created plotly dash dashboard

apps/geo.py

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+from app import *

apps/upload_data.py

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+import base64
+import io
+from app import *
+
+def load_data(contents):
+    content_type, content_string = contents.split(',')
+    decoded = base64.b64decode(content_string)
+    try:
+        if 'csv' in content_type:
+            # Assume that the user uploaded a CSV file
+            df = pd.read_csv(io.StringIO(decoded.decode('utf-8')))
+            df.to_csv('data/test0.csv')
+        elif 'xls' in content_type:
+            # Assume that the user uploaded an excel file
+            df = pd.read_excel(io.BytesIO(decoded))
+        return('file loaded')
+    except Exception as e:
+        print(e)
+        return('There was an error processing this file.')
+
+layout = html.Div([
+    html.H1('Upload Data'),
+    dcc.Upload(
+    id='upload-data',
+    children=html.Div([
+        'Drag or ',
+        html.A('Select Files')
+    ]),
+    style={
+        'width': '100%',
+        'height': '60px',
+        'lineHeight': '60px',
+        'borderWidth': '1px',
+        'borderStyle': 'dashed',
+        'borderRadius': '5px',
+        'textAlign': 'center',
+        'margin': '10px'}),
+    html.Div(id='output-data-upload'),
+    ])
+
+@app.callback(Output('output-data-upload', 'children'),
+              [Input('upload-data', 'contents')])
+def update_output(contents):
+    if contents is not None:
+        children = load_data(contents)
+        return(children)

apps/volume.py

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+import plotly.express as px
+from app import *
+
+# data
+df=pd.read_csv('data/df0.csv',parse_dates=['Date'])
+# marks
+index_list=list(range(len(df.loc[:,"Date"].dt.strftime('%Y%m').unique())))
+date_list=df.loc[:,"Date"].dt.strftime('%Y%m').unique()
+
+colors = {
+    'background': '#111111',
+    'text': '#7FDBFF'}
+
+layout = html.Div([
+    html.H1('Volume and CTN'),
+
+    dcc.Graph(id='cubic-with-slider',style={'backgroundColor':'black'}),
+
+    dcc.Graph(id='ctn-with-slider'),
+
+    dcc.RangeSlider(
+        id='month-slider',
+        min=index_list[0],
+        max=index_list[-1],
+        step=1,
+        marks=dict(zip(index_list,date_list)),
+        value=[index_list[list(date_list).index('202005')],index_list[-1]]),
+    ])
+
+@app.callback(
+    Output('cubic-with-slider', 'figure'),
+    Output('ctn-with-slider', 'figure'),
+    [Input('month-slider', 'value')])
+def update_figure(selected_month):
+    start_time=date_list[selected_month[0]]
+    end_time=date_list[selected_month[1]]
+    filtered_df = df.loc[df.loc[:,'Date'] >= pd.to_datetime(start_time,format='%Y%m')]
+    filtered_df = filtered_df.loc[filtered_df.loc[:,'Date'] <= pd.to_datetime(end_time,format='%Y%m')]
+    fig_cubic = px.bar(filtered_df, x="Date", y="Cubic",color="Cubic",hover_data=['Daily total cubic','Marking'])
+    fig_ctn = px.bar(filtered_df, x="Date", y="CTN",color="CTN",hover_data=['Daily total CTN','Marking'])
+
+    fig_cubic.update_layout(
+        plot_bgcolor=colors['background'],
+        paper_bgcolor=colors['background'],
+        font_color=colors['text'])
+
+    fig_ctn.update_layout(
+        plot_bgcolor=colors['background'],
+        paper_bgcolor=colors['background'],
+        font_color=colors['text'])
+    return(fig_cubic,fig_ctn)