Hea 698/pipeline status dashboard

apps/viz/apps.py

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+# viz/apps.py
+from django.apps import AppConfig
+from django.utils.translation import gettext_lazy as _
+
+
+class VizConfig(AppConfig):
+    default_auto_field = "django.db.models.BigAutoField"
+    name = "viz"
+    verbose_name = _("viz")

apps/viz/dash/inventory_dashboard/app.py

@@ -0,0 +1,317 @@
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from dash import Input, Output, dcc, html
+
+from ...dash_wrapper import SecureDjangoDash
+from .functions import (
+    get_bss_corrections,
+    get_livelihood_activity_dataframe,
+    get_livelihood_zone_baseline,
+    get_wealthcharactestics,
+)
+
+app = SecureDjangoDash("bss_inventory", suppress_callback_exceptions=True)
+app.title = "BSS Inventory"
+
+
+app.layout = html.Div(
+    [
+        html.Div([html.H1("BSS Inventories", style={"textAlign": "center", "color": "#2c3e50"})]),
+        html.Div(
+            [
+                html.Div(
+                    [
+                        html.Label("Select Country:", style={"fontWeight": "bold"}),
+                        dcc.Dropdown(
+                            id="country-dropdown",
+                            # Options will be loaded dynamically in callback
+                            options=[],
+                            value=None,
+                            clearable=True,
+                            placeholder="Select a country (or leave blank for all)",
+                        ),
+                    ],
+                    style={"width": "30%", "display": "inline-block", "marginRight": "20px"},
+                ),
+                html.Div(
+                    [
+                        html.Label("Select Livelihood Zone(s):", style={"fontWeight": "bold"}),
+                        dcc.Dropdown(id="zone-dropdown", multi=True),
+                    ],
+                    style={"width": "65%", "display": "inline-block"},
+                ),
+            ],
+            style={"margin": "20px", "padding": "20px", "backgroundColor": "#f8f9fa", "borderRadius": "10px"},
+        ),
+        html.Div(
+            [dcc.Loading(id="loading-overview", type="circle", children=html.Div(id="overview-content"))],
+            style={"padding": "20px"},
+        ),
+        # Hidden div to trigger initial loading
+        html.Div(id="initial-load-trigger", style={"display": "none"}),
+    ],
+    style={"fontFamily": "Arial, sans-serif"},
+)
+
+
+@app.callback(
+    Output("country-dropdown", "options"),
+    Output("country-dropdown", "value"),
+    Input("initial-load-trigger", "children"),
+)
+def initialize_country_dropdown(_):
+    """Initialize country dropdown options on first load."""
+    try:
+        baseline_df = get_livelihood_zone_baseline()
+        countries = sorted(baseline_df["country"].unique().tolist()) if not baseline_df.empty else []
+        options = [{"label": country, "value": country} for country in countries]
+        default_value = countries[0] if countries else None
+        return options, default_value
+    except Exception as e:
+        # Handle gracefully in case of connection issues
+        print(f"Error loading baseline data: {e}")
+        return [], None
+
+
+@app.callback(Output("zone-dropdown", "options"), Output("zone-dropdown", "value"), Input("country-dropdown", "value"))
+def update_livelihood_zone_dropdown(selected_country):
+    """Update zone dropdown based on selected country."""
+    if not selected_country:
+        return [], []
+
+    try:
+        baseline_df = get_livelihood_zone_baseline()
+        zones = sorted(baseline_df[baseline_df["country"] == selected_country]["zone_code"].unique())
+        options = [{"label": zone, "value": zone} for zone in zones]
+        return options, zones
+    except Exception as e:
+        print(f"Error loading zone data: {e}")
+        return [], []
+
+
+@app.callback(
+    Output("overview-content", "children"), Input("country-dropdown", "value"), Input("zone-dropdown", "value")
+)
+def update_kpi_content(selected_country, selected_zone):
+    """Update main content based on selected filters."""
+    try:
+        # Load all required data fresh each time
+        baseline_df = get_livelihood_zone_baseline()
+        livelihood_activity_df = get_livelihood_activity_dataframe()
+        corrections_df = get_bss_corrections()
+        wealthcharactestics_df = get_wealthcharactestics()
+
+        title_segment = selected_country if selected_country else "All Countries"
+
+        if selected_country:
+            filtered_baseline_df = baseline_df[baseline_df["country"] == selected_country].copy()
+            if not livelihood_activity_df.empty:
+                filtered_activity_df = livelihood_activity_df[
+                    livelihood_activity_df["country"] == selected_country
+                ].copy()
+            else:
+                filtered_activity_df = pd.DataFrame()
+            filtered_corrections_df = pd.DataFrame()
+            if not corrections_df.empty:
+                filtered_corrections_df = corrections_df[corrections_df["country"] == selected_country].copy()
+
+            most_frequent_wc = ""
+            if not wealthcharactestics_df.empty:
+                filtered_wc = wealthcharactestics_df[wealthcharactestics_df["country"] == selected_country].copy()
+                counts = filtered_wc["wealth_characteristic"].value_counts()
+                # Drop "household size" as it is in almost all bsses
+                counts = counts.drop("household size", errors="ignore")
+                if not counts.empty:
+                    most_frequent_wc = counts.idxmax()
+
+        else:
+            filtered_baseline_df = baseline_df.copy()
+            filtered_activity_df = livelihood_activity_df.copy()
+            filtered_corrections_df = corrections_df.copy()
+            most_frequent_wc = ""
+            if not wealthcharactestics_df.empty:
+                counts = wealthcharactestics_df["wealth_characteristic"].value_counts()
+                # Drop "household size" as it is in almost all bsses
+                counts = counts.drop("household size", errors="ignore")
+                if not counts.empty:
+                    most_frequent_wc = counts.idxmax()
+
+        if filtered_baseline_df.empty:
+            return html.Div(f"No data available for {title_segment}.", style={"padding": "20px"})
+
+        return create_kpi_layout(filtered_baseline_df, filtered_activity_df, filtered_corrections_df, most_frequent_wc)
+
+    except Exception as e:
+        print(f"Error updating content: {e}")
+        return html.Div(
+            "Error loading data. Please try again later.",
+            style={"padding": "20px", "color": "red", "textAlign": "center"},
+        )
+
+
+def create_livelihood_pie_chart(df):
+    if df.empty:
+        return go.Figure().update_layout(title_text="No Livelihood Category Data")
+    livelihood_counts = df["main_livelihood_category"].value_counts()
+    color_map = {
+        "Agricultural": "#096640",  # brand green
+        "Agropastoral": "#0B7A4A",  # slightly brighter
+        "Fishing": "#0E8E54",  # lighter green
+        "Irrigation": "#12A35F",  # medium green
+        "Pastoral": "#27B96B",  # fresh green
+        "Peri-Urban": "#52CC85",  # soft green
+        "Urban": "#7FE09F",  # lightest green
+    }
+    fig = px.pie(
+        values=livelihood_counts.values,
+        names=livelihood_counts.index,
+        title="Distribution of Main Livelihood Categories",
+        hole=0.4,
+        color=livelihood_counts.index,
+        color_discrete_map=color_map,
+    )
+    fig.update_traces(textposition="inside", textinfo="percent+label")
+    fig.update_layout(legend_title_text="Category", uniformtext_minsize=12, uniformtext_mode="hide")
+    return fig
+
+
+def create_organization_treemap(df):
+    if df.empty:
+        return go.Figure().update_layout(title_text="No Source Organization Data")
+    org_counts = df["source_organization"].value_counts().reset_index()
+    org_counts.columns = ["source_organization", "count"]
+    fig = px.treemap(
+        org_counts,
+        path=[px.Constant("All Organizations"), "source_organization"],
+        values="count",
+        title="Data Contribution by Source Organization",
+        color="count",
+        color_continuous_scale="Blues",
+    )
+    fig.update_traces(textinfo="label+value")
+    fig.update_layout(margin=dict(t=50, l=25, r=25, b=25))
+    return fig
+
+
+def create_strategy_barchart(activity_df):
+    """
+    Creates a bar chart showing the count of livelihood activities by strategy type.
+    """
+    if activity_df.empty or "strategy_type" not in activity_df.columns:
+        return go.Figure().update_layout(title_text="No Livelihood Strategy Data")
+
+    strategy_counts = activity_df["strategy_type"].value_counts().reset_index()
+    strategy_counts.columns = ["strategy_type", "count"]
+
+    fig = px.bar(
+        strategy_counts,
+        x="strategy_type",
+        y="count",
+        title="Livelihood Activities by Strategy Type",
+        labels={"strategy_type": "Strategy Type", "count": "Number of Activities"},
+        color="strategy_type",
+        text_auto=True,
+    )
+    fig.update_layout(xaxis_title=None, yaxis_title="Number of Activities", showlegend=False)
+    fig.update_traces(textposition="outside")
+    return fig
+
+
+def get_livelihood_activity_kpis(activity_df):
+    if activity_df.empty:
+        return 0, 0
+    counts = activity_df["data_level"].value_counts().to_dict()
+    return counts.get("community", 0), counts.get("baseline", 0)
+
+
+def create_strategy_sunburst_chart(activity_df):
+    """
+    Creates a sunburst chart for livelihood strategy types.
+    """
+    if activity_df.empty or "strategy_type" not in activity_df.columns:
+        return go.Figure().update_layout(title_text="No Livelihood Activity Data Available")
+
+    strategy_counts = activity_df.groupby(["data_level", "strategy_type"]).size().reset_index(name="count")
+    fig = px.sunburst(
+        strategy_counts,
+        path=["data_level", "strategy_type"],
+        values="count",
+        title="Livelihood Activities by Strategy Type",
+        color="data_level",
+        color_discrete_map={"community": "#2980b9", "baseline": "#8e44ad", "(?)": "#7f8c8d"},
+    )
+    fig.update_traces(textinfo="label+percent parent", insidetextorientation="radial")
+    fig.update_layout(margin=dict(t=50, l=25, r=25, b=25))
+    return fig
+
+
+def create_kpi_layout(filtered_baseline_df, filtered_activity_df, filtered_corrections_df, most_frequent_wc):
+    """
+    All KPI cards and charts into a single layout component.
+    """
+
+    total_bsses = len(filtered_baseline_df)
+    community_count, baseline_count = get_livelihood_activity_kpis(filtered_activity_df)
+    total_corrections = len(filtered_corrections_df)
+    return html.Div(
+        [
+            html.Div(
+                [
+                    html.Div(
+                        [html.H3(f"{total_bsses}", style={"color": "#2ECC71"}), html.P("Total BSSes loaded")],
+                        className="summary-card",
+                    ),
+                    html.Div(
+                        [
+                            html.H3("Livelihood Activity Data", style={"color": "#3498db"}),
+                            html.Div(
+                                [
+                                    html.Div([html.H4(community_count), html.P("Community")], className="sub-kpi"),
+                                    html.Div([html.H4(baseline_count), html.P("Baseline")], className="sub-kpi"),
+                                ],
+                                style={"display": "flex", "justifyContent": "space-around", "marginTop": "10px"},
+                            ),
+                        ],
+                        className="summary-card",
+                    ),
+                    html.Div(
+                        [html.H3(f"{total_corrections}", style={"color": "#9b59b6"}), html.P("Corrections")],
+                        className="summary-card",
+                    ),
+                    html.Div(
+                        [
+                            html.H3("Most Frequent Wealth Characterstics", style={"color": "#f39c12"}),
+                            html.P(f"{most_frequent_wc}"),
+                        ],
+                        className="summary-card",
+                    ),
+                ],
+                className="kpi-card-container",
+            ),
+            html.Div(
+                [
+                    html.Div(
+                        [dcc.Graph(figure=create_livelihood_pie_chart(filtered_baseline_df))],
+                        style={"width": "49%", "display": "inline-block", "verticalAlign": "top"},
+                    ),
+                    html.Div(
+                        [dcc.Graph(figure=create_organization_treemap(filtered_baseline_df))],
+                        style={"width": "49%", "display": "inline-block", "verticalAlign": "top"},
+                    ),
+                ],
+                style={"marginTop": "30px"},
+            ),
+            html.Div(
+                [
+                    html.Div(
+                        [dcc.Graph(figure=create_strategy_sunburst_chart(filtered_activity_df))],
+                    ),
+                    html.Div(
+                        [dcc.Graph(figure=create_strategy_barchart(filtered_activity_df))],
+                    ),
+                ],
+                style={"marginTop": "30px"},
+            ),
+        ]
+    )