Add new dash plotly workshop

plotly-dash/analyse.py

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+from dash import Dash, dcc, html, Input, Output
+import plotly.express as px
+
+import pandas as pd
+from os.path import join
+import plotly.graph_objects as go
+
+data_folder = "data/enershelf_example"
+
+df = pd.read_csv(join(data_folder,"clinic_loads.csv"), index_col=0)
+
+aggregate = df.sum()
+
+
+fig = go.Figure()
+fig.add_trace(
+    go.Scatter(
+        x=df.index,
+        y=df["clinic_only"],
+        name="clinic_only",
+        marker=dict(
+            color='rgba(246, 78, 139, 0.6)',
+            line=dict(color='rgba(246, 78, 139, 1.0)', width=3)
+        ),
+        stackgroup="one" # this property is used to group some timeseries together
+    )
+)
+fig.add_trace(
+    go.Scatter(
+        x=df.index,
+        y=df["hh_only"],
+        name="hh_only",
+        stackgroup="one" # this then belong to the same stack group as the above line
+    )
+)
+fig.add_trace(
+    go.Scatter(
+        x=df.index,
+        y=df["combi"],
+        name="combi",
+    ) # this line does not belong to any stackgroup
+)
+
+
+app = Dash(__name__)
+
+app.layout = html.Div([
+    dcc.Graph(id='graph-with-slider', figure=fig),
+    dcc.Dropdown(id="select", multi=True, options=[{"label": col, "value": col} for col in df.columns]),
+    # dcc.Slider(
+    #     df['year'].min(),
+    #     df['year'].max(),
+    #     step=None,
+    #     value=df['year'].min(),
+    #     marks={str(year): str(year) for year in df['year'].unique()},
+    #     id='year-slider'
+    # )
+] + [
+    html.Div([html.Label(col, htmlFor=f"{col}-value", style={"color":"blue"}), dcc.Input(id=f"{col}-value", value=aggregate[col])])
+    for col in df.columns
+]
+
+)
+
+
+@app.callback(
+    Output('graph-with-slider', 'figure'),
+    Input('select', 'value'))
+def update_figure(selected_columns):
+    print(selected_columns)
+
+    fig = go.Figure()
+    for col_name in df.columns:
+        if col_name in selected_columns:
+            fig.add_trace(
+                go.Scatter(
+                    x=df.index,
+                    y=df[col_name],
+                    name=col_name,
+                )
+            )
+
+    return fig
+
+
+
+if __name__ == '__main__':
+    app.run_server(debug=True)