mirror of
https://gitlab.com/CIEFWorldwideSdnBhd/cief-dashboard.git
synced 2026-08-19 04:24:13 +00:00
shangqian22
87 lines
4.0 KiB
Python
87 lines
4.0 KiB
Python
from app import *
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def plot(df, log=True):
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total=df.loc[:, ['Date', 'Total active case', 'Total recovered', 'Total death', 'Total case']]
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total=pd.melt(total, 'Date')
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fig_total=px.line(total, x='Date', y='value', color='variable', log_y=log)
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fig_total.add_trace(go.Scatter(
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x=df['Date'], y=df['New active case'],
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mode='markers', name='New active case'))
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fig_total.add_trace(go.Scatter(
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x=df['Date'], y=df['New recovered'],
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mode='lines+markers', name='New recovered'))
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fig_total.add_trace(go.Scatter(
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x=df['Date'], y=df['New death'],
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mode='markers', name='New death'))
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fig_total.add_trace(go.Scatter(
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x=df['Date'], y=df['New case'],
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mode='lines+markers', name='New case'))
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update_theme(fig_total)
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percentage=df.loc[:, ['Date', 'Active case percentage', 'Recovery percentage', 'Death percentage', 'Active case increase rate', 'Recovery increase rate', 'Death increase rate', 'New case increase rate']]
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percentage=pd.melt(percentage, 'Date')
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fig_percentage=px.line(percentage, x='Date', y='value', color='variable', log_y=log)
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update_theme(fig_percentage)
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fig_percentage.update_yaxes(tickformat='.2%')
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r0=df.loc[:, ['Date', 'R0', 'R0 in 3 days', 'R0 in 7 days']]
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r0=pd.melt(r0, 'Date')
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fig_r0=px.line(r0, x='Date', y='value', color='variable', log_y=log)
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update_theme(fig_r0)
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return(fig_total, fig_percentage, fig_r0)
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# layout
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layout = html.Div([
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dbc.Row([
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dbc.Col([
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html.H2('Covid-19 Analysis (Malaysia)'),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-malaysia_total'), label="Value"),
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dbc.Tab(dcc.Graph(id='output-malaysia_total_log'), label="Log"),
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]),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-malaysia_percentage'), label="Value"),
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dbc.Tab(dcc.Graph(id='output-malaysia_percentage_log'), label="Log"),
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]),
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dcc.Graph(id='output-malaysia_r0')
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]),
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dbc.Col([
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html.H2('Covid-19 Analysis (Worldwide)'),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-world_wide_total'), label="Value"),
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dbc.Tab(dcc.Graph(id='output-world_wide_total_log'), label="Log"),
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]),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-world_wide_percentage'), label="Value"),
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dbc.Tab(dcc.Graph(id='output-world_wide_percentage_log'), label="Log"),
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]),
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dcc.Graph(id='output-world_wide_r0')
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])
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])
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])
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@app.callback(
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[Output('output-malaysia_total', 'figure'),
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Output('output-malaysia_total_log', 'figure'),
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Output('output-malaysia_percentage', 'figure'),
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Output('output-malaysia_percentage_log', 'figure'),
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Output('output-malaysia_r0', 'figure'),
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Output('output-world_wide_total', 'figure'),
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Output('output-world_wide_total_log', 'figure'),
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Output('output-world_wide_percentage', 'figure'),
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Output('output-world_wide_percentage_log', 'figure'),
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Output('output-world_wide_r0', 'figure')],
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Input('data', 'data'))
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def display_page(data):
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malaysia = pd.read_json(data['covid_malaysia'])
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world_wide = pd.read_json(data['covid_world_wide'])
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fig_malaysia_total, fig_malaysia_percentage, fig_malaysia_r0=plot(malaysia, log=False)
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fig_malaysia_total_log, fig_malaysia_percentage_log, fig_malaysia_r0_log=plot(malaysia, log=True)
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fig_world_wide_total, fig_world_wide_percentage, fig_world_wide_r0=plot(world_wide, log=False)
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fig_world_wide_total_log, fig_world_wide_percentage_log, fig_world_wide_r0_log=plot(world_wide, log=True)
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return(fig_malaysia_total, fig_malaysia_total_log, fig_malaysia_percentage, fig_malaysia_percentage_log, fig_malaysia_r0, fig_world_wide_total, fig_world_wide_total_log, fig_world_wide_percentage, fig_world_wide_percentage_log, fig_world_wide_r0)
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