add condition desk
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@@ -303,7 +303,7 @@ _PILLAR_CONTEXT_FALLBACK: dict = {
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def get_pillar_condition(pillar_name: str, score: float) -> tuple:
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"""
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Mengembalikan (condition_en, condition_id) berdasarkan skor dan nama pilar.
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Mengembalikan 4-tuple kondisi pilar berdasarkan skor dan nama pilar.
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Tier mengacu GFSI 2022 (Economist Impact) + IPC Phase Classification (2019):
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>= 75 -> Secure / Aman
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@@ -320,10 +320,15 @@ def get_pillar_condition(pillar_name: str, score: float) -> tuple:
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score : Skor ternormalisasi skala 1-100.
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Returns:
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Tuple (condition_en: str, condition_id: str)
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Tuple (
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condition_en : str — label tier bahasa Inggris, e.g. "At Risk"
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condition_id : str — label tier bahasa Indonesia, e.g. "Berisiko"
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condition_desc_en : str — deskripsi kontekstual bahasa Inggris
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condition_desc_id : str — deskripsi kontekstual bahasa Indonesia
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)
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"""
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if score is None or (isinstance(score, float) and np.isnan(score)):
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return ("N/A", "N/A")
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return ("N/A", "N/A", "N/A", "N/A")
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# Tentukan tier
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tier_label_en = _CONDITION_TIERS[-1][1] # default: Critical
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@@ -334,7 +339,7 @@ def get_pillar_condition(pillar_name: str, score: float) -> tuple:
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tier_label_id = lbl_id
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break
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# Ambil konteks per pilar
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# Ambil deskripsi kontekstual per pilar
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ctx = _PILLAR_CONTEXT.get(pillar_name, None)
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if ctx:
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ctx_en, ctx_id = ctx.get(
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@@ -344,10 +349,7 @@ def get_pillar_condition(pillar_name: str, score: float) -> tuple:
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else:
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ctx_en, ctx_id = _PILLAR_CONTEXT_FALLBACK.get(tier_label_en, ("", ""))
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# Format akhir: "TIER — Context"
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condition_en = f"{tier_label_en} — {ctx_en}"
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condition_id = f"{tier_label_id} — {ctx_id}"
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return condition_en, condition_id
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return tier_label_en, tier_label_id, ctx_en, ctx_id
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# =============================================================================
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@@ -938,11 +940,17 @@ class FoodSecurityAggregator:
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df["pillar_country_score_1_100"] = global_minmax(df["pillar_country_norm"])
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# ---------------------------------------------------------------
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# TAMBAHAN: kolom kondisi pilar
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# TAMBAHAN: kolom kondisi pilar (tier + deskripsi dipisah)
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# Dibangkitkan SETELAH score_1_100 tersedia, sehingga tier
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# langsung mencerminkan skor dalam skala akhir 1-100.
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# Referensi tier: GFSI 2022 (Economist Impact); IPC 2019;
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# FAO/CFS 1996/2009; FAO SOFI 2024.
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#
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# Kolom yang dihasilkan:
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# pillar_condition_en — label tier EN, e.g. "At Risk"
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# pillar_condition_id — label tier ID, e.g. "Berisiko"
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# pillar_condition_desc_en — deskripsi kontekstual EN
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# pillar_condition_desc_id — deskripsi kontekstual ID
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# ---------------------------------------------------------------
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conditions = df.apply(
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lambda row: get_pillar_condition(
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@@ -953,6 +961,8 @@ class FoodSecurityAggregator:
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)
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df["pillar_condition_en"] = conditions.apply(lambda x: x[0])
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df["pillar_condition_id"] = conditions.apply(lambda x: x[1])
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df["pillar_condition_desc_en"] = conditions.apply(lambda x: x[2])
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df["pillar_condition_desc_id"] = conditions.apply(lambda x: x[3])
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# Rank hanya di antara negara asli
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country_only = df[df["country_id"] != ASEAN_COUNTRY_ID].copy()
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@@ -978,6 +988,8 @@ class FoodSecurityAggregator:
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df["country_name_id"] = df["country_name_id"].astype(str)
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df["pillar_condition_en"] = df["pillar_condition_en"].astype(str)
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df["pillar_condition_id"] = df["pillar_condition_id"].astype(str)
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df["pillar_condition_desc_en"] = df["pillar_condition_desc_en"].astype(str)
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df["pillar_condition_desc_id"] = df["pillar_condition_desc_id"].astype(str)
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self.logger.info(
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f" Total rows: {len(df):,} "
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@@ -1002,10 +1014,13 @@ class FoodSecurityAggregator:
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bigquery.SchemaField("pillar_country_score_1_100", "FLOAT", mode="REQUIRED"),
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bigquery.SchemaField("rank_in_pillar_year", "INTEGER", mode="REQUIRED"),
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bigquery.SchemaField("year_over_year_change", "FLOAT", mode="NULLABLE"),
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# --- KOLOM KONDISI BARU ---
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# Tier skor (GFSI 2022) + konteks substantif per pilar (FAO/CFS; IPC 2019)
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# --- KOLOM KONDISI ---
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# Tier label (GFSI 2022): Secure / Adequate / Moderate / At Risk / Critical
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bigquery.SchemaField("pillar_condition_en", "STRING", mode="REQUIRED"),
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bigquery.SchemaField("pillar_condition_id", "STRING", mode="REQUIRED"),
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# Deskripsi kontekstual per pilar (FAO/CFS 4-pillar; IPC 2019; FAO SOFI 2024)
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bigquery.SchemaField("pillar_condition_desc_en", "STRING", mode="REQUIRED"),
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bigquery.SchemaField("pillar_condition_desc_id", "STRING", mode="REQUIRED"),
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]
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rows = load_to_bigquery(
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self.client, df, table_name, layer='gold',
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@@ -1315,6 +1330,8 @@ class FoodSecurityAggregator:
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# Ambil kondisi dari kolom yang sudah dihitung di df_pillar_by_country
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cond_en = str(row.get("pillar_condition_en", "N/A"))
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cond_id = str(row.get("pillar_condition_id", "N/A"))
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cond_desc_en = str(row.get("pillar_condition_desc_en", "N/A"))
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cond_desc_id = str(row.get("pillar_condition_desc_id", "N/A"))
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records.append({
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"year": yr,
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@@ -1336,6 +1353,8 @@ class FoodSecurityAggregator:
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"is_asean_aggregate": is_asean,
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"pillar_condition_en": cond_en,
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"pillar_condition_id": cond_id,
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"pillar_condition_desc_en": cond_desc_en,
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"pillar_condition_desc_id": cond_desc_id,
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"narrative_en": narrative_en,
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"narrative_id": narrative_id,
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})
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@@ -1350,6 +1369,8 @@ class FoodSecurityAggregator:
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df["country_name_id"] = df["country_name_id"].astype(str)
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df["pillar_condition_en"] = df["pillar_condition_en"].astype(str)
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df["pillar_condition_id"] = df["pillar_condition_id"].astype(str)
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df["pillar_condition_desc_en"] = df["pillar_condition_desc_en"].astype(str)
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df["pillar_condition_desc_id"] = df["pillar_condition_desc_id"].astype(str)
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df["narrative_en"] = df["narrative_en"].astype(str)
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df["narrative_id"] = df["narrative_id"].astype(str)
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for col in ["pillar_score", "yoy_change", "top_country_score", "bottom_country_score"]:
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@@ -1377,8 +1398,12 @@ class FoodSecurityAggregator:
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bigquery.SchemaField("bottom_country_id", "STRING", mode="NULLABLE"),
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bigquery.SchemaField("bottom_country_score", "FLOAT", mode="NULLABLE"),
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bigquery.SchemaField("is_asean_aggregate", "BOOL", mode="REQUIRED"),
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# Tier label: Secure / Adequate / Moderate / At Risk / Critical
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bigquery.SchemaField("pillar_condition_en", "STRING", mode="REQUIRED"),
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bigquery.SchemaField("pillar_condition_id", "STRING", mode="REQUIRED"),
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# Deskripsi kontekstual per pilar
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bigquery.SchemaField("pillar_condition_desc_en", "STRING", mode="REQUIRED"),
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bigquery.SchemaField("pillar_condition_desc_id", "STRING", mode="REQUIRED"),
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bigquery.SchemaField("narrative_en", "STRING", mode="REQUIRED"),
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bigquery.SchemaField("narrative_id", "STRING", mode="REQUIRED"),
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]
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