cah_eda_outputs.ipynb

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    "colab": {
      "name": "cah_eda_outputs.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "experienced-isolation"
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "\n",
        "pd.set_option(\"display.precision\", 3)\n",
        "pd.set_option('display.width', 1024)\n",
        "pd.set_option('display.max_colwidth', None)\n",
        "from matplotlib import pyplot as plt\n",
        "\n",
        "### https://blakeaw.github.io/2020-05-25-improve-matplotlib-notebook-inline-res/\n",
        "from IPython.display import set_matplotlib_formats\n",
        "set_matplotlib_formats('svg',\"png\")\n",
        "# plt.rcParams['figure.format'] = 'svg'\n",
        "\n",
        "plt.rcParams['figure.dpi'] = 400\n",
        "plt.rcParams['savefig.dpi'] = 400\n",
        "\n",
        "# plt.rcParams[bbox_inches] = 'tight'\n",
        "import seaborn as sns\n",
        "sns.set(rc={\"figure.dpi\":400, 'savefig.dpi':400})\n",
        "sns.set_context('notebook')\n",
        "sns.set_style(\"ticks\")\n",
        "\n",
        "# plt.rcParams[\"figure.dpi\"] = 600 ## default 72\n",
        "## https://stackoverflow.com/questions/39870642/matplotlib-how-to-plot-a-high-resolution-graph\n",
        "## https://www.delftstack.com/howto/matplotlib/how-to-plot-and-save-a-graph-in-high-resolution/\n",
        "\n",
        "%matplotlib inline \n",
        "\n",
        "MIN_PAIR_FREQ = 1\n",
        "SAVE_TRAIN_DATA = False\n",
        "\n",
        "LOWERCASE_DATA = False\n",
        "DROP_DOUBLES = True ## drop white cards with pick 2 options ; and their blacks. (TODO: analyze interesting pairs)\n",
        "DROP_SKIPPED = True ## ignore rounds where skipped\n",
        "\n",
        "\n",
        "DRIVE_FILE_PATH = \"/content/drive/MyDrive/Research/CAH/cah_lab_data_for_research_XXX_XXX.csv.gz\"\n",
        "## \"cah_lab_data_for_research_XXX_XXX.csv\""
      ],
      "id": "experienced-isolation",
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xZ84pkSNh-lL",
        "outputId": "29708fdb-ef64-4b98-ebc1-65caa6b52e21"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "id": "xZ84pkSNh-lL",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bridal-paris"
      },
      "source": [
        "Load data\n",
        "\n",
        "* Note there are some near-duplicate cards (e.g. footballers - could minhash - https://github.com/chrisjmccormick/MinHash/blob/master/runMinHashExample.py , LSH/shingles : https://onestopdataanalysis.com/lsh/  (broken library?) , https://github.com/zyocum/dedup/blob/master/dedup.py ,\n",
        "\n",
        "`Datasketch` https://www.learndatasci.com/tutorials/building-recommendation-engine-locality-sensitive-hashing-lsh-python/ ,\n",
        "https://stackoverflow.com/questions/25114338/approximate-string-matching-using-lsh , \n",
        "\n",
        "SKLearn friendly?: http://ethen8181.github.io/machine-learning/recsys/content_based/lsh_text.html\n",
        "\n",
        "`dedupe` library - https://github.com/dedupeio/dedupe\n",
        "\n",
        "* Paraphrase mining using sentence bert - https://www.sbert.net/examples/applications/paraphrase-mining/README.html  (may be too semantic)\n",
        "\n",
        "* Example: \"10 football players with erections *barreling* towards you at full speed\" - 10 football players with erections **barrelling** towards you at full speed.\"\n",
        "\n",
        "Task modelling:\n",
        "* Ranking = most accurate\n",
        "* Regression/classification: can be done just over single cards, or between pairs. \n",
        "    * if pairs-wise: can use sentencebert/SNLI models (which assume pairs of sentences) - https://github.com/UKPLab/sentence-transformers\n",
        "    \n",
        "    \n",
        "Examples:\n",
        "\n",
        "* https://www.sbert.net/examples/training/sts/README.html#training-data\n",
        "* https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/nli/training_nli.py\n",
        "* https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/nli/training_nli_v2.py\n",
        "\n",
        "\n",
        "* Keras example (not sentenceBert): https://keras.io/examples/nlp/semantic_similarity_with_bert/\n",
        "\n",
        "\n",
        "* Interpretability tool : https://github.com/cdpierse/transformers-interpret"
      ],
      "id": "bridal-paris"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sound-transcript",
        "outputId": "dc662a2c-137d-47d2-c99e-81f4eadb91f1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "df = pd.read_csv(DRIVE_FILE_PATH)\n",
        "## remove punct/newlines\n",
        "df[\"white_card_text\"] = df[\"white_card_text\"].replace(\"\\n\", \" \",regex=True).replace(\"\\t\", \" \",regex=True) # .replace(\"\\r\", \"\")\n",
        "df[\"black_card_text\"] = df[\"black_card_text\"].replace(\"\\n\", \" \",regex=True).replace(\"\\t\", \" \",regex=True) # .replace(\"\\r\", \"\")\n",
        "\n",
        "# df = df.replace(\"\\[rnt]\", \"\",regex=True)#.replace(\"\\n\", \" \").replace(\"\\t\", \" \")\n",
        "# df[\"black_card_text\"] = df[\"black_card_text\"].replace(\"\\r\", \"\").replace(\"\\n\", \" \").replace(\"\\t\", \" \")\n",
        "\n",
        "\n",
        "print(df[['black_card_text', 'black_card_pick_num', 'white_card_text',\"fake_round_id\"]].nunique())\n",
        "print(df.describe())\n",
        "df"
      ],
      "id": "sound-transcript",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "black_card_text           650\n",
            "black_card_pick_num         2\n",
            "white_card_text          2128\n",
            "fake_round_id          298955\n",
            "dtype: int64\n",
            "       fake_round_id  round_completion_seconds  black_card_pick_num  winning_index\n",
            "count      2.990e+06                 2.990e+06            2.990e+06     318508.000\n",
            "mean       1.495e+05                 9.344e+01            1.133e+00          0.116\n",
            "std        8.630e+04                 3.353e+03            3.399e-01          0.320\n",
            "min        1.000e+00                 2.000e+00            1.000e+00          0.000\n",
            "25%        7.474e+04                 1.000e+01            1.000e+00          0.000\n",
            "50%        1.495e+05                 1.700e+01            1.000e+00          0.000\n",
            "75%        2.242e+05                 2.800e+01            1.000e+00          0.000\n",
            "max        2.990e+05                 7.021e+05            2.000e+00          1.000\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         fake_round_id  round_completion_seconds  round_skipped                                                                               black_card_text  black_card_pick_num                                        white_card_text    won  winning_index\n",
              "0                    1                        24          False  Hi MTV! My name is Kendra, I live in Malibu, I'm into _____, and I love to have a good time.                    1  Going inside at some point because of the mosquitoes.  False            NaN\n",
              "1                    1                        24          False  Hi MTV! My name is Kendra, I live in Malibu, I'm into _____, and I love to have a good time.                    1                                Being fat from noodles.  False            NaN\n",
              "2                    1                        24          False  Hi MTV! My name is Kendra, I live in Malibu, I'm into _____, and I love to have a good time.                    1                         Letting this loser eat me out.  False            NaN\n",
              "3                    1                        24          False  Hi MTV! My name is Kendra, I live in Malibu, I'm into _____, and I love to have a good time.                    1                            That chicken from Popeyes.®  False            NaN\n",
              "4                    1                        24          False  Hi MTV! My name is Kendra, I live in Malibu, I'm into _____, and I love to have a good time.                    1                           A sorry excuse for a father.  False            NaN\n",
              "...                ...                       ...            ...                                                                                           ...                  ...                                                    ...    ...            ...\n",
              "2989545         298955                      7613          False                                                                Oh my god! _____ killed Kenny!                    1                          Breastfeeding a ten-year-old.  False            NaN\n",
              "2989546         298955                      7613          False                                                                Oh my god! _____ killed Kenny!                    1                      Happy daddies with happy sandals.  False            NaN\n",
              "2989547         298955                      7613          False                                                                Oh my god! _____ killed Kenny!                    1             Jerking off to a 10-second RealMedia clip.  False            NaN\n",
              "2989548         298955                      7613          False                                                                Oh my god! _____ killed Kenny!                    1                Getting naked and watching Nickelodeon.  False            NaN\n",
              "2989549         298955                      7613          False                                                                Oh my god! _____ killed Kenny!                    1                 Awesome pictures of planets and stuff.  False            NaN\n",
              "\n",
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              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0cdaff85"
      },
      "source": [
        "##### analyze rounds skipped\n",
        "* at level of round -  5% of rounds skipped due to all combinations being considered \"unfunny\""
      ],
      "id": "0cdaff85"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "554f408c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6b1e0a43-1c38-4595-d39d-3c5eb3c36029"
      },
      "source": [
        "df.drop_duplicates(\"fake_round_id\")[\"round_skipped\"].mean()"
      ],
      "id": "554f408c",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.058145874797210284"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "53b2859a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "3b9ee31f-5e04-4252-d059-4ccca274b881"
      },
      "source": [
        "# df.dropna(subset=[\"winning_index\"])[\"black_card_text\"].drop_duplicates().values\n",
        "\n",
        "df[\"double_card\"] = df[\"black_card_text\"].str.count(\"_____\")>1\n",
        "print(df[\"double_card\"].describe())\n",
        "df.loc[df[\"double_card\"]].drop_duplicates(\"black_card_text\")\n"
      ],
      "id": "53b2859a",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "count     2989550\n",
            "unique          2\n",
            "top         False\n",
            "freq      2578330\n",
            "Name: double_card, dtype: object\n"
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          "data": {
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              "         fake_round_id  round_completion_seconds  round_skipped                                                                                    black_card_text  black_card_pick_num                                                   white_card_text    won  winning_index  double_card\n",
              "110                 12                        42          False                                                 That's right, I killed _____. How, you ask? _____.                    2                                                            China.   True            0.0         True\n",
              "160                 17                         3          False  Listen, son. If you want to get involved with _____, I won't stop you. Just steer clear of _____.                    2         Watching the life drain from the eyes of my son's killer.  False            NaN         True\n",
              "170                 18                        79          False                                              When I was tripping on acid, _____ turned into _____.                    2                             Flirting with the ladies at the bank.  False            NaN         True\n",
              "270                 28                        26          False                             If God didn't want us to enjoy _____, he wouldn't have given us _____.                    2                                                         Throw up.  False            NaN         True\n",
              "310                 32                         8          False                                                      Step 1: _____. Step 2: _____. Step 3: Profit.                    2                Quacking like a duck in lieu of a cogent argument.  False            NaN         True\n",
              "...                ...                       ...            ...                                                                                                ...                  ...                                                               ...    ...            ...          ...\n",
              "2903880         290389                        15          False                                                     I'm _____, you're _____, let's party! (PICK 2)                    2                           Ejaculating at the apex of a cartwheel.  False            NaN         True\n",
              "2910940         291095                        25          False                                                 You: _____.   Me, an intellectual: _____. (PICK 2)                    2  The primal, ball-slapping sex your parents are having right now.  False            NaN         True\n",
              "2930320         293033                        18          False                                                       Dudes. I just found out that _____ is _____.                    2                             A real cum-dumpster of a saxophonist.   True            1.0         True\n",
              "2934140         293415                         8          False                      Critics are raving about HBO's new fantasy series, \"_____ of _____.\" (PICK 2)                    2                                             Running out of semen.  False            NaN         True\n",
              "2936730         293674                        23           True                                        Alright, I'm done with _____. It's time for _____. (PICK 2)                    2                                                  A dead salesman.  False            NaN         True\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "61278679"
      },
      "source": [
        "if LOWERCASE_DATA:\n",
        "    df[\"white_card_text\"] = df[\"white_card_text\"].str.lower()\n",
        "    df[\"black_card_text\"] = df[\"black_card_text\"].str.lower()"
      ],
      "id": "61278679",
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "opening-pioneer",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c347d3e3-ecdd-4b50-9235-72aaa0c78ba8"
      },
      "source": [
        "df[\"white_card_text\"].drop_duplicates().str.split().str.len().describe()"
      ],
      "id": "opening-pioneer",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    2128.000\n",
              "mean        4.962\n",
              "std         3.216\n",
              "min         1.000\n",
              "25%         2.000\n",
              "50%         4.000\n",
              "75%         7.000\n",
              "max        23.000\n",
              "Name: white_card_text, dtype: float64"
            ]
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          "metadata": {},
          "execution_count": 7
        }
      ]
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    {
      "cell_type": "code",
      "metadata": {
        "id": "serious-natural",
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          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eb3fc69d-22b3-42e1-df0f-f0ac0b51b35f"
      },
      "source": [
        "df[\"black_card_text\"].drop_duplicates().str.split().str.len().describe()"
      ],
      "id": "serious-natural",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    650.000\n",
              "mean      11.295\n",
              "std        5.232\n",
              "min        2.000\n",
              "25%        7.000\n",
              "50%       11.000\n",
              "75%       14.000\n",
              "max       41.000\n",
              "Name: black_card_text, dtype: float64"
            ]
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          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fluid-penguin",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "5757d636-0990-407b-96bc-56243285ea62"
      },
      "source": [
        "df.groupby(by=\"white_card_text\").agg(picks=(\"won\",\"sum\"), pick_opportunities=(\"won\",\"count\"),\n",
        "                                                pick_ratio=(\"won\",\"mean\"))"
      ],
      "id": "fluid-penguin",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                          picks  pick_opportunities  pick_ratio\n",
              "white_card_text                                                                                                \n",
              "...it is unclear.                                                            97                1576       0.062\n",
              "10 Incredible Facts About the Anus.                                         156                1512       0.103\n",
              "10 football players with erections barreling towards you at full speed.       4                  34       0.118\n",
              "10 football players with erections barrelling towards you at full speed.    207                1465       0.141\n",
              "10,000 Syrian refugees.                                                     204                1531       0.133\n",
              "...                                                                         ...                 ...         ...\n",
              "Your mouth.                                                                 174                1600       0.109\n",
              "Your weird brother.                                                         191                1552       0.123\n",
              "Yummy yummy yummy yummy rat pussy.                                          261                1548       0.169\n",
              "[Picture of Sean Connery from Zardoz]                                        84                1520       0.055\n",
              "marvel                                                                       79                1430       0.055\n",
              "\n",
              "[2128 rows x 3 columns]"
            ],
            "text/html": [
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              "      <th>...</th>\n",
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              "      <th>Yummy yummy yummy yummy rat pussy.</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>[Picture of Sean Connery from Zardoz]</th>\n",
              "      <td>84</td>\n",
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              "      <td>0.055</td>\n",
              "    </tr>\n",
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              "      <th>marvel</th>\n",
              "      <td>79</td>\n",
              "      <td>1430</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>2128 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6130e428-68f3-474f-91fc-af94f83f3496')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6130e428-68f3-474f-91fc-af94f83f3496 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-6130e428-68f3-474f-91fc-af94f83f3496');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "generous-explanation",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "outputId": "fba9981a-e619-4516-ca06-00c943889eba"
      },
      "source": [
        "print(\"white cards against humanity - aggregated funniest\")\n",
        "df_white = df.groupby(by=\"white_card_text\").agg(picks=(\"won\",\"sum\"), pick_opportunities=(\"won\",\"count\"),\n",
        "                                                pick_ratio=(\"won\",\"mean\"),round_skip_ratio=(\"round_skipped\",\"mean\")).sort_values(\"pick_ratio\",ascending=False)\n",
        "\n",
        "print(df_white.describe())\n",
        "df_white"
      ],
      "id": "generous-explanation",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "white cards against humanity - aggregated funniest\n",
            "          picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
            "count  2128.000            2128.000    2128.000          2128.000\n",
            "mean    149.675            1404.864       0.106             0.059\n",
            "std      87.077             408.717       0.053             0.013\n",
            "min       0.000              19.000       0.000             0.000\n",
            "25%      91.750            1490.000       0.067             0.054\n",
            "50%     139.000            1522.000       0.096             0.058\n",
            "75%     203.000            1552.000       0.138             0.063\n",
            "max     459.000            3006.000       0.357             0.192\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                    picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "white_card_text                                                                            \n",
              "Syphilis.                              10                  28       0.357             0.036\n",
              "Anal.                                 459                1572       0.292             0.034\n",
              "Sluts, whores, and bitches.           456                1598       0.285             0.054\n",
              "Tentacle porn.                        434                1525       0.285             0.066\n",
              "Incest.                               435                1530       0.284             0.047\n",
              "...                                   ...                 ...         ...               ...\n",
              "Bupkis.                                 0                  32       0.000             0.125\n",
              "Also being named Harvey Weinstein.      0                  28       0.000             0.071\n",
              "The mere concept of Applebee's.®        0                  26       0.000             0.038\n",
              "Swedes.                                 0                  30       0.000             0.067\n",
              "Saudi oil money.                        0                  24       0.000             0.083\n",
              "\n",
              "[2128 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3b41e8e6-b506-4a91-957a-79177791fcf6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>picks</th>\n",
              "      <th>pick_opportunities</th>\n",
              "      <th>pick_ratio</th>\n",
              "      <th>round_skip_ratio</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>white_card_text</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Syphilis.</th>\n",
              "      <td>10</td>\n",
              "      <td>28</td>\n",
              "      <td>0.357</td>\n",
              "      <td>0.036</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Anal.</th>\n",
              "      <td>459</td>\n",
              "      <td>1572</td>\n",
              "      <td>0.292</td>\n",
              "      <td>0.034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sluts, whores, and bitches.</th>\n",
              "      <td>456</td>\n",
              "      <td>1598</td>\n",
              "      <td>0.285</td>\n",
              "      <td>0.054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tentacle porn.</th>\n",
              "      <td>434</td>\n",
              "      <td>1525</td>\n",
              "      <td>0.285</td>\n",
              "      <td>0.066</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Incest.</th>\n",
              "      <td>435</td>\n",
              "      <td>1530</td>\n",
              "      <td>0.284</td>\n",
              "      <td>0.047</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bupkis.</th>\n",
              "      <td>0</td>\n",
              "      <td>32</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Also being named Harvey Weinstein.</th>\n",
              "      <td>0</td>\n",
              "      <td>28</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>The mere concept of Applebee's.®</th>\n",
              "      <td>0</td>\n",
              "      <td>26</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.038</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Swedes.</th>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Saudi oil money.</th>\n",
              "      <td>0</td>\n",
              "      <td>24</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.083</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2128 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3b41e8e6-b506-4a91-957a-79177791fcf6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3b41e8e6-b506-4a91-957a-79177791fcf6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_white[\"pick_ratio\"].hist(grid=False)#,legend=True);"
      ],
      "metadata": {
        "id": "gQoLx8vfsyRo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "outputId": "126cf2da-d3d1-4b76-c06c-b88cdc06dcc9"
      },
      "id": "gQoLx8vfsyRo",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f10c1b48150>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Fig 1a- Card counts\t"
      ],
      "metadata": {
        "id": "Y0_5_QLDRG9Z"
      },
      "id": "Y0_5_QLDRG9Z"
    },
    {
      "cell_type": "code",
      "source": [
        "# sns.histplot([df[\"white_card_text\"].value_counts(),df[\"black_card_text\"].value_counts()])"
      ],
      "metadata": {
        "id": "WY3jRZo7alcs"
      },
      "id": "WY3jRZo7alcs",
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig = sns.histplot([df[\"white_card_text\"].value_counts(),df[\"black_card_text\"].value_counts()])\n",
        "fig.set_yscale('log')\n",
        "fig.set_xscale('log')\n",
        "legend = fig.get_legend()\n",
        "handles = legend.legendHandles\n",
        "legend.remove()\n",
        "# fig.legend(handles, ['White Cards', 'Black Cards'])#, title='Card counts')\n",
        "fig.legend(handles, ['Punchline Cards', 'Prompt Cards'])\n",
        "# plt.savefig('Fig 1a- Card counts.svg')\n",
        "plt.savefig('Fig 1a- Card counts.png',bbox_inches='tight')"
      ],
      "metadata": {
        "id": "QWaSD_LjIe4Q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "57b48e31-e484-4545-8edb-6b0712d23159"
      },
      "id": "QWaSD_LjIe4Q",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Add d Pseudo joint text col / \"joke\", mainly for eda purposes"
      ],
      "metadata": {
        "id": "jD7n66ZFNVfY"
      },
      "id": "jD7n66ZFNVfY"
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"joke\"] = df[\"black_card_text\"] + df[\"white_card_text\"]"
      ],
      "metadata": {
        "id": "QS4ct-rINSJm"
      },
      "id": "QS4ct-rINSJm",
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Potential unique jokes:\",df[\"black_card_text\"].nunique() * df[\"white_card_text\"].nunique())\n",
        "print(\"# Jokes observed:\",df[\"joke\"].nunique())\n",
        "print(\"Fraction% of jokes covered:\",100*df[\"joke\"].nunique()/(df[\"black_card_text\"].nunique() * df[\"white_card_text\"].nunique()))"
      ],
      "metadata": {
        "id": "glXmFdT3ugX8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ff410cb3-60b7-4490-933c-c603dcc7c1c4"
      },
      "id": "glXmFdT3ugX8",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Potential unique jokes: 1383200\n",
            "# Jokes observed: 908362\n",
            "Fraction% of jokes covered: 65.67105263157895\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fig 1b- Punchline win rate\n",
        "* Pick ratio (win rate frequency) of punchlines, across all games. A random, uniform distribution would be 0.10 for all."
      ],
      "metadata": {
        "id": "LgfS5oD-RYm8"
      },
      "id": "LgfS5oD-RYm8"
    },
    {
      "cell_type": "code",
      "source": [
        "## https://cmdlinetips.com/2019/02/how-to-make-histogram-in-python-with-pandas-and-seaborn/\n",
        "fig = sns.histplot(df_white[\"pick_ratio\"])#,x=\"Pick Ratio (win rate frequency)\")\n",
        "fig.set(xlabel=\"Pick Ratio (win rate frequency)\",  title='Punchline win rate') # ylabel='common ylabel',\n",
        "plt.axvline(0.1,color=\"red\")\n",
        "\n",
        "plt.savefig('Fig 1b- Punchline win rate.png',bbox_inches='tight')"
      ],
      "metadata": {
        "id": "QgH8dEKU1ci0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        },
        "outputId": "0b6a3742-7cfb-4260-ce0f-bf464cdeb177"
      },
      "id": "QgH8dEKU1ci0",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "#### Fig 1c- Joke counts\t\n",
        "* \"Joke\" Counts/histogram (white + black combinations):\n",
        "1d. Counts for winning combinations only\n",
        "* Jokes’ counts, occurring across all games. 36% appear less than 3 times.\n",
        "\n",
        "https://seaborn.pydata.org/generated/seaborn.countplot.html"
      ],
      "metadata": {
        "id": "4L-Duxc_LwIp"
      },
      "id": "4L-Duxc_LwIp"
    },
    {
      "cell_type": "code",
      "source": [
        "joke_counts = df[\"joke\"].value_counts()\n",
        "\n",
        "# sns.countplot(df[[\"white_card_text\",\"black_card_text\"]].value_counts(),x=\"Joke counts\")\n",
        "# sns.countplot(df[\"joke\"].value_counts(),x=\"Joke counts\")\n",
        "fig = sns.histplot(joke_counts)#,bins=7)\n",
        "# df[\"joke\"].value_counts().hist()\n",
        "\n",
        "\n",
        "plt.savefig('Fig 1c- Joke counts.png',bbox_inches='tight')"
      ],
      "metadata": {
        "id": "eUZBLXFzoKKh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        },
        "outputId": "aa46ae38-e5f0-4299-96c5-806543663bdd"
      },
      "id": "eUZBLXFzoKKh",
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "vEXlr7ALLsGl"
      },
      "id": "vEXlr7ALLsGl",
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# joke_counts.plot(kind= \"kde\")#\"hist\")"
      ],
      "metadata": {
        "id": "3ZqQXWt3l55V"
      },
      "id": "3ZqQXWt3l55V",
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Joke counts by wins and sparsity - cont"
      ],
      "metadata": {
        "id": "nw91cpzd1Pii"
      },
      "id": "nw91cpzd1Pii"
    },
    {
      "cell_type": "code",
      "source": [
        "print((df[\"joke\"].value_counts()==1).mean())\n",
        "print((df[\"joke\"].value_counts()==2).mean())"
      ],
      "metadata": {
        "id": "5Xco8rVLXBnx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe2f00f2-3a68-4fd3-ae85-bdafd9a4a83d"
      },
      "id": "5Xco8rVLXBnx",
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.16927172206675312\n",
            "0.20506912442396313\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## sparsity? : \n",
        "print(\"# jokes played and won:\",df.loc[df[\"won\"]][\"joke\"].nunique())\n",
        "print(\"Therre are ~ 650 * 2128 (1.38 Million) potential unique jokes\")"
      ],
      "metadata": {
        "id": "VUbcCZeIpIFy",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5fe59c08-b3a5-4231-ab53-6e08eecf220f"
      },
      "id": "VUbcCZeIpIFy",
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# jokes played and won: 248896\n",
            "Therre are ~ 650 * 2128 (1.38 Million) potential unique jokes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# g = sns.catplot(x=\"joke\", #hue=\"who\",\n",
        "#                 col=\"won\",\n",
        "#                 data=df, kind=\"count\")\n",
        "# g\n",
        "\n",
        "print((df.loc[df[\"won\"]][[\"joke\"]].value_counts()==1).mean())\n",
        "print((df.loc[df[\"won\"]][[\"joke\"]].value_counts()==2).mean())"
      ],
      "metadata": {
        "id": "N3wZGbPHM9rl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "64b1692c-a7c9-47fb-bf31-5830feebfa25"
      },
      "id": "N3wZGbPHM9rl",
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.7786223965029571\n",
            "0.1748441115968115\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "BNVHiYOJfR-9"
      },
      "id": "BNVHiYOJfR-9",
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fig 1d: Picked Jokes counts\t\n",
        "* Frequency (percent) histogram of jokes being picked as winners\n"
      ],
      "metadata": {
        "id": "pahfyH2cTdJR"
      },
      "id": "pahfyH2cTdJR"
    },
    {
      "cell_type": "code",
      "source": [
        "display(df.loc[df[\"won\"]][[\"joke\"]].value_counts().describe().round(2))\n",
        "sns.histplot(df.loc[df[\"won\"]][[\"joke\"]].value_counts(),stat=\"percent\")#,x=\"Winning joke counts\")"
      ],
      "metadata": {
        "id": "21WVVTszMWJs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 535
        },
        "outputId": "bef44605-fd0c-4ba9-8b7d-dbdc45eb90e2"
      },
      "id": "21WVVTszMWJs",
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "count    248896.00\n",
              "mean          1.28\n",
              "std           0.59\n",
              "min           1.00\n",
              "25%           1.00\n",
              "50%           1.00\n",
              "75%           1.00\n",
              "max           8.00\n",
              "dtype: float64"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f109feaadd0>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[[\"white_card_text\",\"black_card_text\"]].value_counts()"
      ],
      "metadata": {
        "id": "FywXeIsGI546",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "91339e0f-5478-41cb-8c54-80dc55a7d1c5"
      },
      "id": "FywXeIsGI546",
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "white_card_text         black_card_text                                                                             \n",
              "Having a heart attack.  Bitch, you're nasty. You're disgusting. You're _____. Go home, bitch.                           15\n",
              "Déjà vu.                Why am I laughing and crying and taking off my clothes?                                         15\n",
              "                        This year's hottest album is \"_____\" by _____.                                                  14\n",
              "A Bop It.™              I tell you, it was a non-stop fuckfest. When it was over, my asshole looked like _____.         14\n",
              "Deez nuts.              Your persistence is admirable, my dear Prince. But you cannot win my heart with _____ alone.    14\n",
              "                                                                                                                        ..\n",
              "Gay aliens.             You want _____? You can't handle _____! (SAME CARD AGAIN)                                        1\n",
              "                        You city folk would never understand the quiet dignity of _____.                                 1\n",
              "The Hustle.             What will always get you laid?                                                                   1\n",
              "Gay aliens.             You Won't Believe These 15 Hilarious _____ Bloopers!                                             1\n",
              "marvel                  ✮✩✩✩✩ Do NOT go here! Found _____ in my fettuccine alfredo!                                      1\n",
              "Length: 908362, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"white_card_text\"].value_counts().hist()"
      ],
      "metadata": {
        "id": "d890IR5mH_GN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "outputId": "27fee079-ee5d-486e-86ef-a7bb0340edcd"
      },
      "id": "d890IR5mH_GN",
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f109fe66590>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "latest-clerk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1bc2cbd2-0330-401b-dbc6-00b40abde478"
      },
      "source": [
        "df_white.sort_values(\"pick_ratio\",ascending=False).head(20).reset_index()[\"white_card_text\"].values"
      ],
      "id": "latest-clerk",
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Syphilis.', 'Anal.', 'Sluts, whores, and bitches.',\n",
              "       'Tentacle porn.', 'Incest.', 'A big black dick.', 'Cock.',\n",
              "       'The death penalty.', 'Gay thoughts.',\n",
              "       'Three dicks at the same time.', 'The Asshole Destroyer 3000.',\n",
              "       'Dem titties.', 'Masturbating.', 'Horny Christian teens.',\n",
              "       'Double penetration.', 'Masturbating to ISIS beheading videos.',\n",
              "       'Crazy anal orgasms.', 'COVID-19.', 'Elf cum.', 'Joe Biden.'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_white.sort_values(\"pick_ratio\",ascending=True).head(10)#.reset_index()[\"white_card_text\"].values"
      ],
      "metadata": {
        "id": "MS8TQF6qv29M",
        "colab": {
          "base_uri": "https://localhost:8080/",
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        "outputId": "569a5882-93ec-4dbd-bccc-ed6002205012"
      },
      "id": "MS8TQF6qv29M",
      "execution_count": 26,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "                                                                         picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "white_card_text                                                                                                                 \n",
              "Saudi oil money.                                                             0                  24         0.0             0.083\n",
              "The whole enchilada.                                                         0                  24         0.0             0.000\n",
              "Holding a pepper grinder for some reason.                                    0                  21         0.0             0.048\n",
              "Lips that could suck the chrome off a doorknob.                              0                  21         0.0             0.095\n",
              "JFK’s smiling, exploding head.                                               0                  24         0.0             0.083\n",
              "Swedes.                                                                      0                  30         0.0             0.067\n",
              "Acknowledging that we stand on the unceded lands of Indigenous peoples.      0                  33         0.0             0.152\n",
              "The mere concept of Applebee's.®                                             0                  26         0.0             0.038\n",
              "The bond of brotherhood forged in battle, unbreakable and eternal.           0                  30         0.0             0.067\n",
              "Bupkis.                                                                      0                  32         0.0             0.125"
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              "      <th>picks</th>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.067</td>\n",
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              "      <th>Bupkis.</th>\n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "regional-northeast",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 552
        },
        "outputId": "2f42544f-67cc-4a02-fcfa-fdba1df25fe8"
      },
      "source": [
        "print(df_white.loc[df_white[\"picks\"]==0].shape[0], \"0 picks\")\n",
        "print(df_white.loc[df_white[\"picks\"].between(1,5)].shape[0], \"1-5 picks\")\n",
        "\n",
        "print(df_white.describe().round(3))\n",
        "\n",
        "df_white[\"picks\"].hist();"
      ],
      "id": "regional-northeast",
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "11 0 picks\n",
            "127 1-5 picks\n",
            "          picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
            "count  2128.000            2128.000    2128.000          2128.000\n",
            "mean    149.675            1404.864       0.106             0.059\n",
            "std      87.077             408.717       0.053             0.013\n",
            "min       0.000              19.000       0.000             0.000\n",
            "25%      91.750            1490.000       0.067             0.054\n",
            "50%     139.000            1522.000       0.096             0.058\n",
            "75%     203.000            1552.000       0.138             0.063\n",
            "max     459.000            3006.000       0.357             0.192\n"
          ]
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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "accurate-brother",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 534
        },
        "outputId": "efe22930-77e9-4e40-d9e0-899c3ccae575"
      },
      "source": [
        "df.groupby(by=\"black_card_text\").agg(picks=(\"won\",\"sum\"), pick_opportunities=(\"won\",\"count\"),\n",
        "                                                pick_ratio=(\"won\",\"mean\"),round_skip_ratio=(\"round_skipped\",\"mean\")).sort_values([\"pick_ratio\"],ascending=False)"
      ],
      "id": "accurate-brother",
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                                                               picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "black_card_text                                                                                                                                                                                       \n",
              "You: _____.   Me, an intellectual: _____. (PICK 2)                                                                                                10                  50       0.200             0.000\n",
              "Problem: _____. Solution: _____. (PICK 2)                                                                                                         14                  70       0.200             0.000\n",
              "In JorXXX Peele's new thriller, a young family discovers that _____ had really been _____ all along.                                             206                1070       0.193             0.037\n",
              "_____ is a slippery slope that leads to _____.                                                                                                  1300                6790       0.191             0.043\n",
              "_____ would be woefully incomplete without _____.                                                                                               1334                6970       0.191             0.043\n",
              "...                                                                                                                                              ...                 ...         ...               ...\n",
              "Instead of playing a card this round, everyone must stare at the Card Czar while making a sound you'd make after tasting something delicious.    462                6550       0.071             0.295\n",
              "Up on the shore they work all day Out in the sun they slave away While we devotin' Full time to _____ Under the sea!                               2                  30       0.067             0.333\n",
              "I hate to be that guy, but I just don't see the point of _____.                                                                                    2                  30       0.067             0.333\n",
              "I am so, so sorry everyone. I take full responsibility for _____.                                                                                  2                  30       0.067             0.333\n",
              "As Gregor Samsa awoke one morning from uneasy dreams, he found that he was _____.                                                                  3                  50       0.060             0.400\n",
              "\n",
              "[650 rows x 4 columns]"
            ],
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              "      <th>picks</th>\n",
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              "    <tr>\n",
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              "      <td>0.071</td>\n",
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              "      <td>0.333</td>\n",
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              "      <td>3</td>\n",
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              "      <td>0.400</td>\n",
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              "<p>650 rows × 4 columns</p>\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-406573d6-c107-4e24-8810-1170e329d55f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-406573d6-c107-4e24-8810-1170e329d55f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "looking-senior"
      },
      "source": [
        "## Black (\"Question\") Cards"
      ],
      "id": "looking-senior"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "burning-there",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "outputId": "04ae31ce-93a5-4d7d-aecc-690312ed044b"
      },
      "source": [
        "print(\"BLACK cards against humanity - aggregated funniest\")\n",
        "## pick doesn't necessarily make sense here\n",
        "df_black = df.groupby(by=\"black_card_text\").agg(picks=(\"won\",\"sum\"), pick_opportunities=(\"won\",\"count\"),\n",
        "                                                pick_ratio=(\"won\",\"mean\"),round_skip_ratio=(\"round_skipped\",\"mean\"))\n",
        "df_black.sort_values([\"pick_ratio\",\"round_skip_ratio\"],ascending=False,inplace=True)\n",
        "\n",
        "df_black"
      ],
      "id": "burning-there",
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BLACK cards against humanity - aggregated funniest\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                                                               picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "black_card_text                                                                                                                                                                                       \n",
              "Problem: _____. Solution: _____. (PICK 2)                                                                                                         14                  70       0.200             0.000\n",
              "You: _____.   Me, an intellectual: _____. (PICK 2)                                                                                                10                  50       0.200             0.000\n",
              "In JorXXX Peele's new thriller, a young family discovers that _____ had really been _____ all along.                                             206                1070       0.193             0.037\n",
              "_____ is a slippery slope that leads to _____.                                                                                                  1300                6790       0.191             0.043\n",
              "_____ would be woefully incomplete without _____.                                                                                               1334                6970       0.191             0.043\n",
              "...                                                                                                                                              ...                 ...         ...               ...\n",
              "Instead of playing a card this round, everyone must stare at the Card Czar while making a sound you'd make after tasting something delicious.    462                6550       0.071             0.295\n",
              "I am so, so sorry everyone. I take full responsibility for _____.                                                                                  2                  30       0.067             0.333\n",
              "I hate to be that guy, but I just don't see the point of _____.                                                                                    2                  30       0.067             0.333\n",
              "Up on the shore they work all day Out in the sun they slave away While we devotin' Full time to _____ Under the sea!                               2                  30       0.067             0.333\n",
              "As Gregor Samsa awoke one morning from uneasy dreams, he found that he was _____.                                                                  3                  50       0.060             0.400\n",
              "\n",
              "[650 rows x 4 columns]"
            ],
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              "      <td>0.000</td>\n",
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              "    <tr>\n",
              "      <th>You: _____.   Me, an intellectual: _____. (PICK 2)</th>\n",
              "      <td>10</td>\n",
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              "      <td>0.000</td>\n",
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              "    <tr>\n",
              "      <th>In JorXXX Peele's new thriller, a young family discovers that _____ had really been _____ all along.</th>\n",
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              "      <td>0.193</td>\n",
              "      <td>0.037</td>\n",
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              "    <tr>\n",
              "      <th>_____ is a slippery slope that leads to _____.</th>\n",
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              "    <tr>\n",
              "      <th>Instead of playing a card this round, everyone must stare at the Card Czar while making a sound you'd make after tasting something delicious.</th>\n",
              "      <td>462</td>\n",
              "      <td>6550</td>\n",
              "      <td>0.071</td>\n",
              "      <td>0.295</td>\n",
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              "    <tr>\n",
              "      <th>I am so, so sorry everyone. I take full responsibility for _____.</th>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>0.067</td>\n",
              "      <td>0.333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I hate to be that guy, but I just don't see the point of _____.</th>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>0.067</td>\n",
              "      <td>0.333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Up on the shore they work all day Out in the sun they slave away While we devotin' Full time to _____ Under the sea!</th>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>0.067</td>\n",
              "      <td>0.333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>As Gregor Samsa awoke one morning from uneasy dreams, he found that he was _____.</th>\n",
              "      <td>3</td>\n",
              "      <td>50</td>\n",
              "      <td>0.060</td>\n",
              "      <td>0.400</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>650 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7d021155-321c-4fa9-b964-ae6cef8d1a44')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "\n",
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              "      border: none;\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-7d021155-321c-4fa9-b964-ae6cef8d1a44 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7d021155-321c-4fa9-b964-ae6cef8d1a44');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wanted-dakota",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        },
        "outputId": "558f87a3-01d1-4487-ae8f-b8daaf7abd37"
      },
      "source": [
        "df_black.sort_values([\"picks\",\"pick_opportunities\"],ascending=False)"
      ],
      "id": "wanted-dakota",
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                                      picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "black_card_text                                                                                                                                                              \n",
              "When you get right down to it, _____ is just _____.                                                                    1392                7430       0.187             0.063\n",
              "My life is ruled by a vicious cycle of _____ and _____.                                                                1386                7350       0.189             0.057\n",
              "This year's hottest album is \"_____\" by _____.                                                                         1356                7300       0.186             0.071\n",
              "My mom freaked out when she looked at my browser history and found _____.com/_____.                                    1356                7280       0.186             0.069\n",
              "You know, once you get past _____, _____ ain't so bad.                                                                 1354                7200       0.188             0.060\n",
              "...                                                                                                                     ...                 ...         ...               ...\n",
              "I am so, so sorry everyone. I take full responsibility for _____.                                                         2                  30       0.067             0.333\n",
              "I hate to be that guy, but I just don't see the point of _____.                                                           2                  30       0.067             0.333\n",
              "Up on the shore they work all day Out in the sun they slave away While we devotin' Full time to _____ Under the sea!      2                  30       0.067             0.333\n",
              "But I want to say one thing to the American people: I did not have sexual relations with _____.                           2                  20       0.100             0.000\n",
              "_____ is back! Only at McDonalds.                                                                                         1                  10       0.100             0.000\n",
              "\n",
              "[650 rows x 4 columns]"
            ],
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              "\n",
              "  <div id=\"df-8ec51acd-9ec9-450b-a1db-35081fd8d787\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "</style>\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>picks</th>\n",
              "      <th>pick_opportunities</th>\n",
              "      <th>pick_ratio</th>\n",
              "      <th>round_skip_ratio</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>black_card_text</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>When you get right down to it, _____ is just _____.</th>\n",
              "      <td>1392</td>\n",
              "      <td>7430</td>\n",
              "      <td>0.187</td>\n",
              "      <td>0.063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>My life is ruled by a vicious cycle of _____ and _____.</th>\n",
              "      <td>1386</td>\n",
              "      <td>7350</td>\n",
              "      <td>0.189</td>\n",
              "      <td>0.057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>This year's hottest album is \"_____\" by _____.</th>\n",
              "      <td>1356</td>\n",
              "      <td>7300</td>\n",
              "      <td>0.186</td>\n",
              "      <td>0.071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>My mom freaked out when she looked at my browser history and found _____.com/_____.</th>\n",
              "      <td>1356</td>\n",
              "      <td>7280</td>\n",
              "      <td>0.186</td>\n",
              "      <td>0.069</td>\n",
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              "    <tr>\n",
              "      <th>You know, once you get past _____, _____ ain't so bad.</th>\n",
              "      <td>1354</td>\n",
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              "      <td>0.188</td>\n",
              "      <td>0.060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I am so, so sorry everyone. I take full responsibility for _____.</th>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>0.067</td>\n",
              "      <td>0.333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I hate to be that guy, but I just don't see the point of _____.</th>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>0.067</td>\n",
              "      <td>0.333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Up on the shore they work all day Out in the sun they slave away While we devotin' Full time to _____ Under the sea!</th>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>0.067</td>\n",
              "      <td>0.333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>But I want to say one thing to the American people: I did not have sexual relations with _____.</th>\n",
              "      <td>2</td>\n",
              "      <td>20</td>\n",
              "      <td>0.100</td>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>_____ is back! Only at McDonalds.</th>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>0.100</td>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>650 rows × 4 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8ec51acd-9ec9-450b-a1db-35081fd8d787')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8ec51acd-9ec9-450b-a1db-35081fd8d787 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8ec51acd-9ec9-450b-a1db-35081fd8d787');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vertical-geology",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "7593671d-d66d-45ee-e2d6-2475c678c515"
      },
      "source": [
        "df_black.describe().round(2)"
      ],
      "id": "vertical-geology",
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "count   650.00              650.00      650.00            650.00\n",
              "mean    490.01             4599.31        0.10              0.06\n",
              "std     356.67             2850.48        0.03              0.05\n",
              "min       1.00               10.00        0.06              0.00\n",
              "25%      86.25              932.50        0.09              0.04\n",
              "50%     592.00             6275.00        0.10              0.05\n",
              "75%     624.00             6550.00        0.10              0.07\n",
              "max    1392.00             7430.00        0.20              0.40"
            ],
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              "\n",
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              "      <th>picks</th>\n",
              "      <th>pick_opportunities</th>\n",
              "      <th>pick_ratio</th>\n",
              "      <th>round_skip_ratio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>650.00</td>\n",
              "      <td>650.00</td>\n",
              "      <td>650.00</td>\n",
              "      <td>650.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>490.01</td>\n",
              "      <td>4599.31</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>356.67</td>\n",
              "      <td>2850.48</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>86.25</td>\n",
              "      <td>932.50</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>592.00</td>\n",
              "      <td>6275.00</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>624.00</td>\n",
              "      <td>6550.00</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1392.00</td>\n",
              "      <td>7430.00</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.40</td>\n",
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              "  </tbody>\n",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-7f7fd991-ad14-453f-becc-bc860ac29f43 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6d2cc33b"
      },
      "source": [
        "#### Filter data\n",
        "\n",
        "* drop pick 2  cards\n",
        "* Drop rounds where no card picked (ALT: could be alternate target)"
      ],
      "id": "6d2cc33b"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "355e9a19",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f77d1272-6f08-4580-bb75-22a50f0d17dd"
      },
      "source": [
        "if DROP_DOUBLES:\n",
        "    df = df.loc[~df[\"double_card\"]]\n",
        "    \n",
        "if DROP_SKIPPED:\n",
        "    df = df.loc[~df[\"round_skipped\"]]\n",
        "    \n",
        "print(df.shape[0])\n",
        "print(df.nunique())"
      ],
      "id": "355e9a19",
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2434500\n",
            "fake_round_id               243450\n",
            "round_completion_seconds      1657\n",
            "round_skipped                    1\n",
            "black_card_text                581\n",
            "black_card_pick_num              1\n",
            "white_card_text               2128\n",
            "won                              2\n",
            "winning_index                    1\n",
            "double_card                      1\n",
            "joke                        782827\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "golden-drilling"
      },
      "source": [
        "### Analyze pairs\n",
        "* Note cases with few occurrences imbalance the data\n",
        "* This is pairs that actually were shown to users (i.e #picks >= 1) "
      ],
      "id": "golden-drilling"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aggressive-promise",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "outputId": "ae723b02-7dfb-4b65-dd02-e0519db58c58"
      },
      "source": [
        "print(\"Winning pair combinations - aggregated funniest\")\n",
        "df_pairs = df.groupby(by=[\"white_card_text\",\"black_card_text\"]).agg(picks=(\"won\",\"sum\"), pick_opportunities=(\"won\",\"count\"),\n",
        "                                                pick_ratio=(\"won\",\"mean\"),round_skip_ratio=(\"round_skipped\",\"mean\")).sort_values(\"pick_ratio\",ascending=False)\n",
        "\n",
        "df_pairs"
      ],
      "id": "aggressive-promise",
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Winning pair combinations - aggregated funniest\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                                                                                                      picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "white_card_text                                         black_card_text                                                                                                                                                                      \n",
              "Nonsexual activities, such as roller skating.           And now, from WHYY in Philadelphia, it's _____ with Terry Gross.                                                                  1                   1         1.0               0.0\n",
              "Murder.                                                 As Teddy Roosevelt said, the four manly virtues are honor, temperance, industry, and _____.                                       1                   1         1.0               0.0\n",
              "A gay Republican somehow.                               She's a lady in the streets, _____ in the sheets.                                                                                 1                   1         1.0               0.0\n",
              "A terrified fat child who won't come out of the bushes. My grandfather worked his way up from nothing. When he came to this country, all he had was the shoes on his feet and _____.      1                   1         1.0               0.0\n",
              "Genghis Khan's DNA.                                     \"This is madness!\" \"No. THIS IS _____!\"                                                                                           1                   1         1.0               0.0\n",
              "...                                                                                                                                                                                     ...                 ...         ...               ...\n",
              "Frantically writing equations on a chalkboard.          _____. Betcha can't have just one!                                                                                                0                   5         0.0               0.0\n",
              "                                                        _____. High five, bro.                                                                                                            0                   4         0.0               0.0\n",
              "                                                        _____. It's a trap!                                                                                                               0                   6         0.0               0.0\n",
              "                                                        _____. That was so metal.                                                                                                         0                   3         0.0               0.0\n",
              "marvel                                                  ✮✩✩✩✩ Do NOT go here! Found _____ in my fettuccine alfredo!                                                                       0                   1         0.0               0.0\n",
              "\n",
              "[782827 rows x 4 columns]"
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              "      <th>Nonsexual activities, such as roller skating.</th>\n",
              "      <th>And now, from WHYY in Philadelphia, it's _____ with Terry Gross.</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Frantically writing equations on a chalkboard.</th>\n",
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              "      <td>5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "<p>782827 rows × 4 columns</p>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gentle-terrorism",
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          "height": 300
        },
        "outputId": "cafe1536-1ec7-441d-dcc0-2bbdaf2fbc03"
      },
      "source": [
        "df_pairs.describe()"
      ],
      "id": "gentle-terrorism",
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "count  782827.000          782827.000  782827.000          782827.0\n",
              "mean        0.311               3.110       0.100               0.0\n",
              "std         0.600               1.691       0.208               0.0\n",
              "min         0.000               1.000       0.000               0.0\n",
              "25%         0.000               2.000       0.000               0.0\n",
              "50%         0.000               3.000       0.000               0.0\n",
              "75%         1.000               4.000       0.111               0.0\n",
              "max         8.000              15.000       1.000               0.0"
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              "  <tbody>\n",
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              "      <th>count</th>\n",
              "      <td>782827.000</td>\n",
              "      <td>782827.000</td>\n",
              "      <td>782827.000</td>\n",
              "      <td>782827.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.311</td>\n",
              "      <td>3.110</td>\n",
              "      <td>0.100</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.600</td>\n",
              "      <td>1.691</td>\n",
              "      <td>0.208</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000</td>\n",
              "      <td>1.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000</td>\n",
              "      <td>2.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.000</td>\n",
              "      <td>3.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.000</td>\n",
              "      <td>4.000</td>\n",
              "      <td>0.111</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>8.000</td>\n",
              "      <td>15.000</td>\n",
              "      <td>1.000</td>\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "metadata": {},
          "execution_count": 34
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    {
      "cell_type": "code",
      "metadata": {
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        "colab": {
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          "height": 357
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        "outputId": "0e884f9b-87f8-4629-e266-b2c3d7f4691e"
      },
      "source": [
        "df_pairs[\"picks\"].hist();"
      ],
      "id": "executed-pastor",
      "execution_count": 35,
      "outputs": [
        {
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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "instructional-marijuana",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "16753137-7a67-49af-e1d4-fc72267afbf4"
      },
      "source": [
        "df_pairs[\"pick_opportunities\"].hist();"
      ],
      "id": "instructional-marijuana",
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "floppy-arena",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 729
        },
        "outputId": "53e35407-b384-4ec2-e580-f0902c307356"
      },
      "source": [
        "print(f\"Distrib for pairs that had AT LEAST MIN_PAIR_FREQ ({MIN_PAIR_FREQ})\")\n",
        "print(df_pairs.loc[df_pairs[\"pick_opportunities\"]>=MIN_PAIR_FREQ].describe())\n",
        "df_pairs.loc[df_pairs[\"pick_opportunities\"]>=MIN_PAIR_FREQ]"
      ],
      "id": "floppy-arena",
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Distrib for pairs that had AT LEAST MIN_PAIR_FREQ (1)\n",
            "            picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
            "count  782827.000          782827.000  782827.000          782827.0\n",
            "mean        0.311               3.110       0.100               0.0\n",
            "std         0.600               1.691       0.208               0.0\n",
            "min         0.000               1.000       0.000               0.0\n",
            "25%         0.000               2.000       0.000               0.0\n",
            "50%         0.000               3.000       0.000               0.0\n",
            "75%         1.000               4.000       0.111               0.0\n",
            "max         8.000              15.000       1.000               0.0\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                                                                                                      picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "white_card_text                                         black_card_text                                                                                                                                                                      \n",
              "Nonsexual activities, such as roller skating.           And now, from WHYY in Philadelphia, it's _____ with Terry Gross.                                                                  1                   1         1.0               0.0\n",
              "Murder.                                                 As Teddy Roosevelt said, the four manly virtues are honor, temperance, industry, and _____.                                       1                   1         1.0               0.0\n",
              "A gay Republican somehow.                               She's a lady in the streets, _____ in the sheets.                                                                                 1                   1         1.0               0.0\n",
              "A terrified fat child who won't come out of the bushes. My grandfather worked his way up from nothing. When he came to this country, all he had was the shoes on his feet and _____.      1                   1         1.0               0.0\n",
              "Genghis Khan's DNA.                                     \"This is madness!\" \"No. THIS IS _____!\"                                                                                           1                   1         1.0               0.0\n",
              "...                                                                                                                                                                                     ...                 ...         ...               ...\n",
              "Frantically writing equations on a chalkboard.          _____. Betcha can't have just one!                                                                                                0                   5         0.0               0.0\n",
              "                                                        _____. High five, bro.                                                                                                            0                   4         0.0               0.0\n",
              "                                                        _____. It's a trap!                                                                                                               0                   6         0.0               0.0\n",
              "                                                        _____. That was so metal.                                                                                                         0                   3         0.0               0.0\n",
              "marvel                                                  ✮✩✩✩✩ Do NOT go here! Found _____ in my fettuccine alfredo!                                                                       0                   1         0.0               0.0\n",
              "\n",
              "[782827 rows x 4 columns]"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>picks</th>\n",
              "      <th>pick_opportunities</th>\n",
              "      <th>pick_ratio</th>\n",
              "      <th>round_skip_ratio</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>white_card_text</th>\n",
              "      <th>black_card_text</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Nonsexual activities, such as roller skating.</th>\n",
              "      <th>And now, from WHYY in Philadelphia, it's _____ with Terry Gross.</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Murder.</th>\n",
              "      <th>As Teddy Roosevelt said, the four manly virtues are honor, temperance, industry, and _____.</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>A gay Republican somehow.</th>\n",
              "      <th>She's a lady in the streets, _____ in the sheets.</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>A terrified fat child who won't come out of the bushes.</th>\n",
              "      <th>My grandfather worked his way up from nothing. When he came to this country, all he had was the shoes on his feet and _____.</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Genghis Khan's DNA.</th>\n",
              "      <th>\"This is madness!\" \"No. THIS IS _____!\"</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Frantically writing equations on a chalkboard.</th>\n",
              "      <th>_____. Betcha can't have just one!</th>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>_____. High five, bro.</th>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>_____. It's a trap!</th>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>_____. That was so metal.</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>marvel</th>\n",
              "      <th>✮✩✩✩✩ Do NOT go here! Found _____ in my fettuccine alfredo!</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>782827 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f369bfb0-7fc3-4d5f-8f37-3ab28a81bcfd')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f369bfb0-7fc3-4d5f-8f37-3ab28a81bcfd button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f369bfb0-7fc3-4d5f-8f37-3ab28a81bcfd');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ddc8df0f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 718
        },
        "outputId": "6738e333-6d97-4ce0-b7d8-59f045832842"
      },
      "source": [
        "print(\"popular pairs / multiple times picked\")\n",
        "df_pop = df_pairs.loc[(df_pairs[\"pick_opportunities\"]>=2) & (df_pairs[\"picks\"]>1)].sort_values(\"picks\",ascending=False)\n",
        "print(df_pop.describe().round(2))\n",
        "print(df_pop.shape[0])\n",
        "print(\"nunique\",df_pop.reset_index()[[\"black_card_text\",\"white_card_text\"]].nunique())\n",
        "df_pop.reset_index()[[\"black_card_text\",\"white_card_text\",\"picks\"]].head(12)"
      ],
      "id": "ddc8df0f",
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "popular pairs / multiple times picked\n",
            "          picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
            "count  38412.00            38412.00    38412.00           38412.0\n",
            "mean       2.22                4.74        0.52               0.0\n",
            "std        0.51                1.67        0.20               0.0\n",
            "min        2.00                2.00        0.13               0.0\n",
            "25%        2.00                4.00        0.40               0.0\n",
            "50%        2.00                5.00        0.50               0.0\n",
            "75%        2.00                6.00        0.67               0.0\n",
            "max        8.00               15.00        1.00               0.0\n",
            "38412\n",
            "nunique black_card_text     437\n",
            "white_card_text    1951\n",
            "dtype: int64\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                  black_card_text                                          white_card_text  picks\n",
              "0                              Hey, honey. For the bedroom, were you thinking \"Robin's Egg Blue\" or \"_____ Pink?\"                                         My first period.      8\n",
              "1                                                    Run, run, as fast as you can! You can't catch me, I'm _____!                                                COVID-19.      8\n",
              "2                              Hey, honey. For the bedroom, were you thinking \"Robin's Egg Blue\" or \"_____ Pink?\"                               Chunks of dead hitchhiker.      7\n",
              "3                                                                                         Click Here for _____!!!  Bill Clinton, naked on a bearskin rug with a saxophone.      7\n",
              "4                                               Introducing X-treme Baseball! It's like baseball, but with _____!                                            Masturbating.      6\n",
              "5                                                                           Nothing says \"I love you\" like _____.                                             Necrophilia.      6\n",
              "6   The Department of Psychology is looking for paid research volunteers. Are you 18-25 and suffering from _____?                              Some really fucked-up shit.      6\n",
              "7                                                Awww, sick! I just saw this skater do a 720 kickflip into _____!                                 My math teacher's bulge.      6\n",
              "8                   Hi, this is Jim from accounting. We noticed a $1,200 charge labeled \"_____.\" Can you explain?                                           A sad handjob.      6\n",
              "9                                                                        What sounds great after four margaritas?                      Punching a congressman in the face.      6\n",
              "10                                                       Instead of coal, Santa now gives the bad children _____.                                            Dead parents.      6\n",
              "11                                                As the mom of five rambunctious boys, I'm no stranger to _____.                                      Boring vaginal sex.      6"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0a623c11-7d02-496d-9db5-3f63d7bb9712\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>black_card_text</th>\n",
              "      <th>white_card_text</th>\n",
              "      <th>picks</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Hey, honey. For the bedroom, were you thinking \"Robin's Egg Blue\" or \"_____ Pink?\"</td>\n",
              "      <td>My first period.</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Run, run, as fast as you can! You can't catch me, I'm _____!</td>\n",
              "      <td>COVID-19.</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Hey, honey. For the bedroom, were you thinking \"Robin's Egg Blue\" or \"_____ Pink?\"</td>\n",
              "      <td>Chunks of dead hitchhiker.</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Click Here for _____!!!</td>\n",
              "      <td>Bill Clinton, naked on a bearskin rug with a saxophone.</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Introducing X-treme Baseball! It's like baseball, but with _____!</td>\n",
              "      <td>Masturbating.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Nothing says \"I love you\" like _____.</td>\n",
              "      <td>Necrophilia.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>The Department of Psychology is looking for paid research volunteers. Are you 18-25 and suffering from _____?</td>\n",
              "      <td>Some really fucked-up shit.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Awww, sick! I just saw this skater do a 720 kickflip into _____!</td>\n",
              "      <td>My math teacher's bulge.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Hi, this is Jim from accounting. We noticed a $1,200 charge labeled \"_____.\" Can you explain?</td>\n",
              "      <td>A sad handjob.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>What sounds great after four margaritas?</td>\n",
              "      <td>Punching a congressman in the face.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Instead of coal, Santa now gives the bad children _____.</td>\n",
              "      <td>Dead parents.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>As the mom of five rambunctious boys, I'm no stranger to _____.</td>\n",
              "      <td>Boring vaginal sex.</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0a623c11-7d02-496d-9db5-3f63d7bb9712')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0a623c11-7d02-496d-9db5-3f63d7bb9712 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0a623c11-7d02-496d-9db5-3f63d7bb9712');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e8aa65f1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e955a61c-81a8-43a1-a021-af5807993154"
      },
      "source": [
        "# df_pop.loc[df_pop[\"picks\"]>2].reset_index().sort_values([\"white_card_text\",\"picks\"],ascending=False)[[\"white_card_text\",\"black_card_text\"]].head(15).values\n",
        "df_pop.loc[df_pop[\"picks\"]>2].reset_index().sort_values([\"white_card_text\",\"picks\"],ascending=False)[\"black_card_text\"].head(15).values"
      ],
      "id": "e8aa65f1",
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['FW: re: FBI WARNING!!! VIOLENT GANGS USING _____ TO RECRUIT CHILDREN!',\n",
              "       'Computer! Display _____ on screen. Enhance.',\n",
              "       \"Seriously guys, there's nothing funny about _____.\",\n",
              "       \"Hi MTV! My name is Kendra, I live in Malibu, I'm into _____, and I love to have a good time.\",\n",
              "       'The secret to a lasting marriage is communication, communication, and _____.',\n",
              "       'The blind date was going horribly until we discovered our shared interest in _____.',\n",
              "       \"After four platinum albums and three Grammys, it's time to get back to my roots, to what inspired me to make music in the first place: _____.\",\n",
              "       'Why my mustache smell so bad?',\n",
              "       'Having tired of poetry and music, the immortal elves now fill their days with _____.',\n",
              "       'What will end racism once and for all?',\n",
              "       '_____: kid-tested, mother-approved.',\n",
              "       'IF you like _____, YOU MIGHT BE A REDNECK.',\n",
              "       'What totally destroyed my asshole?',\n",
              "       'Why my mustache smell so bad?',\n",
              "       'I tell you, it was a non-stop fuckfest. When it was over, my asshole looked like _____.'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "pressing-equilibrium",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 316
        },
        "outputId": "e6fc5eb0-1d5f-4afc-de36-c3ed7b5e6873"
      },
      "source": [
        "df_pairs.loc[df_pairs[\"pick_opportunities\"]>=4].head()"
      ],
      "id": "pressing-equilibrium",
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                                               picks  pick_opportunities  pick_ratio  round_skip_ratio\n",
              "white_card_text                             black_card_text                                                                                                                           \n",
              "A gay Republican somehow.                   Coming to Red Lobster® this month, _____.                                              4                   4         1.0               0.0\n",
              "The Great Depression.                       What are all those whales singing about?                                               5                   5         1.0               0.0\n",
              "Viagra.®                                    I've got rhythm, I've got music, I've got _____. Who could ask for anything more?      5                   5         1.0               0.0\n",
              "Forty-two years of repressed homosexuality. What is George W. Bush thinking about right now?                                       4                   4         1.0               0.0\n",
              "The Devil himself.                          Jesus is _____.                                                                        5                   5         1.0               0.0"
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              "      <th>round_skip_ratio</th>\n",
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              "\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1513854b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "be40a65a-b560-4542-aa97-be23c61ab1a6"
      },
      "source": [
        "df_pairs[[\"pick_opportunities\",\"picks\",\"pick_ratio\"]].corr() # ,\"picks_sum\""
      ],
      "id": "1513854b",
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    pick_opportunities  picks  pick_ratio\n",
              "pick_opportunities               1.000  0.285       0.003\n",
              "picks                            0.285  1.000       0.809\n",
              "pick_ratio                       0.003  0.809       1.000"
            ],
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              "\n",
              "  <div id=\"df-fcdb0f6e-22fd-417f-9ad9-67875134fa77\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "        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>pick_opportunities</th>\n",
              "      <th>picks</th>\n",
              "      <th>pick_ratio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>pick_opportunities</th>\n",
              "      <td>1.000</td>\n",
              "      <td>0.285</td>\n",
              "      <td>0.003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>picks</th>\n",
              "      <td>0.285</td>\n",
              "      <td>1.000</td>\n",
              "      <td>0.809</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pick_ratio</th>\n",
              "      <td>0.003</td>\n",
              "      <td>0.809</td>\n",
              "      <td>1.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
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              "\n",
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              "\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fcdb0f6e-22fd-417f-9ad9-67875134fa77 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fcdb0f6e-22fd-417f-9ad9-67875134fa77');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wireless-karen",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a20e7b79-8943-4c52-967f-275959f3a922"
      },
      "source": [
        "print(\" 2<=\",df_pairs.loc[df_pairs[\"pick_opportunities\"]<=2].shape[0])\n",
        "print(\" >= 3\",df_pairs.loc[df_pairs[\"pick_opportunities\"]>=3].shape[0])\n",
        "print(\" >= 5\",df_pairs.loc[df_pairs[\"pick_opportunities\"]>=5].shape[0])\n",
        "print(\" >= 7\",df_pairs.loc[df_pairs[\"pick_opportunities\"]>=7].shape[0])\n",
        "100*df_pairs[\"pick_opportunities\"].value_counts(normalize=True).round(4).sort_index()"
      ],
      "id": "wireless-karen",
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " 2<= 323559\n",
            " >= 3 459268\n",
            " >= 5 154501\n",
            " >= 7 29652\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1     19.10\n",
              "2     22.23\n",
              "3     22.03\n",
              "4     16.90\n",
              "5     10.51\n",
              "6      5.43\n",
              "7      2.41\n",
              "8      0.92\n",
              "9      0.32\n",
              "10     0.10\n",
              "11     0.03\n",
              "12     0.01\n",
              "13     0.00\n",
              "14     0.00\n",
              "15     0.00\n",
              "Name: pick_opportunities, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6163b5c0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "79289d5e-62a3-484c-a70a-5f8d4a1e6734"
      },
      "source": [
        "print(df_pairs[\"picks\"].value_counts().sort_index())\n",
        "100*df_pairs[\"picks\"].value_counts(normalize=True).sort_index()"
      ],
      "id": "6163b5c0",
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    586246\n",
            "1    158169\n",
            "2     31409\n",
            "3      5779\n",
            "4      1024\n",
            "5       176\n",
            "6        20\n",
            "7         2\n",
            "8         2\n",
            "Name: picks, dtype: int64\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    7.489e+01\n",
              "1    2.020e+01\n",
              "2    4.012e+00\n",
              "3    7.382e-01\n",
              "4    1.308e-01\n",
              "5    2.248e-02\n",
              "6    2.555e-03\n",
              "7    2.555e-04\n",
              "8    2.555e-04\n",
              "Name: picks, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tired-charleston"
      },
      "source": [
        "# Initial classification target:  Was a card combination ever picked? \n",
        "* Ideally we'd use a higher threshhold, e.g. at least 3-5 instances, but that leaves us with relatively little data. \n",
        "* binary target: was it ever picked, for a given combo. (i.e clip at 1, 0/1)"
      ],
      "id": "tired-charleston"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "26b63513",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "46219d74-7392-4a7f-fad4-e52b4bdb18c1"
      },
      "source": [
        "df_pairs[\"pick_opportunities\"].describe()"
      ],
      "id": "26b63513",
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    782827.000\n",
              "mean          3.110\n",
              "std           1.691\n",
              "min           1.000\n",
              "25%           2.000\n",
              "50%           3.000\n",
              "75%           4.000\n",
              "max          15.000\n",
              "Name: pick_opportunities, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "94d2ec93"
      },
      "source": [
        "* We can set the target to be picked at leat once, or picked more than a random uniform average (~10.6%)\n",
        "    * We can use the background uniform distribution, instead of the distrib for \"popularly picked\". "
      ],
      "id": "94d2ec93"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "33367bf3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9fe595cd-5609-459b-f42b-d2af8ab88ed8"
      },
      "source": [
        "df_pairs[\"pick_ratio\"] = df_pairs[\"picks\"].div(df_pairs[\"pick_opportunities\"])\n",
        "# print(\"global pick_ratio\\n\",df_pairs[\"pick_ratio\"].describe())\n",
        "print(df_pairs.loc[df_pairs[\"pick_opportunities\"]>=MIN_PAIR_FREQ][\"pick_ratio\"].describe())\n",
        "\n",
        "MEAN_PICK_RATIO = df_pairs.loc[df_pairs[\"pick_opportunities\"]>=MIN_PAIR_FREQ][\"pick_ratio\"].mean() + 0.005 # .median() #"
      ],
      "id": "33367bf3",
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "count    782827.000\n",
            "mean          0.100\n",
            "std           0.208\n",
            "min           0.000\n",
            "25%           0.000\n",
            "50%           0.000\n",
            "75%           0.111\n",
            "max           1.000\n",
            "Name: pick_ratio, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "material-parker",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a867ec92-22cf-4293-8efb-fbef11fd6627"
      },
      "source": [
        "print(df_pairs.shape[0],f\"# rows before filter of MIN_PAIR_FREQ ({MIN_PAIR_FREQ})\")\n",
        "df_data = df_pairs.loc[df_pairs[\"pick_opportunities\"]>=MIN_PAIR_FREQ][[\"picks\",\"pick_opportunities\"]].copy()\n",
        "df_data[\"pick_ratio\"] = df_data[\"picks\"].div(df_data[\"pick_opportunities\"]) ## target % , instead of boolean\n",
        "df_data[\"picks_sum\"] = df_data[\"picks\"] # copy of raw count of times picked as funny\n",
        "## We can set the target to be picked at leat once, or picked more than a random uniform average (~10.6%)\n",
        "df_data[\"picks\"] = df_data[\"picks\"].clip(upper=1) # Bool target \n",
        "print(df_data[\"picks\"].mean(), \"boolean target mean\")\n",
        "\n",
        "# ## OPTIONAL: change to \"picked more than most\" target\n",
        "# df_data[\"picks\"] = (df_data[\"pick_ratio\"] > MEAN_PICK_RATIO).astype(int)\n",
        "\n",
        "print(df_data.shape[0],\"# rows after filter\")\n",
        "print(\"pick_ratio\\n\",df_data[\"pick_ratio\"].describe())\n",
        "print(df_data[\"picks\"].mean(), \"target mean\")"
      ],
      "id": "material-parker",
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "782827 # rows before filter of MIN_PAIR_FREQ (1)\n",
            "0.2511167857010553 boolean target mean\n",
            "782827 # rows after filter\n",
            "pick_ratio\n",
            " count    782827.000\n",
            "mean          0.100\n",
            "std           0.208\n",
            "min           0.000\n",
            "25%           0.000\n",
            "50%           0.000\n",
            "75%           0.111\n",
            "max           1.000\n",
            "Name: pick_ratio, dtype: float64\n",
            "0.2511167857010553 target mean\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "opposed-miami",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "9901c6db-adc7-4cd2-e052-8e2ba2b0c226"
      },
      "source": [
        "## add total count of black, white cards\n",
        "df_data = df_data.join(df_black[[\"pick_opportunities\",\"round_skip_ratio\"]].rename(columns={\"pick_opportunities\":\"black_counts\",\n",
        "                                                                                 \"round_skip_ratio\":\"black_round_skip_ratio\"}),  on=\"black_card_text\")\n",
        "\n",
        "df_data = df_data.join(df_white[[\"pick_opportunities\"]].rename({\"pick_opportunities\":\"white_counts\" },axis=1),on=\"white_card_text\")\n",
        "\n",
        "df_data.reset_index(inplace=True)\n",
        "print(df_data.shape)\n",
        "df_data.sort_values([\"pick_ratio\"],ascending=False)"
      ],
      "id": "opposed-miami",
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(782827, 9)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "                                                       white_card_text                                                                            black_card_text  picks  pick_opportunities  pick_ratio  picks_sum  black_counts  black_round_skip_ratio  white_counts\n",
              "0                        Nonsexual activities, such as roller skating.                           And now, from WHYY in Philadelphia, it's _____ with Terry Gross.      1                   1         1.0          1            70                   0.000          1505\n",
              "12031                                                  The government.                                                              What makes me cry every time?      1                   1         1.0          1          1240                   0.024          1575\n",
              "12037               Sucking the caviar straight out of a fish's pussy.        I work my ass off all day for this family, and this is what I come home to? _____!?      1                   1         1.0          1          6320                   0.047          1472\n",
              "12036                                      A positive male role model.                                          I just took a DNA test, turns out I'm 100% _____.      1                   1         1.0          1          1260                   0.087          1533\n",
              "12035               Sucking the caviar straight out of a fish's pussy.                                              I have solved politics. My solution is _____.      1                   1         1.0          1          6390                   0.050          1472\n",
              "...                                                                ...                                                                                        ...    ...                 ...         ...        ...           ...                     ...           ...\n",
              "391990  Sewing two hamsters together to make a Double Hamster Supreme.  This season at Steppenwolf, Samuel Beckett's classic existential play: Waiting for _____.      0                   2         0.0          0          6100                   0.090          1489\n",
              "391989  Sewing two hamsters together to make a Double Hamster Supreme.                            This season at Manhattan Theatre Club: \"Who's afraid of _____?\"      0                   2         0.0          0          6640                   0.047          1489\n",
              "391988  Sewing two hamsters together to make a Double Hamster Supreme.                This is your captain speaking. Fasten your seatbelts and prepare for _____.      0                   3         0.0          0          6550                   0.053          1489\n",
              "391987  Sewing two hamsters together to make a Double Hamster Supreme.                    The Japanese have developed a smaller, more efficient version of _____.      0                   1         0.0          0          6790                   0.059          1489\n",
              "782826                                                          marvel                                ✮✩✩✩✩ Do NOT go here! Found _____ in my fettuccine alfredo!      0                   1         0.0          0          6210                   0.056          1430\n",
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              "<p>782827 rows × 9 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e3fc4b84-b38f-4d9b-9802-a31a0450d119')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e3fc4b84-b38f-4d9b-9802-a31a0450d119 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e3fc4b84-b38f-4d9b-9802-a31a0450d119');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_data.describe().round(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "1gZDPrS1cU3J",
        "outputId": "68ae939b-9f21-435c-95d0-bbb6ecf9a445"
      },
      "id": "1gZDPrS1cU3J",
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           picks  pick_opportunities  pick_ratio  picks_sum  black_counts  black_round_skip_ratio  white_counts\n",
              "count  782827.00           782827.00   782827.00  782827.00     782827.00               782827.00     782827.00\n",
              "mean        0.25                3.11        0.10       0.31       6095.87                    0.06       1515.04\n",
              "std         0.43                1.69        0.21       0.60       1322.21                    0.02        135.89\n",
              "min         0.00                1.00        0.00       0.00         10.00                    0.00         19.00\n",
              "25%         0.00                2.00        0.00       0.00       6180.00                    0.04       1500.00\n",
              "50%         0.00                3.00        0.00       0.00       6390.00                    0.05       1527.00\n",
              "75%         1.00                4.00        0.11       1.00       6580.00                    0.06       1554.00\n",
              "max         1.00               15.00        1.00       8.00       7410.00                    0.40       3006.00"
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              "      <th></th>\n",
              "      <th>picks</th>\n",
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              "      <th>count</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.25</td>\n",
              "      <td>3.11</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.31</td>\n",
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              "    </tr>\n",
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              "      <th>std</th>\n",
              "      <td>0.43</td>\n",
              "      <td>1.69</td>\n",
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              "      <th>min</th>\n",
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              "      <td>0.40</td>\n",
              "      <td>3006.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c22bc4a2-1cbb-4418-a46e-f33e1e3e9190')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c22bc4a2-1cbb-4418-a46e-f33e1e3e9190 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c22bc4a2-1cbb-4418-a46e-f33e1e3e9190');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aware-equivalent"
      },
      "source": [
        "## Save data with just 3 cols"
      ],
      "id": "aware-equivalent"
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "WNYeqiGPcJEr",
        "outputId": "c9a8cdc3-3a8f-4117-b181-265f366c3e2a"
      },
      "id": "WNYeqiGPcJEr",
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            picks\n",
              "count  782827.000\n",
              "mean        0.251\n",
              "std         0.434\n",
              "min         0.000\n",
              "25%         0.000\n",
              "50%         0.000\n",
              "75%         1.000\n",
              "max         1.000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-01c3048b-a939-4d6f-b644-a8ed36343dfa\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>picks</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>782827.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.251</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-01c3048b-a939-4d6f-b644-a8ed36343dfa')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-01c3048b-a939-4d6f-b644-a8ed36343dfa button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-01c3048b-a939-4d6f-b644-a8ed36343dfa');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "traditional-missile"
      },
      "source": [
        "if SAVE_TRAIN_DATA:\n",
        "    df_data[[\"black_card_text\",\"white_card_text\",\"picks\",\"pick_opportunities\",\"picks_sum\"]].sample(frac=1).to_csv(f\"cah_min{MIN_PAIR_FREQ}_v2.csv.gz\",index=False,compression=\"gzip\")"
      ],
      "id": "traditional-missile",
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "composed-adobe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "outputId": "f27cdc2e-4618-4588-98b8-0c8ca9f8443c"
      },
      "source": [
        "df = df_data[[\"black_card_text\",\"white_card_text\",\"picks\"]].sample(frac=1)#.values\n",
        "df"
      ],
      "id": "composed-adobe",
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                                                                         black_card_text                                        white_card_text  picks\n",
              "634020                                                                          When I pooped, what came out of my butt?            Huffing and puffing and blowing my stepdad.      0\n",
              "415089                                                    Fear leads to anger. Anger leads to hate. Hate leads to _____.                              The arrival of the pizza.      0\n",
              "499490                               My memory of last night is pretty hazy. I remember _____ and that's pretty much it.                                               Chowder.      0\n",
              "128513                                                                               What are my parents hiding from me?                      Deregulating the mortgage market.      1\n",
              "36509                    Coming up on Turner Classic Movies: Sean Connery and Alec Baldwin star in \"The Hunt for _____.\"        Stealing a child's nose and keeping it forever.      1\n",
              "...                                                                                                                  ...                                                    ...    ...\n",
              "713625                                                                                        Yo' mama so fat she _____!                               Falling into the toilet.      0\n",
              "603042     Call the law offices of Goldstein & Goldstein, because no one should have to tolerate _____ in the workplace.  A man with the head of a goat and the body of a goat.      0\n",
              "321124                                                   Little Miss Muffet Sat on a tuffet, Eating her curds and _____.                                 The rhythms of Africa.      0\n",
              "119241  Pledges! Time to prove you're Delta Phi material. Chug this beer, take off your shirts, and get ready for _____.      Shitting all over the floor like a bad, bad girl.      1\n",
              "769882                                                                      All classes today are canceled due to _____.                      Film roles for actresses over 40.      0\n",
              "\n",
              "[782827 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a55d8d62-6753-4426-929d-9267fcf8034f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "    .dataframe thead th {\n",
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              "      <th>picks</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>634020</th>\n",
              "      <td>When I pooped, what came out of my butt?</td>\n",
              "      <td>Huffing and puffing and blowing my stepdad.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>415089</th>\n",
              "      <td>Fear leads to anger. Anger leads to hate. Hate leads to _____.</td>\n",
              "      <td>The arrival of the pizza.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>499490</th>\n",
              "      <td>My memory of last night is pretty hazy. I remember _____ and that's pretty much it.</td>\n",
              "      <td>Chowder.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128513</th>\n",
              "      <td>What are my parents hiding from me?</td>\n",
              "      <td>Deregulating the mortgage market.</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36509</th>\n",
              "      <td>Coming up on Turner Classic Movies: Sean Connery and Alec Baldwin star in \"The Hunt for _____.\"</td>\n",
              "      <td>Stealing a child's nose and keeping it forever.</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>713625</th>\n",
              "      <td>Yo' mama so fat she _____!</td>\n",
              "      <td>Falling into the toilet.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>603042</th>\n",
              "      <td>Call the law offices of Goldstein &amp; Goldstein, because no one should have to tolerate _____ in the workplace.</td>\n",
              "      <td>A man with the head of a goat and the body of a goat.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>321124</th>\n",
              "      <td>Little Miss Muffet Sat on a tuffet, Eating her curds and _____.</td>\n",
              "      <td>The rhythms of Africa.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119241</th>\n",
              "      <td>Pledges! Time to prove you're Delta Phi material. Chug this beer, take off your shirts, and get ready for _____.</td>\n",
              "      <td>Shitting all over the floor like a bad, bad girl.</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>769882</th>\n",
              "      <td>All classes today are canceled due to _____.</td>\n",
              "      <td>Film roles for actresses over 40.</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>782827 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a55d8d62-6753-4426-929d-9267fcf8034f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a55d8d62-6753-4426-929d-9267fcf8034f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a55d8d62-6753-4426-929d-9267fcf8034f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    }
  ]
}