Update notebook

Author: katarinasupe

got-analysis/game-of-graphs.ipynb

@@ -13,10 +13,45 @@
    "id": "b1358e7b",
    "metadata": {},
    "source": [
-    "First, we need to run Memgraph. The easiest way to do this, is to run Memgraph Platform with Docker.\n",
+    "\n",
+    "## Prerequisites <a name=\"prerequisites\"></a>\n",
+    "\n",
+    "For this tutorial, we need to install:\n",
+    "\n",
+    "- [Docker](https://docs.docker.com/get-docker/) - to run Memgraph, since Memgraph is a native Linux application and cannot be installed on Windows and macOS\n",
+    "- [Memgraph Platform](https://memgraph.com/docs/memgraph/installation) - the complete streaming graph application platform; follow the instructions to install Memgraph Platform with Docker for your OS\n",
+    "- [GQLAlchemy](https://pypi.org/project/gqlalchemy/)\n",
+    "\n",
+    "> ### Memgraph Platform installation using Docker\n",
+    ">\n",
+    "> After we install Docker, we can run the Memgraph Platform container by running:\n",
+    ">\n",
+    ">```\n",
+    ">docker run -it -p 7687:7687 -p 7444:7444 -p 3000:3000 memgraph/memgraph-platform\n",
+    ">```\n",
+    ">\n",
+    ">**Memgraph Platform** contains:\n",
+    ">\n",
+    ">- **MemgraphDB** - the database that holds your data\n",
+    ">- **Memgraph Lab** - visual user interface for running queries and visualizing graph data (running at >`localhost:3000`)\n",
+    ">- **mgconsole** - command-line interface for running queries\n",
+    ">- **MAGE** - graph algorithms and modules library\n",
+    "\n",
+    "We will use the **GQLAlchemy**'s object graph mapper (OGM) to connect to Memgraph and quickly execute **Cypher** queries. GQLAlchemy also serves as a Python driver/client for Memgraph. We can install it using:\n",
+    "\n",
     "```\n",
-    "docker run -it -p 7687:7687 -p 7444:7444 -p 3000:3000 memgraph/memgraph-platform\n",
-    "```"
+    "pip install gqlalchemy\n",
+    "```\n",
+    "\n",
+    "> You may need to install [CMake](https://cmake.org/download/) before installing GQLAlchemy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9d6dfef6",
+   "metadata": {},
+   "source": [
+    "## Connect to Memgraph with GQLAlchemy"
    ]
   },
   {
@@ -160,6 +195,8 @@
    "id": "05ebf808",
    "metadata": {},
    "source": [
+    "## Load the dataset\n",
+    "\n",
     "The simplest way to load a dataset into Memgraph is by using **Memgraph Lab** which is currently running on `localhost:3000`. The first thing you're going to see on that address is the **Quick Connect**. You just have to click `Connect`!"
    ]
   },
@@ -299,6 +336,8 @@
    "id": "9a13b90e",
    "metadata": {},
    "source": [
+    "## Map nodes and relationships\n",
+    "\n",
     "We can create a schema for this model inside the Python code by defining the classes that inherit from the `Node` and `Relationship` classes."
    ]
   },
@@ -309,7 +348,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from gqlalchemy import Node, Relationship, Field\n",
+    "from gqlalchemy import Node, Relationship\n",
     "\n",
     "class Character(Node):\n",
     "    name: str\n",
@@ -561,26 +600,29 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Lord Snow']\n"
+      "{'Lord Snow'}\n"
      ]
     }
    ],
    "source": [
+    "season_1 = {'Winter Is Coming ', 'The Kingsroad ', 'Lord Snow', \n",
+    "            'Cripples Bastards and Broken Things ', 'The Wolf and the Lion ', \n",
+    "            'A Golden Crown ', 'You Win or You Die', 'The Pointy End ', \n",
+    "            'Baelor ', 'Fire and Blood'}\n",
+    "\n",
     "results = memgraph.execute_and_fetch(\n",
     "    \"\"\"\n",
     "    MATCH (e:Episode)-[p:PART_OF]->(s:Season {number: 1})\n",
     "    RETURN e;\n",
     "    \"\"\"\n",
     ")\n",
     "\n",
-    "season_1_deaths = []\n",
+    "season_1_deaths = set()\n",
     "\n",
     "for result in results:\n",
-    "    season_1_deaths.append(result[\"e\"].name)\n",
+    "    season_1_deaths.add(result[\"e\"].name)\n",
     "\n",
-    "set_season_1_deaths = set(season_1_deaths)\n",
-    "missing = list(sorted(season_1 - set_season_1_deaths))\n",
-    "print(missing)"
+    "print(season_1 - season_1_deaths)"
    ]
   },
   {
@@ -601,7 +643,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['The Prince of Winterfell']\n"
+      "{'The Prince of Winterfell'}\n"
      ]
     }
    ],
@@ -612,13 +654,12 @@
     "    RETURN e;\n",
     "    \"\"\"\n",
     ")\n",
-    "season_2_deaths = []\n",
+    "season_2_deaths = set()\n",
+    "\n",
     "for result in results:\n",
-    "    season_2_deaths.append(result[\"e\"].name)\n",
+    "    season_2_deaths.add(result[\"e\"].name)\n",
     "\n",
-    "set_season_2_deaths = set(season_2_deaths)\n",
-    "missing_2 = list(sorted(season_2 - set_season_2_deaths))\n",
-    "print(missing_2)"
+    "print(season_2 - season_2_deaths)"
    ]
   },
   {
@@ -639,7 +680,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['The Bear and the Maiden Fair']\n"
+      "{'The Bear and the Maiden Fair'}\n"
      ]
     }
    ],
@@ -650,13 +691,12 @@
     "    RETURN e;\n",
     "    \"\"\"\n",
     ")\n",
-    "season_3_deaths = []\n",
+    "season_3_deaths = set()\n",
+    "\n",
     "for result in results:\n",
-    "    season_3_deaths.append(result[\"e\"].name)\n",
+    "    season_3_deaths.add(result[\"e\"].name)\n",
     "\n",
-    "set_season_3_deaths = set(season_3_deaths)\n",
-    "missing_3 = list(sorted(season_3 - set_season_3_deaths))\n",
-    "print(missing_3)"
+    "print(season_3 - season_3_deaths)"
    ]
   },
   {
@@ -677,7 +717,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Blood of My Blood']\n"
+      "{'Blood of My Blood'}\n"
      ]
     }
    ],
@@ -688,13 +728,12 @@
     "    RETURN e;\n",
     "    \"\"\"\n",
     ")\n",
-    "season_6_deaths = []\n",
+    "season_6_deaths = set()\n",
+    "\n",
     "for result in results:\n",
-    "    season_6_deaths.append(result[\"e\"].name)\n",
+    "    season_6_deaths.add(result[\"e\"].name)\n",
     "\n",
-    "set_season_6_deaths = set(season_6_deaths)\n",
-    "missing_6 = list(sorted(season_6 - set_season_6_deaths))\n",
-    "print(missing_6)"
+    "print(season_6 - season_6_deaths)"
    ]
   },
   {
@@ -1371,16 +1410,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Daenerys Targaryen | BC: 0.2641671685970773\n",
-      "Lannister soldier | BC: 0.11163138590238252\n",
-      "Sons of the Harpy agent | BC: 0.04326120746568804\n",
-      "Jon Snow | BC: 0.041527339730212685\n",
-      "Wildling | BC: 0.03782396045716543\n",
-      "Stark Soldier | BC: 0.028609456095599384\n",
-      "Baratheon of Dragonstone soldier | BC: 0.027533816622595353\n",
-      "Cersei Lannister | BC: 0.02644509282920999\n",
-      "Stark soldier | BC: 0.02432818459201448\n",
-      "Nights Watch brother | BC: 0.022719177729567427\n"
+      "Daenerys Targaryen | BC: 0.26416716859707734\n",
+      "Lannister soldier | BC: 0.11163138590238253\n",
+      "Sons of the Harpy agent | BC: 0.04326120746568793\n",
+      "Jon Snow | BC: 0.04152733973021257\n",
+      "Wildling | BC: 0.037823960457165504\n",
+      "Stark Soldier | BC: 0.02860945609559936\n",
+      "Baratheon of Dragonstone soldier | BC: 0.027533816622595367\n",
+      "Cersei Lannister | BC: 0.026445092829209968\n",
+      "Stark soldier | BC: 0.02432818459201446\n",
+      "Nights Watch brother | BC: 0.02271917772956741\n"
      ]
     }
    ],