querying-for-documents-on-an-array-field.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pymongo import MongoClient\n",
    "import pprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We're just reading data, so we can use the course cluster\n",
    "client = MongoClient('mongodb://analytics-student:analytics-password@cluster0-shard-00-00-jxeqq.mongodb.net:27017,cluster0-shard-00-01-jxeqq.mongodb.net:27017,cluster0-shard-00-02-jxeqq.mongodb.net:27017/?ssl=true&replicaSet=Cluster0-shard-0&authSource=admin')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We'll be using two different collections this time around\n",
    "movies = client.mflix.movies\n",
    "surveys = client.results.surveys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace XXXX with a filter document that will find the movies where \"Harrison Ford\" is a member of the cast\n",
    "movie_filter_doc = {\"cast\" : \"Harrison Ford\" }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This is the first part of the answer to the lab\n",
    "movies.find(movie_filter_doc).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace YYYY with a filter document to find the survey results where the \"abc\" product scored greater than 6\n",
    "survey_filter_doc =  { \"results\": { \"$elemMatch\": { \"product\": \"abc\", \"score\": { \"$gt\": 6 } } } }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "295"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This is the second part of the answer to the lab\n",
    "surveys.find(survey_filter_doc).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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