project.ipynb

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  "metadata": {
    "colab": {
      "name": "project.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "OyIDILdKERvM",
        "outputId": "2efff12a-de1b-4487-8be2-7578c6128c45"
      },
      "source": [
        "# SESSION 0PLUS TO 10 \n",
        " \n",
        "#imports my google drive into colab\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "from matplotlib.colors import ListedColormap\n",
        "from sklearn.neighbors import kneighbors_graph\n",
        "\n",
        "#import important libraries\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import networkx as nx\n",
        "from sklearn.cluster import SpectralClustering\n",
        "\n",
        "\n",
        "#uses pandas read_csv function to read csv and store in variable; sets the engine to python \n",
        "session010 = pd.read_csv('gdrive/My Drive/sessions_0plus_to_10_metadata.csv', engine='python')\n",
        "\n",
        "#extract specific columns and store in variable df (dataframe)\n",
        "df = pd.DataFrame(session010, columns=['question1', 'question2','likes', 'shared media', 'follows', 'followed_by', 'cyberaggression', 'cyberbullying']\n",
        ")\n",
        "\n",
        "#convert data types of q1 to binary (0 or 1)\n",
        "#agression and bullying instances set to 1\n",
        "df['question1'] = (df['question1'] == 'aggression').mul(1)\n",
        "df['question2'] = (df['question2'] == 'bullying').mul(1)\n",
        "\n",
        "#takes out string from column and changes the type from string to int\n",
        "df['likes'] = df['likes'].map(lambda x: x.rstrip('\\r\\r likes')).astype(int)\n",
        "\n",
        "print(\"--------------------------------------------------------------------------------------------------\")\n",
        "print(\"\\t\\t\\t\\t\\tThis is session_0plus_to_10\")\n",
        "\n",
        "#convert df to numpy array\n",
        "df.to_numpy()\n",
        "\n",
        "df\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive\n",
            "--------------------------------------------------------------------------------------------------\n",
            "\t\t\t\t\tThis is session_0plus_to_10\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>question1</th>\n",
              "      <th>question2</th>\n",
              "      <th>likes</th>\n",
              "      <th>shared media</th>\n",
              "      <th>follows</th>\n",
              "      <th>followed_by</th>\n",
              "      <th>cyberaggression</th>\n",
              "      <th>cyberbullying</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
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              "      <th>1</th>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>108939</td>\n",
              "      <td>698</td>\n",
              "      <td>389</td>\n",
              "      <td>1974089</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>6441</td>\n",
              "      <td>1257</td>\n",
              "      <td>656</td>\n",
              "      <td>349594</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1153</td>\n",
              "      <td>2052</td>\n",
              "      <td>388</td>\n",
              "      <td>60772</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <th>273</th>\n",
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              "      <td>2158</td>\n",
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              "      <td>0</td>\n",
              "      <td>23223</td>\n",
              "      <td>475</td>\n",
              "      <td>93</td>\n",
              "      <td>651132</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
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              "      <th>275</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1033</td>\n",
              "      <td>1208</td>\n",
              "      <td>209</td>\n",
              "      <td>106468</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>278 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     question1  question2   likes  ...  followed_by  cyberaggression  cyberbullying\n",
              "0            0          0    4313  ...        53913                1              0\n",
              "1            0          0    2102  ...       426533                0              0\n",
              "2            0          0  108939  ...      1974089                1              1\n",
              "3            1          1    6441  ...       349594                3              3\n",
              "4            0          0    1153  ...        60772                0              0\n",
              "..         ...        ...     ...  ...          ...              ...            ...\n",
              "273          0          0   11899  ...       360658                0              0\n",
              "274          0          0   23223  ...       651132                2              2\n",
              "275          0          0    1033  ...       106468                0              0\n",
              "276          0          0    2356  ...       297618                0              0\n",
              "277          0          0    1644  ...       197778                0              0\n",
              "\n",
              "[278 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "VSuxHI5Q6jX-",
        "outputId": "16ce733b-ddd6-483b-bbae-860beeb04d5a"
      },
      "source": [
        "#build a list from df columns\n",
        "cols = list(df.columns)\n",
        "df[cols]\n",
        "\n",
        "#for loop that runs z-score on each column and prints it in new column with column name folowed by zscore\n",
        "for col in cols:\n",
        "    col_zscore = col + '_zscore'\n",
        "    df[col_zscore] = (df[col] - df[col].mean())/df[col].std(ddof=0)\n",
        "\n",
        "df"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>question1</th>\n",
              "      <th>question2</th>\n",
              "      <th>likes</th>\n",
              "      <th>shared media</th>\n",
              "      <th>follows</th>\n",
              "      <th>followed_by</th>\n",
              "      <th>cyberaggression</th>\n",
              "      <th>cyberbullying</th>\n",
              "      <th>question1_zscore</th>\n",
              "      <th>question2_zscore</th>\n",
              "      <th>likes_zscore</th>\n",
              "      <th>shared media_zscore</th>\n",
              "      <th>follows_zscore</th>\n",
              "      <th>followed_by_zscore</th>\n",
              "      <th>cyberaggression_zscore</th>\n",
              "      <th>cyberbullying_zscore</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <td>0.537816</td>\n",
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              "      <td>0.191776</td>\n",
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              "      <th>1</th>\n",
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              "      <td>-0.300019</td>\n",
              "      <td>-0.492186</td>\n",
              "      <td>-0.296432</td>\n",
              "      <td>-0.136516</td>\n",
              "      <td>-0.760256</td>\n",
              "      <td>-0.690815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>108939</td>\n",
              "      <td>698</td>\n",
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              "      <td>1</td>\n",
              "      <td>-0.278423</td>\n",
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              "      <td>1.366819</td>\n",
              "      <td>-0.582815</td>\n",
              "      <td>-0.286376</td>\n",
              "      <td>0.501663</td>\n",
              "      <td>0.191776</td>\n",
              "      <td>0.406594</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>6441</td>\n",
              "      <td>1257</td>\n",
              "      <td>656</td>\n",
              "      <td>349594</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3.591657</td>\n",
              "      <td>4.514932</td>\n",
              "      <td>-0.232324</td>\n",
              "      <td>0.221335</td>\n",
              "      <td>-0.017880</td>\n",
              "      <td>-0.168244</td>\n",
              "      <td>2.095841</td>\n",
              "      <td>2.601413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1153</td>\n",
              "      <td>2052</td>\n",
              "      <td>388</td>\n",
              "      <td>60772</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.278423</td>\n",
              "      <td>-0.221487</td>\n",
              "      <td>-0.314825</td>\n",
              "      <td>1.364982</td>\n",
              "      <td>-0.287382</td>\n",
              "      <td>-0.287348</td>\n",
              "      <td>-0.760256</td>\n",
              "      <td>-0.690815</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>273</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>11899</td>\n",
              "      <td>2158</td>\n",
              "      <td>54</td>\n",
              "      <td>360658</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.278423</td>\n",
              "      <td>-0.221487</td>\n",
              "      <td>-0.147170</td>\n",
              "      <td>1.517469</td>\n",
              "      <td>-0.623254</td>\n",
              "      <td>-0.163682</td>\n",
              "      <td>-0.760256</td>\n",
              "      <td>-0.690815</td>\n",
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              "    <tr>\n",
              "      <th>274</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23223</td>\n",
              "      <td>475</td>\n",
              "      <td>93</td>\n",
              "      <td>651132</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>-0.278423</td>\n",
              "      <td>-0.221487</td>\n",
              "      <td>0.029504</td>\n",
              "      <td>-0.903611</td>\n",
              "      <td>-0.584035</td>\n",
              "      <td>-0.043896</td>\n",
              "      <td>1.143809</td>\n",
              "      <td>1.504003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>275</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1033</td>\n",
              "      <td>1208</td>\n",
              "      <td>209</td>\n",
              "      <td>106468</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.278423</td>\n",
              "      <td>-0.221487</td>\n",
              "      <td>-0.316698</td>\n",
              "      <td>0.150846</td>\n",
              "      <td>-0.467385</td>\n",
              "      <td>-0.268504</td>\n",
              "      <td>-0.760256</td>\n",
              "      <td>-0.690815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>276</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2356</td>\n",
              "      <td>858</td>\n",
              "      <td>873</td>\n",
              "      <td>297618</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.278423</td>\n",
              "      <td>-0.221487</td>\n",
              "      <td>-0.296056</td>\n",
              "      <td>-0.352647</td>\n",
              "      <td>0.200336</td>\n",
              "      <td>-0.189678</td>\n",
              "      <td>-0.760256</td>\n",
              "      <td>-0.690815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>277</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1644</td>\n",
              "      <td>1702</td>\n",
              "      <td>1968</td>\n",
              "      <td>197778</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.278423</td>\n",
              "      <td>-0.221487</td>\n",
              "      <td>-0.307165</td>\n",
              "      <td>0.861490</td>\n",
              "      <td>1.301472</td>\n",
              "      <td>-0.230850</td>\n",
              "      <td>-0.760256</td>\n",
              "      <td>-0.690815</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>278 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     question1  question2  ...  cyberaggression_zscore  cyberbullying_zscore\n",
              "0            0          0  ...                0.191776             -0.690815\n",
              "1            0          0  ...               -0.760256             -0.690815\n",
              "2            0          0  ...                0.191776              0.406594\n",
              "3            1          1  ...                2.095841              2.601413\n",
              "4            0          0  ...               -0.760256             -0.690815\n",
              "..         ...        ...  ...                     ...                   ...\n",
              "273          0          0  ...               -0.760256             -0.690815\n",
              "274          0          0  ...                1.143809              1.504003\n",
              "275          0          0  ...               -0.760256             -0.690815\n",
              "276          0          0  ...               -0.760256             -0.690815\n",
              "277          0          0  ...               -0.760256             -0.690815\n",
              "\n",
              "[278 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lex8Od7T6llZ",
        "outputId": "2de0fb45-65d8-47f3-af4a-66f88a99dec8"
      },
      "source": [
        "#knn graph\n",
        "A = kneighbors_graph(df, 5, mode='connectivity', include_self=True).toarray()\n",
        "A\n",
        "\n",
        "#clustering = SpectralClustering(n_clusters=5, affinity='precomputed', n_init=100, assign_labels='discretize')\n",
        "#clustering.fit_predict(A)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 1., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 1., ..., 0., 0., 0.],\n",
              "       ...,\n",
              "       [0., 0., 0., ..., 1., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 1., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 1.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "JYhx5ntRMT5F",
        "outputId": "5d8e2698-06ba-4616-dfd9-9d0333ef86f9"
      },
      "source": [
        "# SESSION 10PLUS TO 40\n",
        "\n",
        "#imports my google drive into colab\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "from matplotlib.colors import ListedColormap\n",
        "from sklearn.neighbors import kneighbors_graph\n",
        "\n",
        "#import important libraries\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import networkx as nx\n",
        "from sklearn.cluster import SpectralClustering\n",
        "\n",
        "#uses pandas read_csv function to read csv and store in variable; sets the engine to python \n",
        "session1040 = pd.read_csv('gdrive/My Drive/sessions_10plus_to_40_metadata.csv', engine='python')\n",
        "\n",
        "#extract specific columns and store in variable df (dataframe)\n",
        "df = pd.DataFrame(session1040, columns=['question1', 'question2','likes', 'shared media', 'follows', 'followed_by', 'cyberaggression', 'cyberbullying']\n",
        ")\n",
        "\n",
        "#convert data types of q1 to binary (0 or 1)\n",
        "#agression and bullying instances set to 1\n",
        "df['question1'] = (df['question1'] == 'aggression').mul(1)\n",
        "df['question2'] = (df['question2'] == 'bullying').mul(1)\n",
        "\n",
        "#takes out string from column and changes the type from string to int\n",
        "df['likes'] = df['likes'].map(lambda x: x.rstrip('\\r\\r likes')).astype(int)\n",
        "\n",
        "print(\"--------------------------------------------------------------------------------------------------\")\n",
        "print(\"\\t\\t\\t\\t\\tThis is session_10plus_to_40\")\n",
        "\n",
        "#convert df to numpy array\n",
        "df.to_numpy()\n",
        "\n",
        "df"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n",
            "--------------------------------------------------------------------------------------------------\n",
            "\t\t\t\t\tThis is session_10plus_to_40\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>question1</th>\n",
              "      <th>question2</th>\n",
              "      <th>likes</th>\n",
              "      <th>shared media</th>\n",
              "      <th>follows</th>\n",
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              "      <th>0</th>\n",
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              "      <td>1</td>\n",
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              "      <th>1</th>\n",
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              "      <td>1143</td>\n",
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              "      <td>1439385</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
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              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1318</td>\n",
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              "      <td>4</td>\n",
              "      <td>4</td>\n",
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              "      <th>1015</th>\n",
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              "      <td>1101</td>\n",
              "      <td>1434</td>\n",
              "      <td>100</td>\n",
              "      <td>222247</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>1018 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      question1  question2  likes  ...  followed_by  cyberaggression  cyberbullying\n",
              "0             0          0    703  ...       134980                1              1\n",
              "1             0          0   1810  ...        50067                2              2\n",
              "2             1          0   5229  ...       331599                3              2\n",
              "3             1          1  16341  ...      1439385                4              4\n",
              "4             1          1  21623  ...       470346                4              4\n",
              "...         ...        ...    ...  ...          ...              ...            ...\n",
              "1013          0          0     17  ...        58274                1              1\n",
              "1014          1          1   1202  ...        56421                4              4\n",
              "1015          0          0   1101  ...       222247                0              0\n",
              "1016          0          0    435  ...         3757                0              0\n",
              "1017          0          0   7455  ...      2526016                1              1\n",
              "\n",
              "[1018 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "wRM92F60eVIp",
        "outputId": "bd1a3354-0bce-49aa-c354-20ae11fdf1bf"
      },
      "source": [
        "#build a list from df columns\n",
        "cols = list(df.columns)\n",
        "df[cols]\n",
        "\n",
        "#for loop that runs z-score on each column and prints it in new column with column name folowed by zscore\n",
        "for col in cols:\n",
        "    col_zscore = col + '_zscore'\n",
        "    df[col_zscore] = (df[col] - df[col].mean())/df[col].std(ddof=0)\n",
        "\n",
        "df"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>question1</th>\n",
              "      <th>question2</th>\n",
              "      <th>likes</th>\n",
              "      <th>shared media</th>\n",
              "      <th>follows</th>\n",
              "      <th>followed_by</th>\n",
              "      <th>cyberaggression</th>\n",
              "      <th>cyberbullying</th>\n",
              "      <th>question1_zscore</th>\n",
              "      <th>question2_zscore</th>\n",
              "      <th>likes_zscore</th>\n",
              "      <th>shared media_zscore</th>\n",
              "      <th>follows_zscore</th>\n",
              "      <th>followed_by_zscore</th>\n",
              "      <th>cyberaggression_zscore</th>\n",
              "      <th>cyberbullying_zscore</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <td>-0.553248</td>\n",
              "      <td>0.153819</td>\n",
              "      <td>0.591345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5229</td>\n",
              "      <td>1466</td>\n",
              "      <td>731</td>\n",
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              "      <td>0.806267</td>\n",
              "      <td>0.591345</td>\n",
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              "      <th>3</th>\n",
              "      <td>1</td>\n",
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              "      <td>16341</td>\n",
              "      <td>1143</td>\n",
              "      <td>103</td>\n",
              "      <td>1439385</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>1.514760</td>\n",
              "      <td>2.108044</td>\n",
              "      <td>0.368938</td>\n",
              "      <td>-0.015189</td>\n",
              "      <td>-0.523328</td>\n",
              "      <td>1.081570</td>\n",
              "      <td>1.458715</td>\n",
              "      <td>2.140868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>21623</td>\n",
              "      <td>1318</td>\n",
              "      <td>170</td>\n",
              "      <td>470346</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>1.514760</td>\n",
              "      <td>2.108044</td>\n",
              "      <td>0.649702</td>\n",
              "      <td>0.265770</td>\n",
              "      <td>-0.443134</td>\n",
              "      <td>-0.058704</td>\n",
              "      <td>1.458715</td>\n",
              "      <td>2.140868</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1013</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>17</td>\n",
              "      <td>2519</td>\n",
              "      <td>573</td>\n",
              "      <td>58274</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.660171</td>\n",
              "      <td>-0.474373</td>\n",
              "      <td>-0.498759</td>\n",
              "      <td>2.193950</td>\n",
              "      <td>0.039229</td>\n",
              "      <td>-0.543591</td>\n",
              "      <td>-0.498629</td>\n",
              "      <td>-0.183416</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1014</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1202</td>\n",
              "      <td>1452</td>\n",
              "      <td>435</td>\n",
              "      <td>56421</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>1.514760</td>\n",
              "      <td>2.108044</td>\n",
              "      <td>-0.435771</td>\n",
              "      <td>0.480904</td>\n",
              "      <td>-0.125947</td>\n",
              "      <td>-0.545771</td>\n",
              "      <td>1.458715</td>\n",
              "      <td>2.140868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1015</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1101</td>\n",
              "      <td>1434</td>\n",
              "      <td>100</td>\n",
              "      <td>222247</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.660171</td>\n",
              "      <td>-0.474373</td>\n",
              "      <td>-0.441140</td>\n",
              "      <td>0.452005</td>\n",
              "      <td>-0.526919</td>\n",
              "      <td>-0.350643</td>\n",
              "      <td>-1.151078</td>\n",
              "      <td>-0.958177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1016</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>435</td>\n",
              "      <td>441</td>\n",
              "      <td>129</td>\n",
              "      <td>3757</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.660171</td>\n",
              "      <td>-0.474373</td>\n",
              "      <td>-0.476541</td>\n",
              "      <td>-1.142235</td>\n",
              "      <td>-0.492208</td>\n",
              "      <td>-0.607741</td>\n",
              "      <td>-1.151078</td>\n",
              "      <td>-0.958177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1017</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7455</td>\n",
              "      <td>436</td>\n",
              "      <td>520</td>\n",
              "      <td>2526016</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.660171</td>\n",
              "      <td>-0.474373</td>\n",
              "      <td>-0.103394</td>\n",
              "      <td>-1.150262</td>\n",
              "      <td>-0.024208</td>\n",
              "      <td>2.360214</td>\n",
              "      <td>-0.498629</td>\n",
              "      <td>-0.183416</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1018 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      question1  question2  ...  cyberaggression_zscore  cyberbullying_zscore\n",
              "0             0          0  ...               -0.498629             -0.183416\n",
              "1             0          0  ...                0.153819              0.591345\n",
              "2             1          0  ...                0.806267              0.591345\n",
              "3             1          1  ...                1.458715              2.140868\n",
              "4             1          1  ...                1.458715              2.140868\n",
              "...         ...        ...  ...                     ...                   ...\n",
              "1013          0          0  ...               -0.498629             -0.183416\n",
              "1014          1          1  ...                1.458715              2.140868\n",
              "1015          0          0  ...               -1.151078             -0.958177\n",
              "1016          0          0  ...               -1.151078             -0.958177\n",
              "1017          0          0  ...               -0.498629             -0.183416\n",
              "\n",
              "[1018 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bX8YWIuZKT49",
        "outputId": "24443d0a-3118-4162-86df-9d821fb7cfd8"
      },
      "source": [
        "#knn graph\n",
        "A = kneighbors_graph(df, 5, mode='connectivity', include_self=True).toarray()\n",
        "A\n",
        "\n",
        "#clustering = SpectralClustering(n_clusters=5, affinity='precomputed', n_init=100, assign_labels='discretize')\n",
        "#clustering.fit_predict(A)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 1., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 1., ..., 0., 0., 0.],\n",
              "       ...,\n",
              "       [0., 0., 0., ..., 1., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 1., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 1.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "lXg0ZRWpH5ZZ",
        "outputId": "705624ed-f76e-4cfd-bdc2-fa3c2a16de99"
      },
      "source": [
        "#SESSION 40PLUS\n",
        "\n",
        "#imports my google drive into colab\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "import pandas as pd\n",
        "\n",
        "#uses pandas read_csv function to read csv and store in variable; sets the engine to python \n",
        "session40 = pd.read_csv('gdrive/My Drive/sessions_40plus_metadata.csv', engine='python')\n",
        "\n",
        "#extract specific columns and store in variable df (dataframe)\n",
        "df = pd.DataFrame(session40, columns=['question1', 'question2','likes', 'shared media', 'follows', 'followed_by', 'cyberaggression', 'cyberbullying']\n",
        ")\n",
        "\n",
        "#convert data types of q1 to binary (0 or 1)\n",
        "#agression and bullying instances set to 1\n",
        "df['question1'] = (df['question1'] == 'aggression').mul(1)\n",
        "df['question2'] = (df['question2'] == 'bullying').mul(1)\n",
        "\n",
        "#takes out string from column and changes the type from string to int\n",
        "df['likes'] = df['likes'].map(lambda x: x.rstrip('\\r\\r likes')).astype(int)\n",
        "\n",
        "#convert df to numpy array\n",
        "df.to_numpy()\n",
        "\n",
        "df"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>question1</th>\n",
              "      <th>question2</th>\n",
              "      <th>likes</th>\n",
              "      <th>shared media</th>\n",
              "      <th>follows</th>\n",
              "      <th>followed_by</th>\n",
              "      <th>cyberaggression</th>\n",
              "      <th>cyberbullying</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>196</td>\n",
              "      <td>189</td>\n",
              "      <td>6117</td>\n",
              "      <td>95224</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>570</td>\n",
              "      <td>1341</td>\n",
              "      <td>193</td>\n",
              "      <td>61385</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>44</td>\n",
              "      <td>945</td>\n",
              "      <td>1071</td>\n",
              "      <td>50710</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1381</td>\n",
              "      <td>711</td>\n",
              "      <td>272</td>\n",
              "      <td>1905124</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1936</td>\n",
              "      <td>443</td>\n",
              "      <td>427</td>\n",
              "      <td>532939</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>917</th>\n",
              "      <td>1</td>\n",
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              "      <td>442</td>\n",
              "      <td>1607</td>\n",
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              "      <td>24257</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>918</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>196</td>\n",
              "      <td>2204</td>\n",
              "      <td>741</td>\n",
              "      <td>7457</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>919</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>50</td>\n",
              "      <td>1905</td>\n",
              "      <td>261</td>\n",
              "      <td>1180</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>920</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>454</td>\n",
              "      <td>319</td>\n",
              "      <td>485</td>\n",
              "      <td>14265</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>921</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>37734</td>\n",
              "      <td>2009</td>\n",
              "      <td>318</td>\n",
              "      <td>888292</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>922 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     question1  question2  likes  ...  followed_by  cyberaggression  cyberbullying\n",
              "0            1          1    196  ...        95224                5              5\n",
              "1            1          1    570  ...        61385                5              3\n",
              "2            1          1     44  ...        50710                5              5\n",
              "3            1          1   1381  ...      1905124                4              3\n",
              "4            1          1   1936  ...       532939                5              5\n",
              "..         ...        ...    ...  ...          ...              ...            ...\n",
              "917          1          0    442  ...        24257                4              1\n",
              "918          0          0    196  ...         7457                0              0\n",
              "919          1          0     50  ...         1180                3              2\n",
              "920          1          0    454  ...        14265                3              2\n",
              "921          1          1  37734  ...       888292                5              5\n",
              "\n",
              "[922 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "9FnE75U3gRMe",
        "outputId": "3becc7f6-fd21-441a-87f5-d3bde2c3bcae"
      },
      "source": [
        "#build a list from df columns\n",
        "cols = list(df.columns)\n",
        "df[cols]\n",
        "\n",
        "#for loop that runs z-score on each column and prints it in new column with column name folowed by zscore\n",
        "for col in cols:\n",
        "    col_zscore = col + '_zscore'\n",
        "    df[col_zscore] = (df[col] - df[col].mean())/df[col].std(ddof=0)\n",
        "\n",
        "df"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>question1</th>\n",
              "      <th>question2</th>\n",
              "      <th>likes</th>\n",
              "      <th>shared media</th>\n",
              "      <th>follows</th>\n",
              "      <th>followed_by</th>\n",
              "      <th>cyberaggression</th>\n",
              "      <th>cyberbullying</th>\n",
              "      <th>question1_zscore</th>\n",
              "      <th>question2_zscore</th>\n",
              "      <th>likes_zscore</th>\n",
              "      <th>shared media_zscore</th>\n",
              "      <th>follows_zscore</th>\n",
              "      <th>followed_by_zscore</th>\n",
              "      <th>cyberaggression_zscore</th>\n",
              "      <th>cyberbullying_zscore</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>196</td>\n",
              "      <td>189</td>\n",
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              "      <td>0.732575</td>\n",
              "      <td>0.963779</td>\n",
              "      <td>-0.373397</td>\n",
              "      <td>-1.326197</td>\n",
              "      <td>3.270295</td>\n",
              "      <td>-0.327701</td>\n",
              "      <td>0.934943</td>\n",
              "      <td>1.277202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>570</td>\n",
              "      <td>1341</td>\n",
              "      <td>193</td>\n",
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              "      <td>0.732575</td>\n",
              "      <td>0.963779</td>\n",
              "      <td>-0.342518</td>\n",
              "      <td>0.208201</td>\n",
              "      <td>-0.318469</td>\n",
              "      <td>-0.388330</td>\n",
              "      <td>0.934943</td>\n",
              "      <td>0.239229</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>44</td>\n",
              "      <td>945</td>\n",
              "      <td>1071</td>\n",
              "      <td>50710</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>0.963779</td>\n",
              "      <td>-0.385947</td>\n",
              "      <td>-0.319249</td>\n",
              "      <td>0.213425</td>\n",
              "      <td>-0.407456</td>\n",
              "      <td>0.934943</td>\n",
              "      <td>1.277202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1381</td>\n",
              "      <td>711</td>\n",
              "      <td>272</td>\n",
              "      <td>1905124</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>0.963779</td>\n",
              "      <td>-0.275557</td>\n",
              "      <td>-0.630923</td>\n",
              "      <td>-0.270610</td>\n",
              "      <td>2.915071</td>\n",
              "      <td>0.422142</td>\n",
              "      <td>0.239229</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1936</td>\n",
              "      <td>443</td>\n",
              "      <td>427</td>\n",
              "      <td>532939</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>0.963779</td>\n",
              "      <td>-0.229733</td>\n",
              "      <td>-0.987884</td>\n",
              "      <td>-0.176711</td>\n",
              "      <td>0.456547</td>\n",
              "      <td>0.934943</td>\n",
              "      <td>1.277202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>917</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>442</td>\n",
              "      <td>1607</td>\n",
              "      <td>1322</td>\n",
              "      <td>24257</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>-1.037582</td>\n",
              "      <td>-0.353086</td>\n",
              "      <td>0.562497</td>\n",
              "      <td>0.365481</td>\n",
              "      <td>-0.454852</td>\n",
              "      <td>0.422142</td>\n",
              "      <td>-0.798744</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>918</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>196</td>\n",
              "      <td>2204</td>\n",
              "      <td>741</td>\n",
              "      <td>7457</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-1.365047</td>\n",
              "      <td>-1.037582</td>\n",
              "      <td>-0.373397</td>\n",
              "      <td>1.357667</td>\n",
              "      <td>0.013510</td>\n",
              "      <td>-0.484952</td>\n",
              "      <td>-1.629058</td>\n",
              "      <td>-1.317730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>919</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>50</td>\n",
              "      <td>1905</td>\n",
              "      <td>261</td>\n",
              "      <td>1180</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>-1.037582</td>\n",
              "      <td>-0.385452</td>\n",
              "      <td>0.959416</td>\n",
              "      <td>-0.277274</td>\n",
              "      <td>-0.496198</td>\n",
              "      <td>-0.090658</td>\n",
              "      <td>-0.279757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>920</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>454</td>\n",
              "      <td>319</td>\n",
              "      <td>485</td>\n",
              "      <td>14265</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>-1.037582</td>\n",
              "      <td>-0.352095</td>\n",
              "      <td>-1.153045</td>\n",
              "      <td>-0.141575</td>\n",
              "      <td>-0.472754</td>\n",
              "      <td>-0.090658</td>\n",
              "      <td>-0.279757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>921</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>37734</td>\n",
              "      <td>2009</td>\n",
              "      <td>318</td>\n",
              "      <td>888292</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>0.963779</td>\n",
              "      <td>2.725957</td>\n",
              "      <td>1.097938</td>\n",
              "      <td>-0.242743</td>\n",
              "      <td>1.093228</td>\n",
              "      <td>0.934943</td>\n",
              "      <td>1.277202</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>922 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     question1  question2  ...  cyberaggression_zscore  cyberbullying_zscore\n",
              "0            1          1  ...                0.934943              1.277202\n",
              "1            1          1  ...                0.934943              0.239229\n",
              "2            1          1  ...                0.934943              1.277202\n",
              "3            1          1  ...                0.422142              0.239229\n",
              "4            1          1  ...                0.934943              1.277202\n",
              "..         ...        ...  ...                     ...                   ...\n",
              "917          1          0  ...                0.422142             -0.798744\n",
              "918          0          0  ...               -1.629058             -1.317730\n",
              "919          1          0  ...               -0.090658             -0.279757\n",
              "920          1          0  ...               -0.090658             -0.279757\n",
              "921          1          1  ...                0.934943              1.277202\n",
              "\n",
              "[922 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mQhw52wco3xh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e94e8268-84de-4ac2-c703-4f7964d7d2ad"
      },
      "source": [
        "#knn graph\n",
        "A = kneighbors_graph(df, 5, mode='connectivity', include_self=True).toarray()\n",
        "A\n",
        "\n",
        "#clustering = SpectralClustering(n_clusters=5, affinity='precomputed', n_init=100, assign_labels='discretize')\n",
        "#clustering.fit_predict(A)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 1., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 1., ..., 0., 0., 0.],\n",
              "       ...,\n",
              "       [0., 0., 0., ..., 1., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 1., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 1.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    }
  ]
}