Hea 592/inventory 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")
+
+    def ready(self):
+        import viz.dash.inventory_dashboard.app  # noqa

apps/viz/dash/inventory_dashboard/app.py

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+import dash_bootstrap_components as dbc
+import pandas as pd
+import plotly.express as px
+from dash import dash_table, dcc, html
+from dash.dependencies import Input, Output
+from django_plotly_dash import DjangoDash
+
+from .functions import clean_livelihood_data, clean_wealth_group_data
+
+# Unique countries and livelihood zones for dropdowns
+unique_countries = sorted(clean_livelihood_data["country_code"].dropna().unique())
+unique_zones = sorted(clean_livelihood_data["livelihood_zone_baseline_label"].dropna().unique())
+
+# Dash app
+app = DjangoDash("Inventory_dashboard", suppress_callback_exceptions=True, external_stylesheets=[dbc.themes.BOOTSTRAP])
+app.title = "HEA Dashboard"
+
+# Layout
+app.layout = html.Div(
+    [
+        html.H1("HEA Data Inventory Dashboard", style={"textAlign": "center"}),
+        html.Div(
+            [
+                html.Div(
+                    [
+                        dcc.Dropdown(
+                            id="country-dropdown",
+                            options=[{"label": country, "value": country} for country in unique_countries],
+                            placeholder=f"Select Country(s) (e.g., {unique_countries[0]})",
+                            multi=True,
+                        ),
+                    ],
+                    style={"flex": "1", "marginRight": "10px"},
+                ),
+                html.Div(
+                    [
+                        dcc.Dropdown(
+                            id="livelihood-zone-dropdown",
+                            options=[{"label": zone, "value": zone} for zone in unique_zones],
+                            placeholder=f"Select Livelihood Zone(s) (e.g., {unique_zones[0]})",
+                            multi=True,
+                        ),
+                    ],
+                    style={"flex": "1"},
+                ),
+            ],
+            style={
+                "display": "flex",
+                "width": "100%",
+                "justifyContent": "space-between",
+                "marginBottom": "20px",
+            },
+        ),
+        html.Div(
+            [
+                html.Div(
+                    dcc.Graph(id="wealth-chart"),
+                    style={"width": "30%", "display": "inline-block"},
+                ),
+                html.Div(
+                    dcc.Graph(id="livelihood-chart"),
+                    style={"width": "30%", "display": "inline-block"},
+                ),
+                html.Div(
+                    dcc.Graph(id="wealth-monthly-chart"),
+                    style={"width": "30%", "display": "inline-block"},
+                ),
+            ],
+        ),
+        html.Div(
+            [
+                html.H3("Data Table", style={"textAlign": "center"}),
+                dash_table.DataTable(
+                    id="data-table",
+                    columns=[
+                        {"name": "Livelihood Zone", "id": "livelihood_zone_baseline_label"},
+                        {"name": "Total Strategy Type Count", "id": "Strategy Type Count"},
+                        {"name": "Summary Wealth Characteristics", "id": "Summary Data"},
+                        {"name": "Community Wealth Characteristics", "id": "Community Data"},
+                    ],
+                    style_table={"overflowX": "auto"},
+                    style_cell={
+                        "textAlign": "left",
+                        "fontSize": "15px",  # Increase font size
+                        "padding": "10px",  # Add padding
+                    },
+                    style_header={
+                        "fontSize": "18px",  # Increase font size for header
+                        "fontWeight": "bold",  # Make header bold
+                        "textAlign": "center",
+                    },
+                    page_size=10,
+                ),
+            ],
+            className="inventory-filter inventory-filter-last",
+        ),
+    ],
+    className="div-wrapper control-panel-wrapper",
+)
+
+
+# Callbacks
+@app.callback(
+    [
+        Output("livelihood-zone-dropdown", "options"),
+        Output("wealth-chart", "figure"),
+        Output("livelihood-chart", "figure"),
+        Output("wealth-monthly-chart", "figure"),
+        Output("data-table", "data"),
+    ],
+    [Input("country-dropdown", "value"), Input("livelihood-zone-dropdown", "value")],
+)
+def update_charts(selected_countries, selected_zones):
+    # Handle multi-country selection
+    if selected_countries:
+        filtered_livelihood = clean_livelihood_data[clean_livelihood_data["country_code"].isin(selected_countries)]
+        filtered_wealth = clean_wealth_group_data[clean_wealth_group_data["country_code"].isin(selected_countries)]
+        filtered_zones = sorted(filtered_livelihood["livelihood_zone_baseline_label"].unique())
+    else:
+        filtered_livelihood = clean_livelihood_data
+        filtered_wealth = clean_wealth_group_data
+        filtered_zones = unique_zones
+
+    # Update options for livelihood zone dropdown
+    zone_options = [{"label": zone, "value": zone} for zone in filtered_zones]
+
+    # Filter data based on selected livelihood zones
+    if selected_zones:
+        filtered_livelihood = filtered_livelihood[
+            filtered_livelihood["livelihood_zone_baseline_label"].isin(selected_zones)
+        ]
+        filtered_wealth = filtered_wealth[filtered_wealth["livelihood_zone_baseline_label"].isin(selected_zones)]
+
+    # Group and aggregate Strategy Type Count
+    livelihood_grouped = (
+        filtered_livelihood.groupby(["livelihood_zone_baseline_label", "strategy_type_label"])
+        .size()
+        .reset_index(name="Strategy Type Count")
+    )
+    livelihood_summary = (
+        livelihood_grouped.groupby("livelihood_zone_baseline_label")["Strategy Type Count"].sum().reset_index()
+    )
+
+    # Group and pivot Wealth Characteristics Count
+    wealth_grouped = (
+        filtered_wealth.groupby(["livelihood_zone_baseline_label", "Record Type"])
+        .size()
+        .reset_index(name="Wealth Characteristics Count")
+    )
+    wealth_grouped_pivot = wealth_grouped.pivot_table(
+        index="livelihood_zone_baseline_label",
+        columns="Record Type",
+        values="Wealth Characteristics Count",
+        aggfunc="sum",
+        fill_value=0,
+    ).reset_index()
+
+    # Merge livelihood and wealth data
+    merged_data = pd.merge(livelihood_summary, wealth_grouped_pivot, on="livelihood_zone_baseline_label", how="left")
+
+    # Create charts
+    wealth_fig = px.bar(
+        wealth_grouped,
+        x="livelihood_zone_baseline_label",
+        y="Wealth Characteristics Count",
+        color="Record Type",
+        barmode="stack",
+        title="Wealth Characteristics by Type",
+        labels={
+            "livelihood_zone_baseline_label": "Livelihood Zone",
+        },
+    )
+
+    livelihood_fig = px.bar(
+        livelihood_grouped,
+        x="strategy_type_label",
+        y="Strategy Type Count",
+        color="livelihood_zone_baseline_label",
+        barmode="stack",
+        title="Strategy Types by Baseline",
+        labels={
+            "strategy_type_label": "Strategy Type",
+            "livelihood_zone_baseline_label": "Baseline Zone",
+        },
+    )
+
+    wealth_monthly_fig = px.bar(
+        filtered_wealth.groupby(["created_month", "Record Type"])
+        .size()
+        .reset_index(name="Wealth Characteristics Count"),
+        x="created_month",
+        y="Wealth Characteristics Count",
+        color="Record Type",
+        barmode="stack",
+        title="Wealth Characteristics by Month",
+        labels={
+            "created_month": "Month",
+        },
+    )
+
+    return zone_options, wealth_fig, livelihood_fig, wealth_monthly_fig, merged_data.to_dict("records")
+
+
+# Run the app
+if __name__ == "__main__":
+    app.run_server(debug=True)

apps/viz/dash/inventory_dashboard/functions.py

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+import pandas as pd
+import requests
+
+# API Endpoints
+LIVELIHOOD_STRATEGY_URL = "https://headev.fews.net/api/livelihoodstrategy/"
+WEALTH_GROUP_URL = "https://headev.fews.net/api/wealthgroupcharacteristicvalue/"
+LIVELIHOOD_ACTIVITY_URL = "https://headev.fews.net/api/livelihoodactivity/"
+
+
+def fetch_data(api_url):
+    """
+    Fetch data from the given API endpoint and return as a Pandas DataFrame.
+    """
+    try:
+        response = requests.get(api_url)
+        response.raise_for_status()
+        data = response.json()
+        return pd.DataFrame(data)
+    except Exception as e:
+        print(f"Error fetching data: {e}")
+        return pd.DataFrame()
+
+
+def prepare_livelihood_data(df):
+    """
+    Prepare livelihood strategy data for visualization.
+    """
+    df.rename(columns={"livelihood_zone_country": "country_code"}, inplace=True)
+    df["ls_baseline_date"] = df["livelihood_zone_baseline_label"].str.split(": ").str[1]
+    df["ls_baseline_month"] = pd.to_datetime(df["ls_baseline_date"], errors="coerce").dt.month
+    return df
+
+
+def prepare_wealth_group_data(df):
+    """
+    Prepare wealth group data for visualization.
+    """
+    df.rename(columns={"livelihood_zone_country_code": "country_code"}, inplace=True)
+
+    if "livelihood_zone_baseline_label" in df.columns:
+        df["ls_baseline_date"] = df["livelihood_zone_baseline_label"].str.split(": ").str[1]
+    else:
+        df["ls_baseline_date"] = None
+
+    df["ls_baseline_month"] = pd.to_datetime(df["ls_baseline_date"], errors="coerce").dt.month
+
+    month_mapping = {month: pd.Timestamp(f"2023-{month:02}-01").strftime("%B") for month in range(1, 13)}
+
+    if "created_date" in df.columns:
+        df["created_month"] = pd.to_datetime(df["created_date"], errors="coerce").dt.month.map(month_mapping)
+    else:
+        df["created_month"] = pd.to_datetime(df["ls_baseline_date"], errors="coerce").dt.month.map(month_mapping)
+
+    if "community_name" in df.columns:
+        df["Record Type"] = df["community_name"].apply(lambda x: "Summary Data" if pd.isna(x) else "Community Data")
+    else:
+        df["Record Type"] = "Community Data"
+
+    return df
+
+
+# Fetch and prepare data
+livelihood_data = fetch_data(LIVELIHOOD_STRATEGY_URL)
+wealth_group_data = fetch_data(WEALTH_GROUP_URL)
+
+clean_livelihood_data = prepare_livelihood_data(livelihood_data)
+clean_wealth_group_data = prepare_wealth_group_data(wealth_group_data)

apps/viz/dash_wrapper.py

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+from django_plotly_dash import DjangoDash
+
+
+class SecureDjangoDash(DjangoDash):
+    """
+    An extended version of DjangoDash that allows fine-grained control of permissions
+    and clickjacking protection
+    """
+
+    xframe_options = "DENY"  # None (i.e. Allow) or SAMEORIGIN or DENY
+    login_required = True
+    permission_required = None
+
+    def __init__(self, *args, **kwargs):
+        self.permission_required = kwargs.pop("permission_required", None)
+        super().__init__(*args, **kwargs)