{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Access Public Data from BigQuery\n",
    "\n",
    "This example illustrates how to create a Google cloud credentials object from your Data Observatory enabled CARTO account."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cartoframes.auth import Credentials\n",
    "\n",
    "creds = Credentials.from_file('creds.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from google.oauth2.credentials import Credentials as GoogleCredentials\n",
    "\n",
    "gcloud_project, gcloud_token = creds.get_gcloud_credentials()\n",
    "gcloud_credentials = GoogleCredentials(gcloud_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from google.cloud import bigquery, storage\n",
    "\n",
    "bq_client = bigquery.Client(project=gcloud_project, credentials=gcloud_credentials)\n",
    "gcs_client = storage.Client(project=gcloud_project, credentials=gcloud_credentials)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As an example, the following code shows how to use the Google BigQuery client to access to a public dataset from Data Observatory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cartoframes.data.observatory import Dataset\n",
    "\n",
    "dataset = Dataset.get('acs_sociodemogr_8c2655e0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'carto-do-public-data.usa_acs.demographics_sociodemographics_usa_county_2015_5yrs_20132017'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "query_job = bq_client.query('SELECT * FROM `{}` LIMIT 1'.format(dataset.id))\n",
    "results = query_job.result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[SchemaField('geoid', 'STRING', 'NULLABLE', None, (), None),\n",
       " SchemaField('do_date', 'DATE', 'NULLABLE', None, (), None),\n",
       " SchemaField('total_pop', 'FLOAT', 'NULLABLE', None, (), None)]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.schema[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18025 10598.0\n"
     ]
    }
   ],
   "source": [
    "for row in results:\n",
    "    print(row['geoid'], row['total_pop'])"
   ]
  }
 ],
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