diff --git a/data/children_act/10_pub_law_sdp_process.ipynb b/data/children_act/10_pub_law_sdp_process.ipynb
index 4719e6f..ec74811 100644
--- a/data/children_act/10_pub_law_sdp_process.ipynb
+++ b/data/children_act/10_pub_law_sdp_process.ipynb
@@ -31,7 +31,7 @@
     "#snapshot dates and publication period are set in the main run file. However, if running this notebook independently you will need to set them here\n",
     "#snapshot_date = \"2025-05-06\"\n",
     "#pub_year = 2025 #set the publication year\n",
-    "#pub_qtr = 1 #set the publication quarter"
+    "#pub_qtr = 3 #set the publication quarter"
    ]
   },
   {
@@ -108,10 +108,7 @@
     "pydb.dataframe_to_temp_table(ca_apps_lookup, \"ca_apps_lookup\")\n",
     "\n",
     "ca_ords_lookup = pd.read_csv(f\"\"\"{folder_link}/ca_ords_lookup.csv\"\"\")\n",
-    "pydb.dataframe_to_temp_table(ca_ords_lookup, \"ca_ords_lookup\")\n",
-    "\n",
-    "ca_apps_lookup_v2 = pd.read_csv(f\"\"\"{folder_link}/ca_apps_lookup_v2.csv\"\"\")\n",
-    "pydb.dataframe_to_temp_table(ca_apps_lookup_v2, \"ca_apps_lookup_v2\")"
+    "pydb.dataframe_to_temp_table(ca_ords_lookup, \"ca_ords_lookup\")\n"
    ]
   },
   {
@@ -148,36 +145,7 @@
     "ca_ords_breakdown = pd.read_csv(f\"\"\"{folder_link}/ca_ords_breakdown.csv\"\"\", keep_default_na = False, na_values = ['', 'NULL'])\n",
     "ca_ords_breakdown.columns = ca_ords_breakdown.columns.str.lower()\n",
     "ca_ords_breakdown = ca_ords_breakdown.astype({'qtr': 'str'})\n",
-    "\n",
-    "ca_ords_breakdown_orders = ca_ords_breakdown.loc[ca_ords_breakdown['disposal_type'] != 'Withdrawn', :]\n",
-    "ca_ords_breakdown_withdrawn = ca_ords_breakdown.loc[ca_ords_breakdown['disposal_type'] == 'Withdrawn', :]\n",
-    "#pydb.dataframe_to_temp_table(ca_ords_breakdown, \"ca_ords_breakdown\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "10",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Putting them together as temporary tables\n",
-    "pydb.dataframe_to_temp_table(ca_ords_breakdown_orders, \"ca_ords_breakdown_orders\")\n",
-    "pydb.dataframe_to_temp_table(ca_ords_breakdown_withdrawn, \"ca_ords_breakdown_withdrawn\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d05aefad-9dec-4fe8-8974-1f38e4a89bc3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# CCD Disposals\n",
-    "ca_ccd_disp_breakdown = pd.read_csv(f\"\"\"{folder_link}/ca_ccd_disp_breakdown.csv\"\"\", keep_default_na = False, na_values = ['', 'NULL'])\n",
-    "ca_ccd_disp_breakdown.columns = ca_ccd_disp_breakdown.columns.str.lower()\n",
-    "ca_ccd_disp_breakdown = ca_ccd_disp_breakdown.astype({'qtr': 'str'})\n",
-    "pydb.dataframe_to_temp_table(ca_ccd_disp_breakdown, \"ca_ccd_disp_breakdown\")"
+    "pydb.dataframe_to_temp_table(ca_ords_breakdown, \"ca_ords_breakdown\")\n"
    ]
   },
   {
@@ -220,7 +188,7 @@
     "t1.Disposal_type,\n",
     "t2.order_desc,\n",
     "t2.order_type_code,\n",
-    "t1.Gender as Sex,\n",
+    "t1.Gender,\n",
     "t1.age_band,\n",
     "t1.Applicants_in_case,\n",
     "t1.Respondents_in_case,\n",
@@ -235,7 +203,7 @@
     "t1.Disposal_type,\n",
     "t2.order_desc,\n",
     "t2.order_type_code,\n",
-    "t1.Gender as Sex,\n",
+    "t1.Gender,\n",
     "t1.age_band,\n",
     "t1.Applicants_in_case,\n",
     "t1.Respondents_in_case,\n",
@@ -283,7 +251,7 @@
     "SUM(t1.Count) as count\n",
     "\n",
     "\n",
-    "FROM __temp__.ca_ords_breakdown_orders t1\n",
+    "FROM __temp__.ca_ords_breakdown t1\n",
     "LEFT JOIN __temp__.ca_ords_lookup t2\n",
     "ON t1.OrderMadeTypeKey = t2.OrderTypeKey\n",
     "\n",
@@ -297,7 +265,7 @@
     "t2.order_desc,\n",
     "CASE WHEN t1.Disposal_type IN ('Order made', 'Interim Order') THEN t2.order_type_code\n",
     "ELSE NULL END,\n",
-    "t1.Gender as Sex,\n",
+    "t1.Gender,\n",
     "t1.age_band,\n",
     "t1.Applicants_in_case,\n",
     "t1.Respondents_in_case,\n",
@@ -313,7 +281,7 @@
     "t2.order_desc,\n",
     "CASE WHEN t1.Disposal_type IN ('Order made', 'Interim Order') THEN t2.order_type_code\n",
     "ELSE NULL END,\n",
-    "t1.Gender as Sex,\n",
+    "t1.Gender,\n",
     "t1.age_band,\n",
     "t1.Applicants_in_case,\n",
     "t1.Respondents_in_case,\n",
@@ -333,69 +301,6 @@
     "#pydb.read_sql_query('SELECT * FROM __temp__.ca_ords_join')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "15",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Joining withdrawn orders breakdown to application lookup\n",
-    "pydb.create_temp_table(\n",
-    "f\"\"\"\n",
-    "SELECT\n",
-    "t1.Year,\n",
-    "t1.Qtr,\n",
-    "t1.Type,\n",
-    "t1.count_type,\n",
-    "t1.Public_private,\n",
-    "t1.Disposal_type,\n",
-    "t2.order_desc as Order_type,\n",
-    "CAST(NULL AS INT) as order_type_code,\n",
-    "t1.Gender as Sex,\n",
-    "t1.age_band,\n",
-    "t1.Applicants_in_case,\n",
-    "t1.Respondents_in_case,\n",
-    "t1.HC_Indicator,\n",
-    "SUM(t1.Count) as count\n",
-    "\n",
-    "\n",
-    "FROM __temp__.ca_ords_breakdown_withdrawn t1\n",
-    "LEFT JOIN __temp__.ca_apps_lookup_v2 t2\n",
-    "ON t1.order_type = t2.order_type\n",
-    "\n",
-    "GROUP BY\n",
-    "t1.Year,\n",
-    "t1.Qtr,\n",
-    "t1.Type,\n",
-    "t1.count_type,\n",
-    "t1.Public_private,\n",
-    "t1.Disposal_type,\n",
-    "t2.order_desc,\n",
-    "t1.Gender as Sex,\n",
-    "t1.age_band,\n",
-    "t1.Applicants_in_case,\n",
-    "t1.Respondents_in_case,\n",
-    "t1.HC_Indicator\n",
-    "\n",
-    "ORDER BY\n",
-    "t1.Year,\n",
-    "t1.Qtr,\n",
-    "t1.Type,\n",
-    "t1.count_type,\n",
-    "t1.Public_private,\n",
-    "t1.Disposal_type,\n",
-    "t2.order_desc,\n",
-    "t1.Gender as Sex,\n",
-    "t1.age_band,\n",
-    "t1.Applicants_in_case,\n",
-    "t1.Respondents_in_case,\n",
-    "t1.HC_Indicator\n",
-    "\n",
-    "\"\"\",\n",
-    "\"ca_ords_withdrawn_join\")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -406,67 +311,6 @@
     "#pydb.read_sql_query('SELECT * FROM __temp__.ca_ords_withdrawn_join')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3cc80726-61c8-4e62-b86c-89249e6e3468",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Joining CCD Disposals together\n",
-    "pydb.create_temp_table(f\"\"\"SELECT\n",
-    "t1.Year,\n",
-    "t1.Qtr,\n",
-    "t1.Type,\n",
-    "t1.count_type,\n",
-    "t1.Public_private,\n",
-    "t1.Disposal_type,\n",
-    "t2.order_desc as Order_type,\n",
-    "CAST(NULL AS INT) as order_type_code,\n",
-    "t1.Gender as Sex,\n",
-    "t1.age_band,\n",
-    "t1.Applicants_in_case,\n",
-    "t1.Respondents_in_case,\n",
-    "t1.HC_Indicator,\n",
-    "SUM(t1.Count) as count\n",
-    "\n",
-    "\n",
-    "FROM __temp__.ca_ccd_disp_breakdown t1\n",
-    "LEFT JOIN __temp__.ca_apps_lookup t2\n",
-    "ON t1.applicationtypekey = t2.applicationtypekey\n",
-    "\n",
-    "GROUP BY\n",
-    "t1.Year,\n",
-    "t1.Qtr,\n",
-    "t1.Type,\n",
-    "t1.count_type,\n",
-    "t1.Public_private,\n",
-    "t1.Disposal_type,\n",
-    "t2.order_desc,\n",
-    "t1.Gender as Sex,\n",
-    "t1.age_band,\n",
-    "t1.Applicants_in_case,\n",
-    "t1.Respondents_in_case,\n",
-    "t1.HC_Indicator\n",
-    "\n",
-    "ORDER BY\n",
-    "t1.Year,\n",
-    "t1.Qtr,\n",
-    "t1.Type,\n",
-    "t1.count_type,\n",
-    "t1.Public_private,\n",
-    "t1.Disposal_type,\n",
-    "t2.order_desc,\n",
-    "t1.Gender as Sex,\n",
-    "t1.age_band,\n",
-    "t1.Applicants_in_case,\n",
-    "t1.Respondents_in_case,\n",
-    "t1.HC_Indicator\n",
-    "\n",
-    "\"\"\",\n",
-    "\"ca_ccd_disposals_join\")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -481,8 +325,6 @@
     "UNION ALL\n",
     "SELECT * FROM __temp__.ca_ords_join\n",
     "UNION ALL\n",
-    "SELECT * FROM __temp__.ca_ords_withdrawn_join\n",
-    "UNION ALL\n",
     "SELECT * FROM __temp__.ca_cases_child\n",
     "UNION ALL\n",
     "SELECT * FROM __temp__.combined_orders\n",
@@ -544,7 +386,7 @@
     "t1.Disposal_type,\n",
     "t1.Order_type,\n",
     "CAST(order_type_code AS INT) as order_type_code,\n",
-    "t1.Gender as Sex,\n",
+    "t1.Sex,\n",
     "t1.age_band,\n",
     "t1.Applicants_in_case,\n",
     "t1.Respondents_in_case,\n",
@@ -558,6 +400,50 @@
     "WHERE Public_private = 'Private law'\n",
     ") t1                                       \n",
     "\"\"\",\n",
+    "\"ca_csv_v1\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ba534bf8-ed7d-4508-a378-2d2d2998add8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Combining SDP Public Law with only Private Law FamilyMan filtering out unneeded data\n",
+    "ca_csv_combine_sdp = pydb.create_temp_table(\n",
+    "f\"\"\"\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code not in (29, 30, 31, 32, 34) AND Public_private = 'Public law'\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code IS NULL AND Public_private = 'Public law' \n",
+    "AND order_type not in ('Section 8 Contact Order', 'Section 8 Residence Order', 'Section 8 Prohibited Steps Order', 'Section 8 Specific Issue Order', 'Financial Application')\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code in (29, 30, 31, 32) and type = 'Application' and year < 2021 AND Public_private = 'Public law'\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code in (29, 30, 31, 32) and type = 'Disposal' and Public_private = 'Public law' and\n",
+    "((year < 2021) or (year > 2024) or (year = 2024 and qtr = '4'))\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code = 34 and type = 'Disposal' and year < 2023 and Public_private = 'Public law'\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE Public_private = 'Private law' and order_type_code <> 34\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE Public_private = 'Private law' and order_type_code = 34 and year < 2023\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code IS NULL AND Public_private = 'Private law' and order_type <> 'Financial Application'\n",
+    "UNION ALL\n",
+    "SELECT * FROM __temp__.ca_csv_v1\n",
+    "WHERE order_type_code IS NULL AND Public_private = 'Private law' and order_type = 'Financial Application' and year < 2023\n",
+    "\n",
+    "\n",
+    "\"\"\",\n",
     "\"ca_csv_sdp\")"
    ]
   },
@@ -602,7 +488,7 @@
    "outputs": [],
    "source": [
     "print(\"exporting main ca csv to s3....\")\n",
-    "ca_csv_df.to_csv (r's3://alpha-family-data/fcsq_processing/children_act_outputs/CSV Children Act.csv', header = True, index = False)"
+    "ca_csv_df.to_csv (r's3://alpha-family-data/fcsq_processing/children_act_outputs/CSV Test Children Act.csv', header = True, index = False)"
    ]
   },
   {
@@ -838,7 +724,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "fcsq_venv",
+   "display_name": "FCSQ_run",
    "language": "python",
    "name": "venv_fcsq"
   },