def update_ratio_bar(min_seq):
data = call_full_data()
data = data.loc[data['Date'] == data['Date'].max()]
data = data.loc[data['total_sequence'] > min_seq].sort_values(
by=['case_sequence_ratio'])
case_sequence_ratio_bar = create_case_sequence_ratio_bar_fig(data)
return case_sequence_ratio_bar
def update_bar(log_radio, min_seq, sort_radio_selection):
data = call_full_data()
data = data.loc[data['Date'] == data['Date'].max()]
data = data.loc[data['total_sequence'] > min_seq].sort_values(
by=sort_radio_selection)
bar_fig = create_double_bar_fig(data)
bar_fig.update_xaxes(type=log_radio)
return bar_fig
def update_map_line(ClickData, log_radio_line, checklist,
case_sequence_checklist):
data = call_full_data()
try:
data = data.loc[data['iso3'] == ClickData['points'][0]['location']]
fig = create_time_series_country(data)
except:
mask = data.continent.isin(checklist)
fig = create_time_series_continent(data[mask], case_sequence_checklist)
fig.update_yaxes(type=log_radio_line)
fig.update_layout(transition_duration=500)
#try:print(ClickData['points'][0]['location'])
#except: print('unable to print')
return fig
from dash.dependencies import Input, Output, State
import plotly.express as px
#My functions
from figures.map_figs import create_case_sequence_scatter_mapbox_fig
from figures.line_figs import create_time_series_country, create_time_series_continent
from figures.bar_figs import create_double_bar_fig, create_case_sequence_ratio_bar_fig
from pipeline.call_data import call_full_data
#############
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'Covid-19 Dashboard'
px.set_mapbox_access_token(open('mapbox_key.txt').read())
all_continents = call_full_data()['continent'].unique()
data = call_full_data()
app.layout = html.Div([
#BANNER
html.Div([
html.H2("COVID SEQUENCING DASHBOARD"),
html.Img(src="/assets/covid_image.png")
],
className="banner"),
html.
P("This interactive Dashboard aims to provide visualization for global COVID-19 sequencing coverage. This dashboard is fully interactive and easily customizable. A full writeup can be found at the following link: "
),
dcc.Link('github.com/choldener/Vector-Engineering-Project',
href='https://github.com/choldener/Vector-Engineering-Project'),
# )
# fig.update_layout(mapbox_style="carto-positron",
# mapbox_zoom=1, mapbox_center={"lat": 37.0902, "lon": -95.7129},
# width = 1800, height=1000
# )
# fig2 = px.scatter_mapbox(data, lat = 'Lat', lon = 'Long_', size = 'total_sequence_scale',)
# fig2.update_traces(hovertemplate=None, hoverinfo='skip')
# fig.add_trace(
# fig2.data[0]
# )
return fig
df = call_full_data()
df = df.loc[df['Date'] == df['Date'].max()]
app.layout = html.Div(children=[
dcc.Graph(
id='debug-plot',
figure=create_cases_map_fig(df)
def create_case_sequence_scatter_mapbox_fig(relayout_data=None):
"""Creates bar graph with cases represented as color and a bubble representing sequences"""
#DATA GATHERING
data = call_full_data()
data = data.loc[data['Date'] == data['Date'].max()]
data = data.loc[data['total_sequence'] > 0].sort_values(
by=['total_sequence'])
#geojson
with urlopen(
'https://raw.githubusercontent.com/johan/world.geo.json/master/countries.geo.json'
) as response:
countries = json.load(response)
#RELAY DATA
if relayout_data == None:
center_lat = 27
center_lon = 0
map_zoom = .75
else:
center_lat = float(relayout_data['mapbox.center']['lat'])
center_lon = float(relayout_data['mapbox.center']['lon'])
map_zoom = float(relayout_data['mapbox.zoom'])
#Colored mapbox creation
fig = px.choropleth_mapbox(data,
geojson=countries,
locations='iso3',
color=np.log10(data['Cases']),
color_continuous_scale=px.colors.sequential.Jet,
opacity=0.75,
mapbox_style='light',
width=900,
height=600,
hover_name="Country",
hover_data={
'Lat': False,
'Long_': False,
'total_sequence': True,
'Cases': True,
'iso3': False
},
zoom=map_zoom,
center=dict(
lat=center_lat,
lon=center_lon,
))
fig.update_layout(coloraxis_colorbar=dict(title='Cases',
tickvals=[
-1,
np.log10(1000),
np.log10(10000),
np.log10(100000),
np.log10(1000000),
np.log10(10000000)
],
ticktext=[
'0', '1,000', '10,000',
'100,000', '1,000,000',
'10,000,000'
]),
clickmode='event+select')
#Bubble mapbox creation
fig2 = px.scatter_mapbox(data,
lat='Lat',
lon='Long_',
size='total_sequence_scale',
size_max=70,
zoom=map_zoom,
center=dict(lat=center_lat, lon=center_lon),
mapbox_style='light',
width=1800,
height=1000,
opacity=0.5)
fig2.update_traces(hovertemplate=None, hoverinfo='skip')
#adding bubble mapbox data to color mapbox
fig.add_trace(fig2.data[0])
return fig