diff --git a/data_steward/analytics/cdr_ops/ad_hoc_analyses/search_sandbox_for_ids.py b/data_steward/analytics/cdr_ops/ad_hoc_analyses/search_sandbox_for_ids.py
deleted file mode 100644
index 12b0d59cf2..0000000000
--- a/data_steward/analytics/cdr_ops/ad_hoc_analyses/search_sandbox_for_ids.py
+++ /dev/null
@@ -1,126 +0,0 @@
-# -*- coding: utf-8 -*-
-# ---
-# jupyter:
-#   jupytext:
-#     text_representation:
-#       extension: .py
-#       format_name: light
-#       format_version: '1.5'
-#       jupytext_version: 1.7.1
-#   kernelspec:
-#     display_name: Python 3
-#     language: python
-#     name: python3
-# ---
-
-# Purpose: Use this notebook to search for ids in sandbox datasets
-
-# + tags=["parameters"]
-project_id = ''
-sandbox_dataset_id = '' # Sandbox dataset to search in for the problem ids
-search_field = '' # field in the sandbox tables expected to contain the ids. Example: observation_id
-run_as = ''
-
-# +
-from utils import auth
-import pandas as pd
-from gcloud.bq import BigQueryClient
-from common import JINJA_ENV
-from analytics.cdr_ops.notebook_utils import execute, IMPERSONATION_SCOPES, render_message
-
-pd.set_option('display.max_rows', None)
-# -
-
-impersonation_creds = auth.get_impersonation_credentials(
-    run_as, target_scopes=IMPERSONATION_SCOPES)
-
-client = BigQueryClient(project_id, credentials=impersonation_creds)
-
-# # Create list of ids to search
-# Run the following cell to create a list of ids to search for. Recommend using a LIMIT if the list is quite large.<br>
-# OR <br>
-# Manually create a list of ids called ids_list
-
-# +
-tpl = JINJA_ENV.from_string('''
-{INSERT QUERY HERE}
-''')
-query = tpl.render()
-ids = execute(client, query)
-
-ids_list = ids[search_field].to_list()
-
-
-# -
-
-# # Get the tables that contain the search_field, from the sandbox dataset
-#
-# The query will return the sandbox tables in the order of their creation time. Earliest to latest.
-
-# +
-tpl = JINJA_ENV.from_string('''
- 
-SELECT
-  c.*, t.creation_time
-  , ROW_NUMBER() OVER (ORDER BY t.creation_time) as run_order
-FROM
-  `{{project_id}}.{{sandbox_dataset_id}}.INFORMATION_SCHEMA.COLUMNS` AS c
-JOIN
-  `{{project_id}}.{{sandbox_dataset_id}}.INFORMATION_SCHEMA.TABLES` AS t
-ON
-  c.table_name = t.table_name
-WHERE
-  c.column_name = '{{search_field}}'
-ORDER BY
-  t.creation_time;
-    
-''')
-query = tpl.render(sandbox_dataset_id=sandbox_dataset_id,
-                   project_id=project_id,
-                   search_field=search_field)
-tables_in_dataset = execute(client, query)
-
-tables_list = tables_in_dataset['table_name'].to_list()
-tables_list
-# -
-
-# # Search in each sandbox table and print results
-
-queries = []
-for table in tables_list:
-    tpl = JINJA_ENV.from_string('''    
-    SELECT 
-    '{{table}}' as table,
-    COUNT(*) AS n_{{search_field}}s_found
-    FROM
-    `{{project_id}}.{{sandbox_dataset_id}}.{{table}}`
-    WHERE {{search_field}} IN UNNEST ({{ids_list}})
-    ''')
-    query = tpl.render(sandbox_dataset_id=sandbox_dataset_id,
-                       project_id=project_id,
-                       table=table,
-                       ids_list=ids_list,
-                       search_field=search_field)
-    queries.append(query)
-df = execute(client, '\nUNION ALL\n'.join(queries))
-
-
-# # Order and view the results
-
-# +
-# Define the run order
-df['run_order'] = pd.Categorical(df['table'], 
-                                 categories=tables_list,
-                                 ordered=True)
-
-# Sort the results
-ordered_df = (
-    df.sort_values(by='run_order')
-      .iloc[:, :2]
-      .reset_index(drop=True)
-)
-
-ordered_df
-# -
-
-