#!pip install pandas
#!pip install plotly
#!pip install dash
#!pip install dash_bootstrap_components
import pandas as pd
pd.set_option('max_rows',20)
import plotly.express as px
import plotly.io as pio
pio.renderers.default = "browser"
import dash
from dash.dependencies import Input, Output
from dash import dcc
from dash import html
import dash_bootstrap_components as dbc
Get Data
CONF_URL = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
DEAD_URL = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv'
RECV_URL = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv'
covid_conf_ts = pd.read_csv(CONF_URL)
covid_dead_ts = pd.read_csv(DEAD_URL)
covid_recv_ts = pd.read_csv(RECV_URL)
Data Processing
#get data in cleaned time series format for country
def process_data(data,cntry='US',window=3):
conf_ts = data
conf_ts_cntry = conf_ts[conf_ts['Country/Region']==cntry]
final_dataset = conf_ts_cntry.T[4:].sum(axis='columns').diff().rolling(window=window).mean()[40:]
df = pd.DataFrame(final_dataset,columns=['Total'])
return df
#get overall wordlwide total for confirmed, recovered and dead cases
def get_overall_total(df):
return df.iloc[:,-1].sum()
conf_overall_total = get_overall_total(covid_conf_ts)
dead_overall_total = get_overall_total(covid_dead_ts)
recv_overall_total = conf_overall_total - dead_overall_total
print('Overall Confirmed:',conf_overall_total)
print('Overall Dead:',dead_overall_total)
print('Overall Recovered:',recv_overall_total)
Overall Confirmed: 251420477
Overall Dead: 5072444
Overall Recovered: 246348033
#get total for confirmed, recovered and dead for country
def get_cntry_total(df,cntry='US'):
return df[df['Country/Region']==cntry].iloc[:,-1].sum()
cntry = 'US'
conf_cntry_total = get_cntry_total(covid_conf_ts,cntry)
dead_cntry_total = get_cntry_total(covid_dead_ts,cntry)
recv_cntry_total = conf_cntry_total - dead_cntry_total
print(f'{cntry} Confirmed:',conf_cntry_total)
print(f'{cntry} Dead:',dead_cntry_total)
print(f'{cntry} Recovered:',recv_cntry_total)
US Confirmed: 46789031
US Dead: 758916
US Recovered: 46030115
Generate Line Graph Using Plotly
def fig_world_trend(cntry='US',window=3):
df = process_data(data=covid_conf_ts,cntry=cntry,window=window)
df.head(10)
if window==1:
yaxis_title = "Daily Cases"
else:
yaxis_title = "Daily Cases ({}-day MA)".format(window)
fig = px.line(df, y='Total', x=df.index, title='Daily confirmed cases trend for {}'.format(cntry),height=600,color_discrete_sequence =['maroon'])
fig.update_layout(title_x=0.5,plot_bgcolor='#F2DFCE',paper_bgcolor='#F2DFCE',xaxis_title="Date",yaxis_title=yaxis_title)
return fig
external_stylesheets = [dbc.themes.BOOTSTRAP]
Page Header and Form
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'World Covid-19 Dashboard'
colors = {
'background': '#111111',
'bodyColor':'#F2DFCE',
'text': '#7FDBFF'
}
def get_page_heading_style():
return {'backgroundColor': colors['background']}
def get_page_heading_title():
return html.H1(children='World COVID-19 Dashboard',
style={
'textAlign': 'center',
'color': colors['text']
})
def get_page_heading_subtitle():
return html.Div(children='Visualize Covid-19 data generated from sources all over the world.',
style={
'textAlign':'center',
'color':colors['text']
})
def generate_page_header():
main_header = dbc.Row(
[
dbc.Col(get_page_heading_title(),md=12)
],
align="center",
style=get_page_heading_style()
)
subtitle_header = dbc.Row(
[
dbc.Col(get_page_heading_subtitle(),md=12)
],
align="center",
style=get_page_heading_style()
)
header = (main_header,subtitle_header)
return header
Select Country Dropdown
def get_country_list():
return covid_conf_ts['Country/Region'].unique()
def create_dropdown_list(cntry_list):
dropdown_list = []
for cntry in sorted(cntry_list):
tmp_dict = {'label':cntry,'value':cntry}
dropdown_list.append(tmp_dict)
return dropdown_list
def get_country_dropdown(id):
return html.Div([
html.Label('Select Country'),
dcc.Dropdown(id='my-id'+str(id),
options=create_dropdown_list(get_country_list()),
value='US'
),
html.Div(id='my-div'+str(id))
])
Graph Container For Dash
def graph1():
return dcc.Graph(id='graph1',figure=fig_world_trend('US'))
Generate CARDS for Overall Numbers
def generate_card_content(card_header,card_value,overall_value):
card_head_style = {'textAlign':'center','fontSize':'150%'}
card_body_style = {'textAlign':'center','fontSize':'200%'}
card_header = dbc.CardHeader(card_header,style=card_head_style)
card_body = dbc.CardBody(
[
html.H5(f"{int(card_value):,}", className="card-title",style=card_body_style),
html.P(
"Worlwide: {:,}".format(overall_value),
className="card-text",style={'textAlign':'center'}
),
]
)
card = [card_header,card_body]
return card
def generate_cards(cntry='US'):
conf_cntry_total = get_cntry_total(covid_conf_ts,cntry)
dead_cntry_total = get_cntry_total(covid_dead_ts,cntry)
recv_cntry_total = conf_cntry_total - dead_cntry_total
cards = html.Div(
[
dbc.Row(
[
dbc.Col(dbc.Card(generate_card_content("Recovered",recv_cntry_total,recv_overall_total), color="success", inverse=True),md=dict(size=2,offset=3)),
dbc.Col(dbc.Card(generate_card_content("Confirmed",conf_cntry_total,conf_overall_total), color="warning", inverse=True),md=dict(size=2)),
dbc.Col(dbc.Card(generate_card_content("Dead",dead_cntry_total,dead_overall_total),color="dark", inverse=True),md=dict(size=2)),
],
className="mb-4",
),
],id='card1'
)
return cards
DASH Slider for Moving Average Window
def get_slider():
return html.Div([
dcc.Slider(
id='my-slider',
min=1,
max=15,
step=None,
marks={
1: '1',
3: '3',
5: '5',
7: '1-Week',
14: 'Fortnight'
},
value=3,
),
html.Div([html.Label('Select Moving Average Window')],id='my-div'+str(id),style={'textAlign':'center'})
])
Generate APP layout
def generate_layout():
page_header = generate_page_header()
layout = dbc.Container(
[
page_header[0],
page_header[1],
html.Hr(),
generate_cards(),
html.Hr(),
dbc.Row(
[
dbc.Col(get_country_dropdown(id=1),md=dict(size=4,offset=4))
]
),
dbc.Row(
[
dbc.Col(graph1(),md=dict(size=6,offset=3))
],
align="center",
),
dbc.Row(
[
dbc.Col(get_slider(),md=dict(size=4,offset=4))
]
),
],fluid=True,style={'backgroundColor': colors['bodyColor']}
)
return layout
app.layout = generate_layout()
Assign DASH Callbacks
@app.callback(
[Output(component_id='graph1',component_property='figure'), #line chart
Output(component_id='card1',component_property='children')], #overall card numbers
[Input(component_id='my-id1',component_property='value'), #dropdown
Input(component_id='my-slider',component_property='value')] #slider
)
def update_output_div(input_value1,input_value2):
return fig_world_trend(input_value1,input_value2),generate_cards(input_value1)
RUN the app server
if __name__ == '__main__':
app.run_server(debug=False)
Dash is running on http://127.0.0.1:8050/
* Serving Flask app "__main__" (lazy loading)
* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.
* Debug mode: off
* Running on http://127.0.0.1:8050/ (Press CTRL+C to quit)
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