PyCafe - Vizro - status page dashboard testing

app.py
dashboard_graph_data.pkl
distribution.pkl
requirements.txt
sp_data.pkl
app.py
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import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots

import vizro.models as vm
from vizro import Vizro
from vizro.models.types import capture

df = pd.read_pickle('dashboard_graph_data.pkl')
df2 = pd.read_pickle('distribution.pkl')

def build_hierarchical_dataframe(df, levels, name, cnt_column='count', pct_column='percentage', color_column=None):
    """
    Build a hierarchy of levels for Sunburst or Treemap charts.

    Levels are given starting from the bottom to the top of the hierarchy,
    i.e., the last level corresponds to the root.
    """
    df_list = []
    for i, level in enumerate(levels):
        df_tree = pd.DataFrame(columns=['id', 'parent', 'cnt', 'pct', 'color'])
        dfg = df.groupby(levels[i:]).sum()
        dfg = dfg.reset_index()
        df_tree['id'] = dfg[level].copy()
        if i < len(levels) - 1:
            df_tree['parent'] = dfg[levels[i + 1]].copy()
        else:
            df_tree['parent'] = 'total'
        df_tree['cnt'] = dfg[cnt_column]
        df_tree['pct'] = dfg[pct_column]
        if color_column:
            df_tree['color'] = dfg[color_column]
        else:
            df_tree['color'] = df_tree['pct'] * 1
        df_list.append(df_tree)
    total = pd.DataFrame([{
        'id': 'total', 
        'parent': '', 
        'cnt': df[cnt_column].sum(),
        'pct': 1.0,
        'color': 1,
    }])
    df_list.append(total)
    df_res = pd.concat(df_list, ignore_index=True)
    df_res['name'] = name
    return df_res

df_territory = build_hierarchical_dataframe(df2, ['country', 'territory'], 'territory')
df_industry = build_hierarchical_dataframe(df2, ['industry', 'industry_group'], 'industry')

df_distribution = pd.concat([df_territory, df_industry])

@capture("graph")
def create_graph(data_frame):
    """
    Create a Plotly figure from a unified DataFrame with specified colors for each platform.
    """
    # Define a color mapping for platforms
    platform_colors = {
        'AWS': 'blue',
        'Azure': 'red',
        'GCP': 'green',
        'Other': 'gray'
    }

    fig = go.Figure()

    # Loop through each platform and add a trace with its specified color
    for platform in data_frame['platform'].unique():
        platform_data = data_frame[data_frame['platform'] == platform]
        color = platform_colors.get(platform, 'black')  # Default to black if the platform is not in the mapping
        fig.add_trace(go.Scatter(
            x=platform_data['timestamp'],
            y=platform_data['count'],
            mode='lines',
            name=platform,
            hovertext=platform_data['hovertext'],
            hoverinfo='text',
            line=dict(color=color)
        ))

    fig.update_layout(
        title='Active Reports Over Time',
        xaxis=dict(
            title='Time',
            rangeslider=dict(visible=True),
            type='date'
        ),
        yaxis=dict(
            title='Reports',
            fixedrange=False
        ),
        legend=dict(
            orientation="h",
            yanchor="bottom",
            y=1.02,
            xanchor="right",
            x=1
        ),
        width=1200,
        height=700
    )
    return fig

@capture("graph")
def create_sunburst_chart(data_frame, title):
    """
    Create a nested pie chart using Plotly subplots.
    """
    df_territory = data_frame.query('name=="territory"')
    df_industry = data_frame.query('name=="industry"')

    fig = make_subplots(1, 2, specs=[[{"type": "domain"}, {"type": "domain"}]])

    fig.add_trace(go.Sunburst(
        labels=df_territory['id'],
        parents=df_territory['parent'],
        values=df_territory['cnt'],
        branchvalues='total',
        marker=dict(colors=df_territory['color'], colorscale='thermal'),
        name='',
        customdata=df_territory['pct'],
        texttemplate='%{label}<br>%{customdata:.1%}',
        hovertemplate='<b>%{label}</b><br>Count: %{value}<br>Percent: %{color:.2%}',
        maxdepth=3
    ), 1, 1)

    fig.add_trace(go.Sunburst(
        labels=df_industry['id'],
        parents=df_industry['parent'],
        values=df_industry['cnt'],
        branchvalues='total',
        marker=dict(colors=df_industry['color'], colorscale='thermal'),
        name='',
        customdata=df_industry['pct'],
        texttemplate='%{label}<br>%{customdata:.1%}',
        hovertemplate='<b>%{label}</b><br>Count: %{value}<br>Percent: %{color:.2%}',
        maxdepth=3
    ), 1, 2)

    fig.update_layout(
        title=title,
        width=1000,
        height=600,
        margin=dict(t=10, b=10, r=10, l=10),
    #     uniformtext=dict(minsize=10, mode='show'),
    #     uirevision=True
    )
    return fig

page_0 = vm.Page(
    title="Distribution Insights",
    components=[
        vm.Graph(
            id="sunburst",
            figure=create_sunburst_chart(
                data_frame=df_distribution,
                title='Status Pages Distribution by Territory and Industry'
            ),
        ),
    ]
)

page_1 = vm.Page(
    title="Active Report Count",
    components=[
        vm.Graph(
            id="active reports",
            figure=create_graph(data_frame=df),
        ),
    ]
)

dashboard = vm.Dashboard(pages=[page_0, page_1])

Vizro().build(dashboard).run()
Py.Cafe

sp_dashboard

status page dashboard testing
