experimental design (notebook)
This commit is contained in:
Steve L. Nyemba -- The Architect
parent
cbf41d0fc5
commit
18bfa63df1
|
|
@ -0,0 +1,273 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 66,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import pandas as pd\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"from google.cloud import bigquery as bq\n",
|
||||||
|
"\n",
|
||||||
|
"client = bq.Client.from_service_account_json('/home/steve/dev/google-cloud-sdk/accounts/vumc-test.json')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 33,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"xo = ['person_id','date_of_birth','race']\n",
|
||||||
|
"xi = ['person_id','value_as_number','value_source_value']"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 53,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def get_tables(client,did,fields=[]):\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" getting table lists from google\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" r = []\n",
|
||||||
|
" ref = client.dataset(id)\n",
|
||||||
|
" tables = list(client.list_tables(ref))\n",
|
||||||
|
" for table in tables :\n",
|
||||||
|
" ref = table.reference\n",
|
||||||
|
" schema = client.get_table(ref).schema\n",
|
||||||
|
" names = [f.field_name for f in schema]\n",
|
||||||
|
" x = list(set(names) & set(fields))\n",
|
||||||
|
" if x :\n",
|
||||||
|
" r.append({\"name\":table.table_id,\"fields\":names})\n",
|
||||||
|
" return r\n",
|
||||||
|
" \n",
|
||||||
|
"def get_fields(**args):\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" This function will generate a random set of fields from two tables. Tables are structured as follows \n",
|
||||||
|
" {name,fields:[],\"y\":}, with \n",
|
||||||
|
" name table name (needed to generate sql query)\n",
|
||||||
|
" fields list of field names, used in the projection\n",
|
||||||
|
" y name of the field to be joined.\n",
|
||||||
|
" @param xo candidate table in the join\n",
|
||||||
|
" @param xi candidate table in the join\n",
|
||||||
|
" @param join field by which the tables can be joined.\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" # The set operation will remove redundancies in the field names (not sure it's a good idea)\n",
|
||||||
|
" xo = args['xo']['fields']\n",
|
||||||
|
" xi = args['xi']['fields']\n",
|
||||||
|
" zi = args['xi']['name']\n",
|
||||||
|
" return list(set(xo) | set(['.'.join([args['xi']['name'],name]) for name in xi if name != args['join']]) )\n",
|
||||||
|
"def generate_sql(**args):\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" This function will generate the SQL query for the resulting join\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" xo = args['xo']\n",
|
||||||
|
" xi = args['xi']\n",
|
||||||
|
" sql = \"SELECT :fields FROM :xo.name INNER JOIN :xi.name ON :xi.name.:xi.y = :xo.y \"\n",
|
||||||
|
" fields = \",\".join(get_fields(xo=xi,xi=xi,join=xi['y']))\n",
|
||||||
|
" \n",
|
||||||
|
" \n",
|
||||||
|
" sql = sql.replace(\":fields\",fields).replace(\":xo.name\",xo['name']).replace(\":xi.name\",xi['name'])\n",
|
||||||
|
" sql = sql.replace(\":xi.y\",xi['y']).replace(\":xo.y\",xo['y'])\n",
|
||||||
|
" return sql\n",
|
||||||
|
" \n",
|
||||||
|
" "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 54,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"['person_id',\n",
|
||||||
|
" 'measurements.value_as_number',\n",
|
||||||
|
" 'date_of_birth',\n",
|
||||||
|
" 'race',\n",
|
||||||
|
" 'measurements.value_source_value']"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 54,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"xo = {\"name\":\"person\",\"fields\":['person_id','date_of_birth','race']}\n",
|
||||||
|
"xi = {\"name\":\"measurements\",\"fields\":['person_id','value_as_number','value_source_value']}\n",
|
||||||
|
"get_fields(xo=xo,xi=xi,join=\"person_id\")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 55,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"'SELECT person_id,value_as_number,measurements.value_source_value,measurements.value_as_number,value_source_value FROM person INNER JOIN measurements ON measurements.person_id = person_id '"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 55,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"xo = {\"name\":\"person\",\"fields\":['person_id','date_of_birth','race'],\"y\":\"person_id\"}\n",
|
||||||
|
"xi = {\"name\":\"measurements\",\"fields\":['person_id','value_as_number','value_source_value'],\"y\":\"person_id\"}\n",
|
||||||
|
"generate_sql(xo=xo,xi=xi)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 59,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"[('a', 'b'), ('a', 'c'), ('b', 'c')]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 59,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"\"\"\"\n",
|
||||||
|
" We are designing a process that will take two tables that will generate \n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"import itertools\n",
|
||||||
|
"list(itertools.combinations(['a','b','c'],2))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 87,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"TableReference(DatasetReference(u'aou-res-deid-vumc-test', u'raw'), 'care_site')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 87,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"ref = client.dataset('raw')\n",
|
||||||
|
"tables = list(client.list_tables(ref))\n",
|
||||||
|
"names = [table.table_id for table in tables]\n",
|
||||||
|
"(tables[0].reference)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 85,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"(u'care_site',\n",
|
||||||
|
" u'concept',\n",
|
||||||
|
" u'concept_ancestor',\n",
|
||||||
|
" u'concept_class',\n",
|
||||||
|
" u'concept_relationship',\n",
|
||||||
|
" u'concept_synonym',\n",
|
||||||
|
" u'condition_occurrence',\n",
|
||||||
|
" u'criteria',\n",
|
||||||
|
" u'death',\n",
|
||||||
|
" u'device_exposure',\n",
|
||||||
|
" u'domain',\n",
|
||||||
|
" u'drug_exposure',\n",
|
||||||
|
" u'drug_strength',\n",
|
||||||
|
" u'location',\n",
|
||||||
|
" u'measurement',\n",
|
||||||
|
" u'note',\n",
|
||||||
|
" u'observation',\n",
|
||||||
|
" u'people_seed',\n",
|
||||||
|
" u'person',\n",
|
||||||
|
" u'procedure_occurrence',\n",
|
||||||
|
" u'relationship',\n",
|
||||||
|
" u'visit_occurrence',\n",
|
||||||
|
" u'vocabulary')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 85,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"#\n",
|
||||||
|
"# find every table with person id at the very least or a subset of fields\n",
|
||||||
|
"#\n",
|
||||||
|
"def get_tables\n",
|
||||||
|
"q = ['person_id']\n",
|
||||||
|
"pairs = list(itertools.combinations(names,len(names)))\n",
|
||||||
|
"pairs[0]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 90,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"['a']"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 90,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"list(set(['a','b']) & set(['a']))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": []
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 2",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python2"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 2
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython2",
|
||||||
|
"version": "2.7.15rc1"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 2
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,319 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 66,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import pandas as pd\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"from google.cloud import bigquery as bq\n",
|
||||||
|
"\n",
|
||||||
|
"client = bq.Client.from_service_account_json('/home/steve/dev/google-cloud-sdk/accounts/vumc-test.json')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 33,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"xo = ['person_id','date_of_birth','race']\n",
|
||||||
|
"xi = ['person_id','value_as_number','value_source_value']"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 181,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def get_tables(client,id,fields=[]):\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" getting table lists from google\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" r = []\n",
|
||||||
|
" ref = client.dataset(id)\n",
|
||||||
|
" tables = list(client.list_tables(ref))\n",
|
||||||
|
" for table in tables :\n",
|
||||||
|
" ref = table.reference\n",
|
||||||
|
" schema = client.get_table(ref).schema\n",
|
||||||
|
" names = [f.name for f in schema]\n",
|
||||||
|
" x = list(set(names) & set(fields))\n",
|
||||||
|
" if x :\n",
|
||||||
|
" r.append({\"name\":table.table_id,\"fields\":names})\n",
|
||||||
|
" return r\n",
|
||||||
|
" \n",
|
||||||
|
"def get_fields(**args):\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" This function will generate a random set of fields from two tables. Tables are structured as follows \n",
|
||||||
|
" {name,fields:[],\"y\":}, with \n",
|
||||||
|
" name table name (needed to generate sql query)\n",
|
||||||
|
" fields list of field names, used in the projection\n",
|
||||||
|
" y name of the field to be joined.\n",
|
||||||
|
" @param xo candidate table in the join\n",
|
||||||
|
" @param xi candidate table in the join\n",
|
||||||
|
" @param join field by which the tables can be joined.\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" # The set operation will remove redundancies in the field names (not sure it's a good idea)\n",
|
||||||
|
"# xo = args['xo']['fields']\n",
|
||||||
|
"# xi = args['xi']['fields']\n",
|
||||||
|
"# zi = args['xi']['name']\n",
|
||||||
|
"# return list(set([ \".\".join([args['xo']['name'],name]) for name in xo]) | set(['.'.join([args['xi']['name'],name]) for name in xi if name != args['join']]) )\n",
|
||||||
|
" xo = args['xo']\n",
|
||||||
|
" fields = [\".\".join([args['xo']['name'],name]) for name in args['xo']['fields']]\n",
|
||||||
|
" if not isinstance(args['xi'],list) :\n",
|
||||||
|
" x_ = [args['xi']]\n",
|
||||||
|
" else:\n",
|
||||||
|
" x_ = args['xi']\n",
|
||||||
|
" for xi in x_ :\n",
|
||||||
|
" fields += (['.'.join([xi['name'],name]) for name in xi['fields'] if name != args['join']])\n",
|
||||||
|
" return fields\n",
|
||||||
|
"def generate_sql(**args):\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" This function will generate the SQL query for the resulting join\n",
|
||||||
|
" \"\"\"\n",
|
||||||
|
" \n",
|
||||||
|
" xo = args['xo']\n",
|
||||||
|
" x_ = args['xi']\n",
|
||||||
|
" xo_name = \".\".join([args['prefix'],xo['name'] ]) if 'prefix' in args else xo['name']\n",
|
||||||
|
" SQL = \"SELECT :fields FROM :xo.name \".replace(\":xo.name\",xo_name)\n",
|
||||||
|
" if not isinstance(x_,list):\n",
|
||||||
|
" x_ = [x_]\n",
|
||||||
|
" f = []#[\".\".join([args['xo']['name'],args['join']] )] \n",
|
||||||
|
" INNER_JOINS = []\n",
|
||||||
|
" for xi in x_ :\n",
|
||||||
|
" xi_name = \".\".join([args['prefix'],xi['name'] ]) if 'prefix' in args else xi['name']\n",
|
||||||
|
" JOIN_SQL = \"INNER JOIN :xi.name ON \".replace(':xi.name',xi_name)\n",
|
||||||
|
" value = \".\".join([xi['name'],args['join']])\n",
|
||||||
|
" f.append(value) \n",
|
||||||
|
" \n",
|
||||||
|
" ON_SQL = \"\"\n",
|
||||||
|
" tmp = []\n",
|
||||||
|
" for term in f :\n",
|
||||||
|
" ON_SQL = \":xi.name.:ofield = :xo.name.:ofield\".replace(\":xo.name\",xo['name'])\n",
|
||||||
|
" ON_SQL = ON_SQL.replace(\":xi.name.:ofield\",term).replace(\":ofield\",args['join'])\n",
|
||||||
|
" tmp.append(ON_SQL)\n",
|
||||||
|
" INNER_JOINS += [JOIN_SQL + \" AND \".join(tmp)]\n",
|
||||||
|
" return SQL + \" \".join(INNER_JOINS)\n",
|
||||||
|
" \n",
|
||||||
|
"# sql = \"SELECT :fields FROM :xo.name INNER JOIN :xi.name ON :xi.name.:xi.y = :xo.y \"\n",
|
||||||
|
"# fields = \",\".join(get_fields(xo=xi,xi=xi,join=xi['y']))\n",
|
||||||
|
" \n",
|
||||||
|
" \n",
|
||||||
|
"# sql = sql.replace(\":fields\",fields).replace(\":xo.name\",xo['name']).replace(\":xi.name\",xi['name'])\n",
|
||||||
|
"# sql = sql.replace(\":xi.y\",xi['y']).replace(\":xo.y\",xo['y'])\n",
|
||||||
|
"# return sql\n",
|
||||||
|
" \n",
|
||||||
|
" "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 183,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"'SELECT :fields FROM raw.person INNER JOIN raw.measurement ON measurement.person_id = person.person_id'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 183,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"xo = {\"name\":\"person\",\"fields\":['person_id','date_of_birth','race']}\n",
|
||||||
|
"xi = [{\"name\":\"measurement\",\"fields\":['person_id','value_as_number','value_source_value']}] #,{\"name\":\"observation\",\"fields\":[\"person_id\",\"value_as_string\",\"observation_source_value\"]}]\n",
|
||||||
|
"generate_sql(xo=xo,xi=xi,join=\"person_id\",prefix='raw')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 55,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"'SELECT person_id,value_as_number,measurements.value_source_value,measurements.value_as_number,value_source_value FROM person INNER JOIN measurements ON measurements.person_id = person_id '"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 55,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"xo = {\"name\":\"person\",\"fields\":['person_id','date_of_birth','race'],\"y\":\"person_id\"}\n",
|
||||||
|
"xi = {\"name\":\"measurements\",\"fields\":['person_id','value_as_number','value_source_value'],\"y\":\"person_id\"}\n",
|
||||||
|
"generate_sql(xo=xo,xi=xi)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 59,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"[('a', 'b'), ('a', 'c'), ('b', 'c')]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 59,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"\"\"\"\n",
|
||||||
|
" We are designing a process that will take two tables that will generate \n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"import itertools\n",
|
||||||
|
"list(itertools.combinations(['a','b','c'],2))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 111,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"[u'condition_occurrence.condition_occurrence_id',\n",
|
||||||
|
" u'condition_occurrence.person_id',\n",
|
||||||
|
" u'condition_occurrence.condition_concept_id',\n",
|
||||||
|
" u'condition_occurrence.condition_start_date',\n",
|
||||||
|
" u'condition_occurrence.condition_start_datetime',\n",
|
||||||
|
" u'condition_occurrence.condition_end_date',\n",
|
||||||
|
" u'condition_occurrence.condition_end_datetime',\n",
|
||||||
|
" u'condition_occurrence.condition_type_concept_id',\n",
|
||||||
|
" u'condition_occurrence.stop_reason',\n",
|
||||||
|
" u'condition_occurrence.provider_id',\n",
|
||||||
|
" u'condition_occurrence.visit_occurrence_id',\n",
|
||||||
|
" u'condition_occurrence.condition_source_value',\n",
|
||||||
|
" u'condition_occurrence.condition_source_concept_id',\n",
|
||||||
|
" u'death.death_date',\n",
|
||||||
|
" u'death.death_datetime',\n",
|
||||||
|
" u'death.death_type_concept_id',\n",
|
||||||
|
" u'death.cause_concept_id',\n",
|
||||||
|
" u'death.cause_source_value',\n",
|
||||||
|
" u'death.cause_source_concept_id',\n",
|
||||||
|
" u'device_exposure.device_exposure_id',\n",
|
||||||
|
" u'device_exposure.device_concept_id',\n",
|
||||||
|
" u'device_exposure.device_exposure_start_date',\n",
|
||||||
|
" u'device_exposure.device_exposure_start_datetime',\n",
|
||||||
|
" u'device_exposure.device_exposure_end_date',\n",
|
||||||
|
" u'device_exposure.device_exposure_end_datetime',\n",
|
||||||
|
" u'device_exposure.device_type_concept_id',\n",
|
||||||
|
" u'device_exposure.unique_device_id',\n",
|
||||||
|
" u'device_exposure.quantity',\n",
|
||||||
|
" u'device_exposure.provider_id',\n",
|
||||||
|
" u'device_exposure.visit_occurrence_id',\n",
|
||||||
|
" u'device_exposure.device_source_value',\n",
|
||||||
|
" u'device_exposure.device_source_concept_id',\n",
|
||||||
|
" u'drug_exposure.drug_exposure_id',\n",
|
||||||
|
" u'drug_exposure.drug_concept_id',\n",
|
||||||
|
" u'drug_exposure.drug_exposure_start_date',\n",
|
||||||
|
" u'drug_exposure.drug_exposure_start_datetime',\n",
|
||||||
|
" u'drug_exposure.drug_exposure_end_date',\n",
|
||||||
|
" u'drug_exposure.drug_exposure_end_datetime',\n",
|
||||||
|
" u'drug_exposure.drug_type_concept_id',\n",
|
||||||
|
" u'drug_exposure.stop_reason',\n",
|
||||||
|
" u'drug_exposure.refills',\n",
|
||||||
|
" u'drug_exposure.quantity',\n",
|
||||||
|
" u'drug_exposure.days_supply',\n",
|
||||||
|
" u'drug_exposure.sig',\n",
|
||||||
|
" u'drug_exposure.route_concept_id',\n",
|
||||||
|
" u'drug_exposure.effective_drug_dose',\n",
|
||||||
|
" u'drug_exposure.dose_unit_concept_id',\n",
|
||||||
|
" u'drug_exposure.lot_number',\n",
|
||||||
|
" u'drug_exposure.provider_id',\n",
|
||||||
|
" u'drug_exposure.visit_occurrence_id',\n",
|
||||||
|
" u'drug_exposure.drug_source_value',\n",
|
||||||
|
" u'drug_exposure.drug_source_concept_id',\n",
|
||||||
|
" u'drug_exposure.route_source_value',\n",
|
||||||
|
" u'drug_exposure.dose_unit_source_value']"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 111,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"#\n",
|
||||||
|
"# find every table with person id at the very least or a subset of fields\n",
|
||||||
|
"#\n",
|
||||||
|
"info = get_tables(client,'raw',['person_id'])\n",
|
||||||
|
"# get_fields(xo=names[0],xi=names[1:4],join='person_id')\n",
|
||||||
|
"\n",
|
||||||
|
"# q = ['person_id']\n",
|
||||||
|
"# pairs = list(itertools.combinations(names,len(names)))\n",
|
||||||
|
"# pairs[0]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 90,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"['a']"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 90,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"list(set(['a','b']) & set(['a']))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 120,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"x_ = 1"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": []
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 2",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python2"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 2
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython2",
|
||||||
|
"version": "2.7.15rc1"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 2
|
||||||
|
}
|
||||||
Loading…
Reference in New Issue