data_analysis.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "data_analysis.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#Data Analysis\n",
        "This notebooks contains some sample queries with output to showcase the use case of the capstone data infrastructure."
      ],
      "metadata": {
        "id": "_uDyFBYcVyHp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import psycopg2"
      ],
      "metadata": {
        "id": "kGDzYN4PWwAU"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "3VljzemzVpZ1"
      },
      "outputs": [],
      "source": [
        "host = \"\"\n",
        "dbname = \"dev\"\n",
        "user = \"awsuser\"\n",
        "password = \"\"\n",
        "port = 5439"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "conn = psycopg2.connect(f\"host={host} port={port} dbname={dbname} user={user} password={password}\")\n",
        "cur = conn.cursor()"
      ],
      "metadata": {
        "id": "ZX20kU9XblDx"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "schema_query = \"\"\"\n",
        "select n.nspname as table_schema,\n",
        "       c.relname as table_name,\n",
        "       c.reltuples as rows\n",
        "from pg_class c\n",
        "join pg_namespace n on n.oid = c.relnamespace\n",
        "where c.relkind = 'r'\n",
        "      and n.nspname not in ('information_schema','pg_catalog')\n",
        "order by c.reltuples desc;\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "fpJIljg7u_xx"
      },
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(schema_query)\n",
        "cur.fetchall()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aoSVoEAzvEg0",
        "outputId": "b8a938b9-46b2-42cc-a5a9-fe181aa2be6d"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('public', 'fact_event_attributes', 2231740.0),\n",
              " ('public', 'fact_events', 930624.0),\n",
              " ('public', 'staging_events', 930408.0),\n",
              " ('public', 'dim_players', 1055.0),\n",
              " ('public', 'staging_players', 1055.0),\n",
              " ('public', 'dim_matches', 243.0),\n",
              " ('public', 'staging_matches', 243.0),\n",
              " ('public', 'dim_type_attributes', 112.0),\n",
              " ('public', 'dim_types', 35.0),\n",
              " ('public', 'dim_teams', 31.0),\n",
              " ('pg_internal', 'redshift_auto_health_check_4298753', 0.001)]"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Average number of events & attributes per match\n"
      ],
      "metadata": {
        "id": "W6Q9-9iYJsEK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "number_matches = \"\"\"\n",
        "SELECT \n",
        "count(match_id) \n",
        "FROM dim_matches;\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "k80Zkq-OJpVi"
      },
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(number_matches)\n",
        "res_number_matches = cur.fetchone()\n",
        "print(f\"Number of matches: {res_number_matches[0]}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4RfO33YzLH7y",
        "outputId": "2170a6d2-9445-4f77-f5e7-43947806ce67"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of matches: 243\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "avg_events = \"\"\"\n",
        "SELECT avg(event_count) \n",
        "FROM (\n",
        "\tSELECT count(event.event_id) AS event_count\n",
        "\tFROM fact_events AS event\n",
        "\tGROUP BY match_id\n",
        ")\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "OLD1vwF6L74I"
      },
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(avg_events)\n",
        "res_avg_events = cur.fetchone()\n",
        "print(f\"Average events per match: {res_avg_events[0]}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P0yrgAfaMDPQ",
        "outputId": "af073568-23cc-45b2-d09a-d7ae3561c3ae"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average events per match: 3829\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "avg_attributes = \"\"\"\n",
        "SELECT avg(attribute_count) \n",
        "FROM (\n",
        "\tSELECT count(event_attribute.event_attribute_id) AS attribute_count\n",
        "\tFROM fact_event_attributes AS event_attribute\n",
        "\tLEFT JOIN fact_events AS event\n",
        "\tON event.event_id = event_attribute.event_id\n",
        "\tGROUP BY event.match_id\n",
        ")\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "kAW-nTU-MSnX"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(avg_attributes)\n",
        "res_avg_attributes = cur.fetchone()\n",
        "print(f\"Average attributes per match: {res_avg_attributes[0]}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c9007KixNHi7",
        "outputId": "5a9e1eba-8a73-44c5-e0b2-00c41db69d80"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average attributes per match: 9186\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Top 10 Goalscorers"
      ],
      "metadata": {
        "id": "dtKg7psFAjVN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "topscorer_query = \"\"\"\n",
        "SELECT\n",
        "count(event.event_id) as number_goals,\n",
        "  player.player_name as player\n",
        "FROM fact_events as event\n",
        "LEFT JOIN dim_players AS player\n",
        "ON event.player_id = player.player_id\n",
        "LEFT JOIN fact_event_attributes AS attribute\n",
        "ON event.event_id = attribute.event_id\n",
        "WHERE attribute.attribute_name = 'shot.outcome.name'\n",
        "AND attribute.attribute_value = 'Goal'\n",
        "GROUP BY player\n",
        "ORDER BY number_goals DESC\n",
        "LIMIT 10\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "VL3HIbbPb8B6"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(topscorer_query)\n",
        "cur.fetchall()"
      ],
      "metadata": {
        "id": "Cqn8WptNbtqZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ec65ddae-4a5d-4858-c792-920b61ccfab7"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(231, 'Lionel Andrés Messi Cuccittini'),\n",
              " (129, 'Luis Alberto Suárez Díaz'),\n",
              " (47, 'Neymar da Silva Santos Júnior'),\n",
              " (24, 'Ivan Rakitić'),\n",
              " (19, 'Antoine Griezmann'),\n",
              " (16, 'Ousmane Dembélé'),\n",
              " (13, 'Gerard Piqué Bernabéu'),\n",
              " (10, 'Jordi Alba Ramos'),\n",
              " (10, 'Philippe Coutinho Correia'),\n",
              " (9, 'Arturo Erasmo Vidal Pardo')]"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Average passes per game"
      ],
      "metadata": {
        "id": "b-8SHyI4BTbS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "avg_pass = \"\"\"\n",
        "select avg(pass_count) \n",
        "from (\n",
        "\tselect count(event.event_id) as pass_count\n",
        "\tfrom fact_events as event\n",
        "\tleft join dim_types as type\n",
        "\ton event.type_id = type.type_id\n",
        "\twhere type.type_name = 'Pass'\n",
        "\tgroup by match_id\n",
        ")\n",
        "\"\"\"\n"
      ],
      "metadata": {
        "id": "0-2nRJd3BSrv"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(avg_pass)\n",
        "res_avg_passes = cur.fetchone()\n",
        "print(f\"Average passes per match: {res_avg_passes[0]}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GnU-UU5TDn4P",
        "outputId": "d5c86dc7-be6f-4960-adcf-4368264c4470"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average passes per match: 1074\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Dribbling score and avg successfull dribblings"
      ],
      "metadata": {
        "id": "2u4v_xIhermD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "dribbling = \"\"\"\n",
        "SELECT round(avg(cast(dribble_count AS FLOAT)), 2), dribbling, player_name FROM (\n",
        "\tSELECT count(event_attribute_id) AS dribble_count, player.dribbling, player.player_name\n",
        "\tFROM fact_event_attributes AS attribute\n",
        "\tLEFT JOIN fact_events AS event\n",
        "\tON event.event_id = attribute.event_id\n",
        "\tLEFT JOIN dim_players AS player\n",
        "\tON player.player_id = event.player_id\n",
        "\tWHERE attribute_name = 'dribble.outcome.name' \n",
        "\tAND attribute_value='Complete'\n",
        "\tAND player.team_id = 217\n",
        "\t\n",
        "\tGROUP BY event.match_id, player.player_name, player.dribbling\n",
        ")\n",
        "GROUP BY player_name, dribbling\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "DpC-fifRevEt"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cur.execute(dribbling)\n",
        "res_dribbling = cur.fetchall()\n",
        "dribbling_df = pd.DataFrame(res_dribbling)"
      ],
      "metadata": {
        "id": "kDEIvNmcmTzv"
      },
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(figsize=(16, 9))\n",
        "ax.scatter(dribbling_df[0], dribbling_df[1])\n",
        "\n",
        "for i, txt in enumerate(dribbling_df[2]):\n",
        "    ax.annotate(txt, (dribbling_df[0][i], dribbling_df[1][i]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "sqFzSNaan_Cp",
        "outputId": "91e60c57-e929-4216-c83f-9c728bfa1463"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1152x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "conn.close()"
      ],
      "metadata": {
        "id": "oVH8ZO9JUG4r"
      },
      "execution_count": 57,
      "outputs": []
    }
  ]
}