get_data_from_postgres()
date = ts_recovered.columns[-2]
zoom = 2
filtered_ts_confirmed = ts_confirmed
filtered_ts_death = ts_death
filtered_ts_recovered = ts_recovered
px.set_mapbox_access_token(mapbox_access_token)
## Rename columns to prettify hover data
temp_deaths_df = filtered_ts_death.rename(columns = {date:'Deaths', 'Lat':'Latitude', 'Long':'Longitude'})
temp_recovered_df = filtered_ts_recovered.rename(columns = {date:'Recovered', 'Lat':'Latitude', 'Long':'Longitude'})
temp_confirmed_df = filtered_ts_confirmed.rename(columns = {date:'Confirmed', 'Lat':'Latitude', 'Long':'Longitude'})
#Some data from JHU appears as -1 unsure why
temp_recovered_df[temp_recovered_df['Recovered'] < 0] = 0
temp_confirmed_df[temp_confirmed_df['Confirmed'] < 0] = 0
temp_deaths_df[temp_deaths_df['Deaths'] < 0] = 0
#assumes order of countries from datasets are the same
temp_all = temp_confirmed_df[['City/Country', 'Confirmed','Latitude','Longitude']]
temp_all.insert(2,'Deaths', temp_deaths_df[['Deaths']])
temp_all.insert(2,'Recovered',temp_recovered_df[['Recovered']])
fig = px.scatter_mapbox(temp_all, lat="Latitude", lon="Longitude", color="Deaths", size="Confirmed",
#color_continuous_scale=px.colors.diverging.Picnic,
size_max=50, hover_name="City/Country",
#hover_data=["Confirmed", "Recovered", "Deaths"],
hover_data=["Confirmed", "Deaths"],
)
fig.update_traces(hoverinfo='text', marker=dict(sizemin=2),showlegend=False)
fig.update(
layout=dict(title=dict(x=0.5), paper_bgcolor=colors['background'] )
)
fig.update_layout(
autosize=True,
height=750,
#width=1500,
font={
'family': 'Courier New, monospace',
'size': 18,
'color': 'white'
},
hovermode='closest',
legend=dict(
font={'color':colors['background']},
),
mapbox=dict(
accesstoken=mapbox_access_token,
bearing=0,
style="dark",
# center=dict(
# lat=56,
# lon=324
# ),
pitch=0,
zoom=zoom
),
)
return fig
html.Div(
[
dcc.Graph(id='time-series', figure=initial_graph()),
]
), width=12, lg=9),
]
)
], style={'padding-bottom':'20px'}),
#style={'padding-bottom': 40, 'padding-right': 40, 'padding-left': 40,}
## DROPDOWN ROW
html.Div([
dbc.Row(
[
dbc.Col([NationsDropdown(get_data_from_postgres()[0])]),
dbc.Col([CasesDropdown()]),
]
)
]),
html.Div([
daq.ToggleSwitch(
id='exclude-china',
value=True,
label=['Excluding China', 'Including China'],
color='#0275d8',
style={
'color': 'white',
'width':'350px'
}