mirror of
https://gitlab.com/CIEFWorldwideSdnBhd/cief-dashboard.git
synced 2026-08-19 04:24:13 +00:00
shangqian22
116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
from app import *
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# layout
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layout = html.Div([
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html.H1('Summery data'),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-volume_day'), label="Day"),
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dbc.Tab(dcc.Graph(id='output-volume_month'), label="Month"),
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dbc.Tab(dcc.Graph(id='output-volume_year'), label="Year"),
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dbc.Tab(dcc.Graph(id='output-volume_quarter'), label="Quarter"),
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dbc.Tab(dcc.Graph(id='output-volume_week'), label="Week"),
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dbc.Tab(dcc.Graph(id='output-volume_weekday'), label="Weekday")
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]),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-amount_day'), label="Day"),
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dbc.Tab(dcc.Graph(id='output-amount_month'), label="Month"),
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dbc.Tab(dcc.Graph(id='output-amount_year'), label="Year"),
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dbc.Tab(dcc.Graph(id='output-amount_quarter'), label="Quarter"),
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dbc.Tab(dcc.Graph(id='output-amount_week'), label="Week"),
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dbc.Tab(dcc.Graph(id='output-amount_weekday'), label="Weekday")
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]),
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dbc.Tabs([
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dbc.Tab(dcc.Graph(id='output-booking_rate'), label="Booking rate"),
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dbc.Tab(dcc.Graph(id='output-n_transfer'), label="Number of transfer"),
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dbc.Tab(dcc.Graph(id='output-ctn'), label="CTN"),
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dbc.Tab(dcc.Graph(id='output-delivery'), label="Delivery"),
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]),
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dbc.Row([
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dcc.Graph(id='output-place')
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])
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])
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@app.callback(
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[Output('output-booking_rate', 'figure'),
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Output('output-n_transfer', 'figure'),
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Output('output-ctn', 'figure'),
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Output('output-delivery', 'figure'),
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Output('output-place', 'figure'),
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Output('output-volume_day', 'figure'),
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Output('output-volume_month', 'figure'),
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Output('output-volume_year', 'figure'),
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Output('output-volume_quarter', 'figure'),
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Output('output-volume_week', 'figure'),
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Output('output-volume_weekday', 'figure'),
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Output('output-amount_day', 'figure'),
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Output('output-amount_month', 'figure'),
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Output('output-amount_year', 'figure'),
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Output('output-amount_quarter', 'figure'),
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Output('output-amount_week', 'figure'),
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Output('output-amount_weekday', 'figure')],
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Input('data-summery', 'data'))
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def update_figure(data):
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cbms=data.pop('cbms')
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x1_x2s=data.pop('x1_x2s')
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to_df(data)
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# cbm
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to_df(cbms)
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fig_cbms=[]
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for i in range(len(cbms)):
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fig_cbms.append(px.line(cbms[i], x='Date', y='CBM', title='Period CBM'))
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update_theme(fig_cbms[i])
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# x1 x2
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to_df(x1_x2s)
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fig_x1_x2s=[]
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for i in range(len(x1_x2s)):
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fig_x1_x2s.append(px.line(x1_x2s[i], x='Date', y='value', color='variable', title='Period Number of transfer'))
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fig_x1_x2s[i].update_yaxes(title_text='RM')
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update_theme(fig_x1_x2s[i])
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# booking rate
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booking_rate=data['booking_rate']
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fig_rate=px.line(booking_rate, x='Date',y='Booking rate', title='Daily average Booking Rate')
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update_theme(fig_rate)
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# number of transfer
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n_transfer=data['n_transfer']
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fig_count=px.line(n_transfer, x='Date',y='Number of transfer', title='Monthly number of transfer')
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update_theme(fig_count)
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# ctn
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ctn=data['ctn']
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fig_ctn=px.line(ctn, x='Date',y='CTN', title='Monthly CTN')
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update_theme(fig_ctn)
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# place
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place=data['place']
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fig_place = px.scatter_mapbox(
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place, lat="Latitude", lon="Longitude",
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title='CBM in Malaysia',
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hover_name="CBM by place", hover_data=["Place name","State name",'CBM by place'],
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size='CBM by place',color='State name',
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color_discrete_sequence=px.colors.diverging.Portland,
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size_max=80, zoom=6,
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center={'lat':3.4339, 'lon':102.1543}
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)
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fig_place.update_layout(
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mapbox_style="stamen-terrain",
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margin={"r":0,"t":0,"l":0,"b":0},
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)
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update_theme(fig_place)
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# delivery time
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delivery=data['delivery']
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fig_delivery=px.line(delivery, x="Date",y="value",color="variable")
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update_theme(fig_delivery)
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# save
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figs=[fig_rate, fig_count, fig_ctn, fig_delivery, fig_place]
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figs=figs+fig_cbms+fig_x1_x2s
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return(figs)
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