feat(ees): rewrite EES tap and KS2 models for actual data structure

- Fix publication slugs (KS4, Phonics, Admissions were wrong)
- Split KS2 into two streams: ees_ks2_attainment (long format) and
  ees_ks2_info (wide format context data)
- Target specific filenames instead of keyword matching
- Handle school_urn vs urn column naming
- Pivot KS2 attainment from long to wide format in dbt staging
- Add all ~40 KS2 columns the backend needs (GPS, absence, gender,
  disadvantaged breakdowns, context demographics)
- Pass through all columns in int_ks2_with_lineage and fact_ks2

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py

@@ -1,4 +1,10 @@
-"""EES Singer tap — extracts KS2, KS4, Census, Admissions, Phonics data."""
+"""EES Singer tap — extracts KS2, KS4, Census, Admissions, Phonics data.
+
+Each stream targets a specific CSV file within an EES release ZIP.
+The EES data uses 'school_urn' for school-level records and 'z' for
+suppressed values. Column names vary by file — schemas declare all
+columns needed by downstream dbt staging models.
+"""
 
 from __future__ import annotations
 
@@ -12,7 +18,6 @@ from singer_sdk import typing as th
 CONTENT_API_BASE = (
     "https://content.explore-education-statistics.service.gov.uk/api"
 )
-STATS_API_BASE = "https://api.education.gov.uk/statistics/v1"
 TIMEOUT = 120
 
 
@@ -37,7 +42,8 @@ class EESDatasetStream(Stream):
 
     replication_key = None
     _publication_slug: str = ""
-    _file_keyword: str = ""
+    _target_filename: str = ""  # exact filename within the ZIP
+    _urn_column: str = "school_urn"  # column name for URN in the CSV
 
     def get_records(self, context):
         import pandas as pd
@@ -50,84 +56,153 @@ class EESDatasetStream(Stream):
         )
         zf = download_release_zip(release_id)
 
-        # Find the CSV matching our keyword
+        # Find the target file
-        csv_names = [n for n in zf.namelist() if n.endswith(".csv")]
+        all_files = zf.namelist()
         target = None
-        for name in csv_names:
+        for name in all_files:
-            if self._file_keyword.lower() in name.lower():
+            if name.endswith(self._target_filename):
                 target = name
                 break
-        if not target and csv_names:
-            target = csv_names[0]
 
         if not target:
-            self.logger.warning("No CSV found in release ZIP")
+            self.logger.error(
+                "File '%s' not found in ZIP. Available: %s",
+                self._target_filename,
+                [n for n in all_files if n.endswith(".csv")],
+            )
             return
 
         self.logger.info("Reading %s from ZIP", target)
         with zf.open(target) as f:
             df = pd.read_csv(f, dtype=str, keep_default_na=False)
 
-        # Filter to school-level data
+        # Filter to school-level data if the column exists
         if "geographic_level" in df.columns:
             df = df[df["geographic_level"] == "School"]
 
+        self.logger.info("Emitting %d school-level rows", len(df))
+
         for _, row in df.iterrows():
-            yield row.to_dict()
+            record = row.to_dict()
+            # Normalise URN column to 'school_urn' for consistency
+            if self._urn_column in record and self._urn_column != "school_urn":
+                record["school_urn"] = record.pop(self._urn_column)
+            yield record
 
 
-class EESKS2Stream(EESDatasetStream):
+# ── KS2 Attainment (long format: one row per school × subject × breakdown) ──
-    name = "ees_ks2"
+
-    primary_keys = ["urn", "time_period"]
+class EESKS2AttainmentStream(EESDatasetStream):
+    name = "ees_ks2_attainment"
+    primary_keys = ["school_urn", "time_period", "subject", "breakdown_topic", "breakdown"]
     _publication_slug = "key-stage-2-attainment"
-    _file_keyword = "school"
+    _target_filename = "ks2_school_attainment_data.csv"
     schema = th.PropertiesList(
-        th.Property("urn", th.StringType, required=True),
         th.Property("time_period", th.StringType, required=True),
+        th.Property("school_urn", th.StringType, required=True),
+        th.Property("school_laestab", th.StringType),
+        th.Property("school_name", th.StringType),
+        th.Property("breakdown_topic", th.StringType, required=True),
+        th.Property("breakdown", th.StringType, required=True),
+        th.Property("subject", th.StringType, required=True),
+        th.Property("expected_standard_pupil_percent", th.StringType),
+        th.Property("higher_standard_pupil_percent", th.StringType),
+        th.Property("average_scaled_score", th.StringType),
+        th.Property("progress_measure_score", th.StringType),
+        th.Property("progress_measure_lower_conf_interval", th.StringType),
+        th.Property("progress_measure_upper_conf_interval", th.StringType),
+        th.Property("absent_or_not_able_to_access_percent", th.StringType),
+        th.Property("working_towards_expected_standard_pupil_percent", th.StringType),
+        th.Property("absent_or_disapplied_percent", th.StringType),
+        th.Property("higher_standard", th.StringType),
+        th.Property("progress_measure_unadjusted", th.StringType),
+        th.Property("progress_measure_description", th.StringType),
     ).to_dict()
 
 
+# ── KS2 Information (wide format: one row per school, context/demographics) ──
+
+class EESKS2InfoStream(EESDatasetStream):
+    name = "ees_ks2_info"
+    primary_keys = ["school_urn", "time_period"]
+    _publication_slug = "key-stage-2-attainment"
+    _target_filename = "ks2_school_information_data.csv"
+    schema = th.PropertiesList(
+        th.Property("time_period", th.StringType, required=True),
+        th.Property("school_urn", th.StringType, required=True),
+        th.Property("school_laestab", th.StringType),
+        th.Property("school_name", th.StringType),
+        th.Property("nftype", th.StringType),
+        th.Property("reldenom", th.StringType),
+        th.Property("agerange", th.StringType),
+        th.Property("totpups", th.StringType),
+        th.Property("telig", th.StringType),
+        th.Property("belig", th.StringType),
+        th.Property("gelig", th.StringType),
+        th.Property("ptfsm6cla1a", th.StringType),
+        th.Property("ptnotfsm6cla1a", th.StringType),
+        th.Property("ptealgrp2", th.StringType),
+        th.Property("ptmobn", th.StringType),
+        th.Property("psenelk", th.StringType),
+        th.Property("psenele", th.StringType),
+        th.Property("psenelek", th.StringType),
+        th.Property("telig_3yr", th.StringType),
+    ).to_dict()
+
+
+# ── KS4 Attainment ──────────────────────────────────────────────────────────
+
 class EESKS4Stream(EESDatasetStream):
     name = "ees_ks4"
-    primary_keys = ["urn", "time_period"]
+    primary_keys = ["school_urn", "time_period"]
-    _publication_slug = "key-stage-4-performance-revised"
+    _publication_slug = "key-stage-4-performance"
-    _file_keyword = "school"
+    _target_filename = "school"  # Will be refined once we see the actual ZIP contents
     schema = th.PropertiesList(
-        th.Property("urn", th.StringType, required=True),
         th.Property("time_period", th.StringType, required=True),
+        th.Property("school_urn", th.StringType, required=True),
     ).to_dict()
 
 
+# ── Census (school-level pupil characteristics) ─────────────────────────────
+
 class EESCensusStream(EESDatasetStream):
     name = "ees_census"
     primary_keys = ["urn", "time_period"]
     _publication_slug = "school-pupils-and-their-characteristics"
-    _file_keyword = "school"
+    _target_filename = "spc_school_level_underlying_data_2025.csv"
+    _urn_column = "urn"
     schema = th.PropertiesList(
-        th.Property("urn", th.StringType, required=True),
         th.Property("time_period", th.StringType, required=True),
+        th.Property("urn", th.StringType, required=True),
+        th.Property("school_name", th.StringType),
+        th.Property("laestab", th.StringType),
+        th.Property("phase_type_grouping", th.StringType),
     ).to_dict()
 
 
+# ── Admissions ───────────────────────────────────────────────────────────────
+
 class EESAdmissionsStream(EESDatasetStream):
     name = "ees_admissions"
-    primary_keys = ["urn", "time_period"]
+    primary_keys = ["school_urn", "time_period"]
-    _publication_slug = "secondary-and-primary-school-applications-and-offers"
+    _publication_slug = "primary-and-secondary-school-applications-and-offers"
-    _file_keyword = "school"
+    _target_filename = "school"  # Will be refined once we see the actual ZIP contents
     schema = th.PropertiesList(
-        th.Property("urn", th.StringType, required=True),
         th.Property("time_period", th.StringType, required=True),
+        th.Property("school_urn", th.StringType, required=True),
     ).to_dict()
 
 
+# ── Phonics ──────────────────────────────────────────────────────────────────
+
 class EESPhonicsStream(EESDatasetStream):
     name = "ees_phonics"
-    primary_keys = ["urn", "time_period"]
+    primary_keys = ["school_urn", "time_period"]
-    _publication_slug = "phonics-screening-check-and-key-stage-1-assessments"
+    _publication_slug = "phonics-screening-check-attainment"
-    _file_keyword = "school"
+    _target_filename = "school"  # Will be refined once we see the actual ZIP contents
     schema = th.PropertiesList(
-        th.Property("urn", th.StringType, required=True),
         th.Property("time_period", th.StringType, required=True),
+        th.Property("school_urn", th.StringType, required=True),
     ).to_dict()
 
 
@@ -142,7 +217,8 @@ class TapUKEES(Tap):
 
     def discover_streams(self):
         return [
-            EESKS2Stream(self),
+            EESKS2AttainmentStream(self),
+            EESKS2InfoStream(self),
             EESKS4Stream(self),
             EESCensusStream(self),
             EESAdmissionsStream(self),

pipeline/transform/models/intermediate/int_ks2_with_lineage.sql

@@ -5,21 +5,16 @@ with current_ks2 as (
     select
         urn as current_urn,
         urn as source_urn,
-        year,
+        year, total_pupils, eligible_pupils,
-        total_pupils,
+        rwm_expected_pct, rwm_high_pct,
-        rwm_expected_pct,
+        reading_expected_pct, reading_high_pct, reading_avg_score, reading_progress,
-        reading_expected_pct,
+        writing_expected_pct, writing_high_pct, writing_progress,
-        writing_expected_pct,
+        maths_expected_pct, maths_high_pct, maths_avg_score, maths_progress,
-        maths_expected_pct,
+        gps_expected_pct, gps_high_pct, gps_avg_score, science_expected_pct,
-        rwm_high_pct,
+        reading_absence_pct, writing_absence_pct, maths_absence_pct, gps_absence_pct, science_absence_pct,
-        reading_high_pct,
+        rwm_expected_boys_pct, rwm_high_boys_pct, rwm_expected_girls_pct, rwm_high_girls_pct,
-        writing_high_pct,
+        rwm_expected_disadvantaged_pct, rwm_expected_non_disadvantaged_pct, disadvantaged_gap,
-        maths_high_pct,
+        disadvantaged_pct, eal_pct, sen_support_pct, sen_ehcp_pct, stability_pct
-        reading_progress,
-        writing_progress,
-        maths_progress,
-        reading_avg_score,
-        maths_avg_score
     from {{ ref('stg_ees_ks2') }}
 ),
 
@@ -27,25 +22,19 @@ predecessor_ks2 as (
     select
         lin.current_urn,
         ks2.urn as source_urn,
-        ks2.year,
+        ks2.year, ks2.total_pupils, ks2.eligible_pupils,
-        ks2.total_pupils,
+        ks2.rwm_expected_pct, ks2.rwm_high_pct,
-        ks2.rwm_expected_pct,
+        ks2.reading_expected_pct, ks2.reading_high_pct, ks2.reading_avg_score, ks2.reading_progress,
-        ks2.reading_expected_pct,
+        ks2.writing_expected_pct, ks2.writing_high_pct, ks2.writing_progress,
-        ks2.writing_expected_pct,
+        ks2.maths_expected_pct, ks2.maths_high_pct, ks2.maths_avg_score, ks2.maths_progress,
-        ks2.maths_expected_pct,
+        ks2.gps_expected_pct, ks2.gps_high_pct, ks2.gps_avg_score, ks2.science_expected_pct,
-        ks2.rwm_high_pct,
+        ks2.reading_absence_pct, ks2.writing_absence_pct, ks2.maths_absence_pct, ks2.gps_absence_pct, ks2.science_absence_pct,
-        ks2.reading_high_pct,
+        ks2.rwm_expected_boys_pct, ks2.rwm_high_boys_pct, ks2.rwm_expected_girls_pct, ks2.rwm_high_girls_pct,
-        ks2.writing_high_pct,
+        ks2.rwm_expected_disadvantaged_pct, ks2.rwm_expected_non_disadvantaged_pct, ks2.disadvantaged_gap,
-        ks2.maths_high_pct,
+        ks2.disadvantaged_pct, ks2.eal_pct, ks2.sen_support_pct, ks2.sen_ehcp_pct, ks2.stability_pct
-        ks2.reading_progress,
-        ks2.writing_progress,
-        ks2.maths_progress,
-        ks2.reading_avg_score,
-        ks2.maths_avg_score
     from {{ ref('stg_ees_ks2') }} ks2
     inner join {{ ref('int_school_lineage') }} lin
         on ks2.urn = lin.predecessor_urn
-    -- Only include predecessor data for years before the current URN has data
     where not exists (
         select 1 from {{ ref('stg_ees_ks2') }} curr
         where curr.urn = lin.current_urn

pipeline/transform/models/marts/fact_ks2_performance.sql

@@ -6,17 +6,50 @@ select
     source_urn,
     year,
     total_pupils,
+    eligible_pupils,
+
+    -- Core attainment
     rwm_expected_pct,
-    reading_expected_pct,
-    writing_expected_pct,
-    maths_expected_pct,
     rwm_high_pct,
+    reading_expected_pct,
     reading_high_pct,
-    writing_high_pct,
-    maths_high_pct,
-    reading_progress,
-    writing_progress,
-    maths_progress,
     reading_avg_score,
-    maths_avg_score
+    reading_progress,
+    writing_expected_pct,
+    writing_high_pct,
+    writing_progress,
+    maths_expected_pct,
+    maths_high_pct,
+    maths_avg_score,
+    maths_progress,
+    gps_expected_pct,
+    gps_high_pct,
+    gps_avg_score,
+    science_expected_pct,
+
+    -- Absence
+    reading_absence_pct,
+    writing_absence_pct,
+    maths_absence_pct,
+    gps_absence_pct,
+    science_absence_pct,
+
+    -- Gender
+    rwm_expected_boys_pct,
+    rwm_high_boys_pct,
+    rwm_expected_girls_pct,
+    rwm_high_girls_pct,
+
+    -- Disadvantaged
+    rwm_expected_disadvantaged_pct,
+    rwm_expected_non_disadvantaged_pct,
+    disadvantaged_gap,
+
+    -- Context
+    disadvantaged_pct,
+    eal_pct,
+    sen_support_pct,
+    sen_ehcp_pct,
+    stability_pct
+
 from {{ ref('int_ks2_with_lineage') }}

pipeline/transform/models/staging/_stg_sources.yml

@@ -24,8 +24,11 @@ sources:
       - name: ofsted_inspections
         description: Ofsted Management Information inspection records
 
-      - name: ees_ks2
+      - name: ees_ks2_attainment
-        description: KS2 attainment data from Explore Education Statistics
+        description: KS2 school attainment (long format — one row per school × subject × breakdown)
+
+      - name: ees_ks2_info
+        description: KS2 school information (wide format — context/demographics per school)
 
       - name: ees_ks4
         description: KS4 attainment data from Explore Education Statistics

pipeline/transform/models/staging/stg_ees_ks2.sql

@@ -1,31 +1,185 @@
--- Staging model: KS2 attainment data from EES
+-- Staging model: KS2 attainment + information
--- Column names depend on the EES dataset schema; these will be finalised
+-- Pivots long-format attainment data (one row per subject × breakdown) into
--- once the tap-uk-ees extractor resolves the actual column names.
+-- wide format (one row per school per year) and joins context from info table.
+-- EES uses 'z' for suppressed values — cast to null via nullif.
 
-with source as (
+with attainment as (
-    select * from {{ source('raw', 'ees_ks2') }}
+    select * from {{ source('raw', 'ees_ks2_attainment') }}
+    where school_urn is not null
 ),
 
-renamed as (
+-- Pivot: extract metrics for each subject where breakdown = 'Total'
+all_pupils as (
     select
-        cast(urn as integer)                    as urn,
+        school_urn,
-        cast(time_period as integer)            as year,
+        time_period,
-        cast(t_pupils as integer)               as total_pupils,
+        subject,
-        cast(pt_rwm_met_expected_standard as numeric) as rwm_expected_pct,
+        nullif(expected_standard_pupil_percent, 'z') as expected_pct,
-        cast(pt_read_met_expected_standard as numeric) as reading_expected_pct,
+        nullif(higher_standard_pupil_percent, 'z') as higher_pct,
-        cast(pt_write_met_expected_standard as numeric) as writing_expected_pct,
+        nullif(average_scaled_score, 'z') as avg_score,
-        cast(pt_maths_met_expected_standard as numeric) as maths_expected_pct,
+        nullif(progress_measure_score, 'z') as progress,
-        cast(pt_rwm_met_higher_standard as numeric) as rwm_high_pct,
+        nullif(absent_or_not_able_to_access_percent, 'z') as absence_pct
-        cast(pt_read_met_higher_standard as numeric) as reading_high_pct,
+    from attainment
-        cast(pt_write_met_higher_standard as numeric) as writing_high_pct,
+    where breakdown_topic = 'All pupils'
-        cast(pt_maths_met_higher_standard as numeric) as maths_high_pct,
+      and breakdown = 'Total'
-        cast(read_progress as numeric)          as reading_progress,
+),
-        cast(write_progress as numeric)         as writing_progress,
+
-        cast(maths_progress as numeric)         as maths_progress,
+pivoted as (
-        cast(read_average_score as numeric)     as reading_avg_score,
+    select
-        cast(maths_average_score as numeric)    as maths_avg_score
+        cast(school_urn as integer) as urn,
-    from source
+        cast(time_period as integer) as year,
-    where urn is not null
+
+        -- RWM combined
+        max(case when subject = 'Reading, writing and maths' then cast(expected_pct as numeric) end) as rwm_expected_pct,
+        max(case when subject = 'Reading, writing and maths' then cast(higher_pct as numeric) end) as rwm_high_pct,
+
+        -- Reading
+        max(case when subject = 'Reading' then cast(expected_pct as numeric) end) as reading_expected_pct,
+        max(case when subject = 'Reading' then cast(higher_pct as numeric) end) as reading_high_pct,
+        max(case when subject = 'Reading' then cast(avg_score as numeric) end) as reading_avg_score,
+        max(case when subject = 'Reading' then cast(progress as numeric) end) as reading_progress,
+        max(case when subject = 'Reading' then cast(absence_pct as numeric) end) as reading_absence_pct,
+
+        -- Writing
+        max(case when subject = 'Writing' then cast(expected_pct as numeric) end) as writing_expected_pct,
+        max(case when subject = 'Writing' then cast(higher_pct as numeric) end) as writing_high_pct,
+        max(case when subject = 'Writing' then cast(progress as numeric) end) as writing_progress,
+        max(case when subject = 'Writing' then cast(absence_pct as numeric) end) as writing_absence_pct,
+
+        -- Maths
+        max(case when subject = 'Maths' then cast(expected_pct as numeric) end) as maths_expected_pct,
+        max(case when subject = 'Maths' then cast(higher_pct as numeric) end) as maths_high_pct,
+        max(case when subject = 'Maths' then cast(avg_score as numeric) end) as maths_avg_score,
+        max(case when subject = 'Maths' then cast(progress as numeric) end) as maths_progress,
+        max(case when subject = 'Maths' then cast(absence_pct as numeric) end) as maths_absence_pct,
+
+        -- GPS
+        max(case when subject ilike '%grammar%' or subject = 'GPS' then cast(expected_pct as numeric) end) as gps_expected_pct,
+        max(case when subject ilike '%grammar%' or subject = 'GPS' then cast(higher_pct as numeric) end) as gps_high_pct,
+        max(case when subject ilike '%grammar%' or subject = 'GPS' then cast(avg_score as numeric) end) as gps_avg_score,
+        max(case when subject ilike '%grammar%' or subject = 'GPS' then cast(absence_pct as numeric) end) as gps_absence_pct,
+
+        -- Science
+        max(case when subject = 'Science' then cast(expected_pct as numeric) end) as science_expected_pct,
+        max(case when subject = 'Science' then cast(absence_pct as numeric) end) as science_absence_pct
+
+    from all_pupils
+    group by school_urn, time_period
+),
+
+-- Gender breakdown for RWM
+gender_boys as (
+    select
+        school_urn,
+        time_period,
+        nullif(expected_standard_pupil_percent, 'z') as rwm_expected_boys_pct,
+        nullif(higher_standard_pupil_percent, 'z') as rwm_high_boys_pct
+    from attainment
+    where subject = 'Reading, writing and maths'
+      and breakdown = 'Boys'
+),
+
+gender_girls as (
+    select
+        school_urn,
+        time_period,
+        nullif(expected_standard_pupil_percent, 'z') as rwm_expected_girls_pct,
+        nullif(higher_standard_pupil_percent, 'z') as rwm_high_girls_pct
+    from attainment
+    where subject = 'Reading, writing and maths'
+      and breakdown = 'Girls'
+),
+
+-- Disadvantaged breakdown for RWM
+disadv as (
+    select
+        school_urn,
+        time_period,
+        nullif(expected_standard_pupil_percent, 'z') as rwm_expected_disadvantaged_pct
+    from attainment
+    where subject = 'Reading, writing and maths'
+      and breakdown = 'Disadvantaged'
+),
+
+not_disadv as (
+    select
+        school_urn,
+        time_period,
+        nullif(expected_standard_pupil_percent, 'z') as rwm_expected_non_disadvantaged_pct
+    from attainment
+    where subject = 'Reading, writing and maths'
+      and breakdown = 'Not disadvantaged'
+),
+
+-- School info (context/demographics)
+info as (
+    select
+        cast(school_urn as integer) as urn,
+        cast(time_period as integer) as year,
+        cast(nullif(totpups, 'z') as integer) as total_pupils,
+        cast(nullif(telig, 'z') as integer) as eligible_pupils,
+        cast(nullif(ptfsm6cla1a, 'z') as numeric) as disadvantaged_pct,
+        cast(nullif(ptealgrp2, 'z') as numeric) as eal_pct,
+        cast(nullif(psenelk, 'z') as numeric) as sen_support_pct,
+        cast(nullif(psenele, 'z') as numeric) as sen_ehcp_pct,
+        cast(nullif(ptmobn, 'z') as numeric) as stability_pct
+    from {{ source('raw', 'ees_ks2_info') }}
+    where school_urn is not null
 )
 
-select * from renamed
+select
+    p.urn,
+    p.year,
+    i.total_pupils,
+    i.eligible_pupils,
+
+    -- Core attainment
+    p.rwm_expected_pct,
+    p.rwm_high_pct,
+    p.reading_expected_pct,
+    p.reading_high_pct,
+    p.reading_avg_score,
+    p.reading_progress,
+    p.writing_expected_pct,
+    p.writing_high_pct,
+    p.writing_progress,
+    p.maths_expected_pct,
+    p.maths_high_pct,
+    p.maths_avg_score,
+    p.maths_progress,
+    p.gps_expected_pct,
+    p.gps_high_pct,
+    p.gps_avg_score,
+    p.science_expected_pct,
+
+    -- Absence
+    p.reading_absence_pct,
+    p.writing_absence_pct,
+    p.maths_absence_pct,
+    p.gps_absence_pct,
+    p.science_absence_pct,
+
+    -- Gender
+    cast(gb.rwm_expected_boys_pct as numeric) as rwm_expected_boys_pct,
+    cast(gb.rwm_high_boys_pct as numeric) as rwm_high_boys_pct,
+    cast(gg.rwm_expected_girls_pct as numeric) as rwm_expected_girls_pct,
+    cast(gg.rwm_high_girls_pct as numeric) as rwm_high_girls_pct,
+
+    -- Disadvantaged
+    cast(d.rwm_expected_disadvantaged_pct as numeric) as rwm_expected_disadvantaged_pct,
+    cast(nd.rwm_expected_non_disadvantaged_pct as numeric) as rwm_expected_non_disadvantaged_pct,
+    cast(d.rwm_expected_disadvantaged_pct as numeric) - cast(nd.rwm_expected_non_disadvantaged_pct as numeric) as disadvantaged_gap,
+
+    -- Context
+    i.disadvantaged_pct,
+    i.eal_pct,
+    i.sen_support_pct,
+    i.sen_ehcp_pct,
+    i.stability_pct
+
+from pivoted p
+left join info i on p.urn = i.urn and p.year = i.year
+left join gender_boys gb on p.urn = cast(gb.school_urn as integer) and p.year = cast(gb.time_period as integer)
+left join gender_girls gg on p.urn = cast(gg.school_urn as integer) and p.year = cast(gg.time_period as integer)
+left join disadv d on p.urn = cast(d.school_urn as integer) and p.year = cast(d.time_period as integer)
+left join not_disadv nd on p.urn = cast(nd.school_urn as integer) and p.year = cast(nd.time_period as integer)