def dataframe_to_date(usa_only=False, scale=1000):
# We should connect the last expensive data querying steps needed to render the graphs with this data
# Get Today's Date
today = datetime.date.today()
# Get the date 7 days ago
week_ago = today - datetime.timedelta(days=60)
# Create Variable = Async Data Fetch requesting date
df_list = fetch_to_date.main(date=str(week_ago),
value=scale,
usa_only=usa_only)
# returns a list [df1, df2, ... df7]
# loop through the list
for df in df_list:
print(f'Building Redis Storage on: {df["lastUpdate"][0]}-dataframe')
# Creates a redis instence to store data, turns df to dictionary & encodes in json
redis_instance.set(
f'{df["lastUpdate"][0]}-dataframe',
json.dumps(
df.to_dict(),
# This JSON Encoder will handle things like numpy arrays
# and datetimes
cls=plotly.utils.PlotlyJSONEncoder,
),
)
]
}
],
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
frames = []
for l in maps:
frames.append(go.Frame(data=l))
fig = go.Figure(data=[maps[0][0], maps[0][1], maps[0][2]], layout=layout, frames=frames[::-1])
return fig
if __name__ == '__main__':
map = request_map(fetch_to_date.main(date='2020-03-24', usa_only=False, value=500))
map.show()
print(map)
def query_to_date(date='2020-03-24', usa_only=False, scale=500):
data = fetch_to_date.main(date=date, value=scale, usa_only=usa_only)
return conn.setex('TO_Date', TIMEOUT, zlib.compress(pickle.dumps(data)))
def display_worldmap(date):
fetch_data = fetch_to_date.main(date, usa_only=False)
date_data = three_d(fetch_data)
return dcc.Graph(figure=date_data, style={'height': '85vh'})
dbc.Label("Cases / Scale", html_for="slider"),
dcc.Slider(id="slider",
min=1,
max=1000,
step=10,
value=400),
])
])),
width=3),
dbc.Col(html.H1(id='rate-slider', ), width=3),
]),
dbc.Row([
dbc.Col(html.Div(id='rate-scale'), md=12, lg=6),
dbc.Col(html.Div(
dcc.Graph(figure=usa_barchart(
data=fetch_to_date.main('2020-03-28', usa_only=True)),
style={'height': '75vh'})),
md=12,
lg=6)
]),
])))
tab_snapshot = dbc.Card(
dbc.CardBody([
dbc.Row([
# Header
dbc.Row([
dbc.Col(html.Div(), width=3),
dbc.Col(dcc.DatePickerSingle(
id='date-picker-single',
min_date_allowed=dt(2020, 3, 23),
text=x['countryRegion'],
name=str(x['lastUpdate'][0]),
customdata=x.loc[:, ['confirmed']],
hovertemplate="<b>%{text}</b><br><br>" +
"Confirmed: %{customdata[0]}<br>" + "<extra></extra>",
))
layout = go.Layout(
paper_bgcolor='#060606',
plot_bgcolor='rgba(0,0,0,0)',
barmode='stack',
title='Daily Growth By Country',
font=dict(family="Courier New, monospace", size=18, color="#7f7f7f"),
xaxis={
'rangeslider_visible':
True,
'range': [
data[-1]['lastUpdate'][0],
str(datetime.date.today() - datetime.timedelta(days=1))
]
},
)
fig = go.Figure(data=graphs, layout=layout)
return fig
if __name__ == '__main__':
fetch_data = fetch_to_date.main('2020-03-28', usa_only=False)
date_data = three_d(fetch_data).show()
"below":
'traces',
"sourcetype":
"raster",
"source": [
"https://basemap.nationalmap.gov/arcgis/rest/services/USGSImageryOnly/MapServer/tile/{z}/{y}/{x}"
]
}],
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(family="Courier New, monospace",
size=18,
color="#7f7f7f"))
frames = []
for m in maps:
frames.append(go.Frame(data=m))
fig = go.Figure(data=[maps[0][0], maps[0][1], maps[0][2]],
frames=frames,
layout=layout)
return fig
if __name__ == '__main__':
map = request_home_map(
fetch_to_date.main(date='2020-03-24', usa_only=False, value=10000))
map.show()
print(map)