Weighted_Naive_Bayes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import numpy.random as rnd\n",
    "import seaborn as sns\n",
    "from matplotlib import animation\n",
    "import pymc3 as pm\n",
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Read datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>roll</th>\n",
       "      <th>adv</th>\n",
       "      <th>stat</th>\n",
       "      <th>basis</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12</td>\n",
       "      <td>advantage</td>\n",
       "      <td>ATTACK</td>\n",
       "      <td>melee</td>\n",
       "      <td>attack</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>advantage</td>\n",
       "      <td>INIT</td>\n",
       "      <td>perception</td>\n",
       "      <td>check</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16</td>\n",
       "      <td>advantage</td>\n",
       "      <td>WIS</td>\n",
       "      <td>strength</td>\n",
       "      <td>save</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16</td>\n",
       "      <td>advantage</td>\n",
       "      <td>DEX</td>\n",
       "      <td>melee</td>\n",
       "      <td>attack</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>disadvantage</td>\n",
       "      <td>ATTACK</td>\n",
       "      <td>melee</td>\n",
       "      <td>attack</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   roll           adv    stat       basis    type\n",
       "0    12     advantage  ATTACK       melee  attack\n",
       "1    16     advantage    INIT  perception   check\n",
       "2    16     advantage     WIS    strength    save\n",
       "3    16     advantage     DEX       melee  attack\n",
       "4     2  disadvantage  ATTACK       melee  attack"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the WEIGHTED data\n",
    "data = pd.read_csv(r\"nerd_shit1.csv\")\n",
    "data = data.iloc[:,1:]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>episode</th>\n",
       "      <th>roll</th>\n",
       "      <th>mod</th>\n",
       "      <th>basis</th>\n",
       "      <th>type</th>\n",
       "      <th>adv</th>\n",
       "      <th>nat</th>\n",
       "      <th>adv_num</th>\n",
       "      <th>stat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>wisdom</td>\n",
       "      <td>save</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>WIS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>investigation</td>\n",
       "      <td>check</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>INT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>dexterity</td>\n",
       "      <td>save</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>DEX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>7</td>\n",
       "      <td>melee</td>\n",
       "      <td>attack</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>ATTACK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>7</td>\n",
       "      <td>melee</td>\n",
       "      <td>attack</td>\n",
       "      <td>advantage</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>ATTACK</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   season  episode  roll  mod          basis    type        adv    nat  \\\n",
       "0       3        1    13    0         wisdom    save        NaN  False   \n",
       "1       3        1    17    0  investigation   check        NaN  False   \n",
       "2       3        1     4    2      dexterity    save        NaN  False   \n",
       "3       3        2    16    7          melee  attack        NaN  False   \n",
       "4       3        2    16    7          melee  attack  advantage  False   \n",
       "\n",
       "   adv_num    stat  \n",
       "0        0     WIS  \n",
       "1        0     INT  \n",
       "2        0     DEX  \n",
       "3        0  ATTACK  \n",
       "4        1  ATTACK  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file2 = \"TravisRollsDataset.csv\"\n",
    "data2 = pd.read_csv(file2)\n",
    "data2 = data2.iloc[:,1:]\n",
    "data2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Data pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a column to delineate between simulated data and Travis' rolls\n",
    "# 0 is a Travis roll\n",
    "deter = [0] * len(data2)\n",
    "data2[\"deter\"] = deter\n",
    "\n",
    "# 1 is a generated roll\n",
    "deter = [1] * len(data)\n",
    "data[\"deter\"] = deter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pick out shared columns\n",
    "col_names = list(data.columns)\n",
    "merge1 = data[col_names]\n",
    "merge2 = data2[col_names]\n",
    "\n",
    "# merge the datasets\n",
    "total_data_rodeo = pd.concat([merge1, merge2], axis=0).reset_index()\n",
    "\n",
    "# shuffle the data 3x in replicable way\n",
    "rodeo = total_data_rodeo.sample(frac=1, random_state=1234567).reset_index(drop=True)\n",
    "rodeo = rodeo.sample(frac=1, random_state=57389).reset_index(drop=True)\n",
    "rodeo = rodeo.sample(frac=1, random_state=98754).reset_index(drop=True)\n",
    "rodeo = rodeo[col_names]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# put rolls into bins\n",
    "rodeo[\"new_rolls\"] = pd.cut(rodeo.roll, bins=[0, 12, 20], labels=[\"0-11\", \"12-20\"])\n",
    "rodeo = rodeo.drop(\"roll\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sample 2/3 of the data\n",
    "dnd_train, dnd_test = train_test_split(rodeo, test_size=1/3, random_state = 2263748)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dnd_train = dnd_train.set_index(\"deter\")\n",
    "# dummy code the variables to get the word list\n",
    "dnd_dum = pd.get_dummies(dnd_train)\n",
    "\n",
    "column_list = list(dnd_dum.columns)\n",
    "column_list.remove(\"deter\")\n",
    "#column_list.remove(\"new_rolls\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "agg_dict = {}\n",
    "for column in column_list:\n",
    "    agg_dict[column] = \"sum\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>deter</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>adv_advantage</th>\n",
       "      <td>10.0</td>\n",
       "      <td>1049.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>adv_disadvantage</th>\n",
       "      <td>2.0</td>\n",
       "      <td>284.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stat_ATTACK</th>\n",
       "      <td>36.0</td>\n",
       "      <td>439.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stat_CHA</th>\n",
       "      <td>8.0</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stat_CON</th>\n",
       "      <td>5.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "deter                0       1\n",
       "adv_advantage     10.0  1049.0\n",
       "adv_disadvantage   2.0   284.0\n",
       "stat_ATTACK       36.0   439.0\n",
       "stat_CHA           8.0    92.0\n",
       "stat_CON           5.0    43.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group by determination, sum all other columns\n",
    "groupies = pd.DataFrame(dnd_dum.groupby(\"deter\").agg(agg_dict))\n",
    "\n",
    "dummies = groupies.T\n",
    "dummies.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Generate Priors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 113 Travis rolls and 1333 Roll20 generated rolls in our training set.\n",
      "\n",
      "The prior probability of a roll being from Travis is 0.0781 and that of being Roll20 generated is 0.9219\n"
     ]
    }
   ],
   "source": [
    "# calculate the priors\n",
    "count = dnd_train.groupby(\"deter\").size()\n",
    "print(\"There are\", count.iloc[0], \"Travis rolls and\", count.iloc[1], \"Roll20 generated rolls in our training set.\" )\n",
    "\n",
    "nrolls = np.array([count.iloc[0], count.iloc[1]])\n",
    "\n",
    "# take sums\n",
    "total_rolls = sum(nrolls)\n",
    "\n",
    "# find proportion of edible and poisonous mushrooms to all\n",
    "priors = nrolls/total_rolls\n",
    "print(\"\\nThe prior probability of a roll being from Travis is\", round(priors[0], 4), \"and that of being Roll20 generated is\", round(priors[1], 4))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# find the sum of the wordlist\n",
    "dum_sums = dummies.sum(0)\n",
    "\n",
    "# number of distinct words in the data\n",
    "v = len(dummies.index)\n",
    "# smoothing parameter\n",
    "α = 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>deter</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>adv_advantage</th>\n",
       "      <td>10.0</td>\n",
       "      <td>1049.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>adv_disadvantage</th>\n",
       "      <td>2.0</td>\n",
       "      <td>284.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stat_ATTACK</th>\n",
       "      <td>36.0</td>\n",
       "      <td>439.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stat_CHA</th>\n",
       "      <td>8.0</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stat_CON</th>\n",
       "      <td>5.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "deter                0       1\n",
       "adv_advantage     10.0  1049.0\n",
       "adv_disadvantage   2.0   284.0\n",
       "stat_ATTACK       36.0   439.0\n",
       "stat_CHA           8.0    92.0\n",
       "stat_CON           5.0    43.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummies.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Generate Likelihoods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.022308</td>\n",
       "      <td>0.159203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.006790</td>\n",
       "      <td>0.043267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.072745</td>\n",
       "      <td>0.066758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.018429</td>\n",
       "      <td>0.014170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.012609</td>\n",
       "      <td>0.006744</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1\n",
       "0  0.022308  0.159203\n",
       "1  0.006790  0.043267\n",
       "2  0.072745  0.066758\n",
       "3  0.018429  0.014170\n",
       "4  0.012609  0.006744"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find the likelihood of each trait in the list\n",
    "proll = np.zeros([len(dummies.index), len(dummies.columns)])\n",
    "for i in range(len(dummies.index)):\n",
    "    for j in range(len(dummies.columns)):\n",
    "        proll[i,j] = (dummies.iloc[i,j] + α)/(dum_sums[j] + v*α)\n",
    "proll = pd.DataFrame(proll)\n",
    "proll.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adv_advantage</th>\n",
       "      <th>adv_disadvantage</th>\n",
       "      <th>stat_ATTACK</th>\n",
       "      <th>stat_CHA</th>\n",
       "      <th>stat_CON</th>\n",
       "      <th>stat_DEX</th>\n",
       "      <th>stat_INIT</th>\n",
       "      <th>stat_INT</th>\n",
       "      <th>stat_STR</th>\n",
       "      <th>stat_WIS</th>\n",
       "      <th>...</th>\n",
       "      <th>basis_sleight of hand</th>\n",
       "      <th>basis_stealth</th>\n",
       "      <th>basis_strength</th>\n",
       "      <th>basis_thieves’ tools</th>\n",
       "      <th>basis_wisdom</th>\n",
       "      <th>type_attack</th>\n",
       "      <th>type_check</th>\n",
       "      <th>type_save</th>\n",
       "      <th>new_rolls_0-11</th>\n",
       "      <th>new_rolls_12-20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   adv_advantage  adv_disadvantage  stat_ATTACK  stat_CHA  stat_CON  stat_DEX  \\\n",
       "0              1                 0            0         0         0         0   \n",
       "1              1                 0            0         0         0         1   \n",
       "2              1                 0            0         0         0         0   \n",
       "3              1                 0            1         0         0         0   \n",
       "4              1                 0            0         1         0         0   \n",
       "\n",
       "   stat_INIT  stat_INT  stat_STR  stat_WIS  ...  basis_sleight of hand  \\\n",
       "0          0         0         0         1  ...                      0   \n",
       "1          0         0         0         0  ...                      0   \n",
       "2          0         0         1         0  ...                      0   \n",
       "3          0         0         0         0  ...                      1   \n",
       "4          0         0         0         0  ...                      0   \n",
       "\n",
       "   basis_stealth  basis_strength  basis_thieves’ tools  basis_wisdom  \\\n",
       "0              0               0                     0             0   \n",
       "1              0               1                     0             0   \n",
       "2              0               1                     0             0   \n",
       "3              0               0                     0             0   \n",
       "4              0               0                     0             0   \n",
       "\n",
       "   type_attack  type_check  type_save  new_rolls_0-11  new_rolls_12-20  \n",
       "0            0           1          0               0                1  \n",
       "1            0           1          0               0                1  \n",
       "2            0           0          1               0                1  \n",
       "3            0           1          0               0                1  \n",
       "4            1           0          0               0                1  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# process the test data -- take dummies\n",
    "dnd_test_dum = pd.get_dummies(dnd_test).reset_index(drop=True).copy()\n",
    "\n",
    "# drop column we will predict\n",
    "dnd_test_dum = dnd_test_dum.drop(columns=[\"deter\"], inplace=False)\n",
    "dnd_test_dum.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Calculate Posteriors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_posteriors(dummy_dataset, likelihood_src):\n",
    "    # create dummy dataframes filled with 1s\n",
    "    nrows = len(dummy_dataset.index)\n",
    "    ncols = len(dummy_dataset.columns)\n",
    "    likelihood_travis = pd.DataFrame(index = range(nrows), \n",
    "                        columns = range(ncols))\n",
    "    likelihood_travis = likelihood_travis.fillna(value=1)\n",
    "\n",
    "    likelihood_rand = pd.DataFrame(index = range(nrows), \n",
    "                        columns = range(ncols))\n",
    "    likelihood_rand = likelihood_rand.fillna(value=1)\n",
    "\n",
    "    likelihoods = pd.DataFrame(index = range(nrows), \n",
    "                        columns= range(len(likelihood_src.columns)))\n",
    "\n",
    "    # replace 1 with probability of that predictor\n",
    "    # time consuming\n",
    "    for i in range(nrows):\n",
    "        for j in range(ncols):\n",
    "                if dummy_dataset.iloc[i,j] == 1:\n",
    "                    likelihood_rand.iloc[i,j] = likelihood_src.iloc[j,0]\n",
    "    # replace 1 with probability of that predictor\n",
    "    # not a quick calculation\n",
    "                    likelihood_travis.iloc[i,j] = likelihood_src.iloc[j,1]\n",
    "        # aggregate likelihoods by taking the product\n",
    "        likelihoods.iloc[i,0] = np.prod(likelihood_rand.iloc[i,:])\n",
    "        likelihoods.iloc[i,1] = np.prod(likelihood_travis.iloc[i,:])\n",
    "\n",
    "    #Find the posterior probability of each class assignment\n",
    "    postprob = likelihoods.copy()\n",
    "\n",
    "    for j in range(len(likelihoods.columns)):\n",
    "        postprob.iloc[:,j] = likelihoods.iloc[:,j] * priors[j]\n",
    "    postprob = pd.DataFrame(postprob)\n",
    "    postprob.columns = [\"deter_0\", \"deter_1\"]\n",
    "    postprob['prediction'] = postprob.apply(lambda x: \\\n",
    "                1 if x['deter_1'] > x['deter_0'] else 0, axis=1)\n",
    "    \n",
    "    return postprob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>deter_0</th>\n",
       "      <th>deter_1</th>\n",
       "      <th>prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.63797e-09</td>\n",
       "      <td>1.72064e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.58723e-08</td>\n",
       "      <td>1.47993e-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.59628e-09</td>\n",
       "      <td>7.02691e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.5042e-08</td>\n",
       "      <td>3.58027e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.98078e-08</td>\n",
       "      <td>9.17374e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       deter_0      deter_1  prediction\n",
       "0  5.63797e-09  1.72064e-07           1\n",
       "1  2.58723e-08  1.47993e-06           1\n",
       "2  8.59628e-09  7.02691e-07           1\n",
       "3   1.5042e-08  3.58027e-07           1\n",
       "4  1.98078e-08  9.17374e-07           1"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posterior_test = calculate_posteriors(dnd_test_dum, proll)\n",
    "posterior_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Predicted Travis</th>\n",
       "      <th>Predicted Simulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>True Travis</th>\n",
       "      <td>0</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>True Simulation</th>\n",
       "      <td>0</td>\n",
       "      <td>667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Predicted Travis  Predicted Simulation\n",
       "True Travis                     0                    57\n",
       "True Simulation                 0                   667"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conf_matrix = pd.DataFrame(confusion_matrix(dnd_test.deter, \n",
    "                        posterior_test.prediction, labels = [0,1]), \n",
    "                        columns = [\"Predicted Travis\", \"Predicted Simulation\"])\n",
    "conf_matrix.index = conf_matrix.index.to_series().replace({0: \"True Travis\", 1: \"True Simulation\"})\n",
    "conf_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Travis Only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run previously built model only on Travis data\n",
    "travis_data = data2.copy()\n",
    "travis_data[\"deter\"] = 0\n",
    "\n",
    "# bin rolls\n",
    "travis_data[\"new_rolls\"] = pd.cut(travis_data.roll, bins=[0, 12, 20], labels=[\"0-11\", \"12-20\"])\n",
    "travis_data = travis_data.drop([\"roll\", \"season\", \"episode\", \"mod\", \"nat\", \"adv_num\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>basis_arcana</th>\n",
       "      <th>basis_athletics</th>\n",
       "      <th>basis_charisma</th>\n",
       "      <th>basis_constitution</th>\n",
       "      <th>basis_deception</th>\n",
       "      <th>basis_dexterity</th>\n",
       "      <th>basis_initiative</th>\n",
       "      <th>basis_insight</th>\n",
       "      <th>basis_intimidate</th>\n",
       "      <th>basis_intimidation</th>\n",
       "      <th>...</th>\n",
       "      <th>stat_DEX</th>\n",
       "      <th>stat_INIT</th>\n",
       "      <th>stat_INT</th>\n",
       "      <th>stat_STR</th>\n",
       "      <th>stat_WIS</th>\n",
       "      <th>stat_intimidate</th>\n",
       "      <th>stat_investigate</th>\n",
       "      <th>stat_thieves’ tools</th>\n",
       "      <th>new_rolls_0-11</th>\n",
       "      <th>new_rolls_12-20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   basis_arcana  basis_athletics  basis_charisma  basis_constitution  \\\n",
       "0             0                0               0                   0   \n",
       "1             0                0               0                   0   \n",
       "2             0                0               0                   0   \n",
       "3             0                0               0                   0   \n",
       "4             0                0               0                   0   \n",
       "\n",
       "   basis_deception  basis_dexterity  basis_initiative  basis_insight  \\\n",
       "0                0                0                 0              0   \n",
       "1                0                0                 0              0   \n",
       "2                0                1                 0              0   \n",
       "3                0                0                 0              0   \n",
       "4                0                0                 0              0   \n",
       "\n",
       "   basis_intimidate  basis_intimidation  ...  stat_DEX  stat_INIT  stat_INT  \\\n",
       "0                 0                   0  ...         0          0         0   \n",
       "1                 0                   0  ...         0          0         1   \n",
       "2                 0                   0  ...         1          0         0   \n",
       "3                 0                   0  ...         0          0         0   \n",
       "4                 0                   0  ...         0          0         0   \n",
       "\n",
       "   stat_STR  stat_WIS  stat_intimidate  stat_investigate  stat_thieves’ tools  \\\n",
       "0         0         1                0                 0                    0   \n",
       "1         0         0                0                 0                    0   \n",
       "2         0         0                0                 0                    0   \n",
       "3         0         0                0                 0                    0   \n",
       "4         0         0                0                 0                    0   \n",
       "\n",
       "   new_rolls_0-11  new_rolls_12-20  \n",
       "0               0                1  \n",
       "1               0                1  \n",
       "2               1                0  \n",
       "3               0                1  \n",
       "4               0                1  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# process the test data -- take dummies\n",
    "travis_dum = pd.get_dummies(travis_data).reset_index(drop=True)\n",
    "\n",
    "# drop column we will predict\n",
    "travis_dum = travis_dum.drop(columns=[\"deter\"], inplace=False)\n",
    "travis_dum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>deter_0</th>\n",
       "      <th>deter_1</th>\n",
       "      <th>prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.3352e-09</td>\n",
       "      <td>1.10898e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.34638e-09</td>\n",
       "      <td>2.73332e-08</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.14657e-09</td>\n",
       "      <td>5.31978e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.21436e-09</td>\n",
       "      <td>1.81997e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.96416e-10</td>\n",
       "      <td>1.02189e-10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>2.00055e-09</td>\n",
       "      <td>1.23402e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>3.21436e-09</td>\n",
       "      <td>2.09996e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>2.00055e-09</td>\n",
       "      <td>1.23402e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>1.14827e-08</td>\n",
       "      <td>9.05277e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>3.21436e-09</td>\n",
       "      <td>2.09996e-09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>170 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         deter_0      deter_1  prediction\n",
       "0     1.3352e-09  1.10898e-09           0\n",
       "1    9.34638e-09  2.73332e-08           1\n",
       "2    7.14657e-09  5.31978e-09           0\n",
       "3    3.21436e-09  1.81997e-09           0\n",
       "4    1.96416e-10  1.02189e-10           0\n",
       "..           ...          ...         ...\n",
       "165  2.00055e-09  1.23402e-09           0\n",
       "166  3.21436e-09  2.09996e-09           0\n",
       "167  2.00055e-09  1.23402e-09           0\n",
       "168  1.14827e-08  9.05277e-09           0\n",
       "169  3.21436e-09  2.09996e-09           0\n",
       "\n",
       "[170 rows x 3 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posterior_travis = calculate_posteriors(travis_dum, proll)\n",
    "posterior_travis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Predicted Travis</th>\n",
       "      <th>Predicted Simulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>True Travis</th>\n",
       "      <td>82</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>True Simulation</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Predicted Travis  Predicted Simulation\n",
       "True Travis                    82                    88\n",
       "True Simulation                 0                     0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conf_matrix = pd.DataFrame(confusion_matrix(travis_data.deter, \n",
    "                        posterior_travis.prediction, labels = [0,1]), \n",
    "                        columns = [\"Predicted Travis\", \"Predicted Simulation\"])\n",
    "conf_matrix.index = conf_matrix.index.to_series().replace({0: \"True Travis\", 1: \"True Simulation\"})\n",
    "conf_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. All Data Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adv_advantage</th>\n",
       "      <th>adv_disadvantage</th>\n",
       "      <th>stat_ATTACK</th>\n",
       "      <th>stat_CHA</th>\n",
       "      <th>stat_CON</th>\n",
       "      <th>stat_DEX</th>\n",
       "      <th>stat_INIT</th>\n",
       "      <th>stat_INT</th>\n",
       "      <th>stat_STR</th>\n",
       "      <th>stat_WIS</th>\n",
       "      <th>...</th>\n",
       "      <th>basis_sleight of hand</th>\n",
       "      <th>basis_stealth</th>\n",
       "      <th>basis_strength</th>\n",
       "      <th>basis_thieves’ tools</th>\n",
       "      <th>basis_wisdom</th>\n",
       "      <th>type_attack</th>\n",
       "      <th>type_check</th>\n",
       "      <th>type_save</th>\n",
       "      <th>new_rolls_0-11</th>\n",
       "      <th>new_rolls_12-20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   adv_advantage  adv_disadvantage  stat_ATTACK  stat_CHA  stat_CON  stat_DEX  \\\n",
       "0              1                 0            0         0         1         0   \n",
       "1              0                 0            0         0         0         1   \n",
       "2              1                 0            1         0         0         0   \n",
       "3              1                 0            0         0         0         0   \n",
       "4              1                 0            0         0         0         1   \n",
       "\n",
       "   stat_INIT  stat_INT  stat_STR  stat_WIS  ...  basis_sleight of hand  \\\n",
       "0          0         0         0         0  ...                      0   \n",
       "1          0         0         0         0  ...                      0   \n",
       "2          0         0         0         0  ...                      0   \n",
       "3          0         0         0         1  ...                      0   \n",
       "4          0         0         0         0  ...                      0   \n",
       "\n",
       "   basis_stealth  basis_strength  basis_thieves’ tools  basis_wisdom  \\\n",
       "0              0               0                     0             0   \n",
       "1              0               0                     0             0   \n",
       "2              0               0                     0             0   \n",
       "3              0               0                     0             0   \n",
       "4              0               1                     0             0   \n",
       "\n",
       "   type_attack  type_check  type_save  new_rolls_0-11  new_rolls_12-20  \n",
       "0            0           0          1               0                1  \n",
       "1            0           0          1               0                1  \n",
       "2            0           1          0               1                0  \n",
       "3            1           0          0               0                1  \n",
       "4            0           1          0               0                1  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# run model on all data together\n",
    "rodeo = rodeo.copy()\n",
    "\n",
    "# process the test data -- take dummies\n",
    "all_dum = pd.get_dummies(rodeo).reset_index(drop=True)\n",
    "\n",
    "# drop column we will predict\n",
    "all_dum = all_dum.drop(columns=[\"deter\"], inplace=False)\n",
    "all_dum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>deter_0</th>\n",
       "      <th>deter_1</th>\n",
       "      <th>prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.46777e-09</td>\n",
       "      <td>1.24989e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.14169e-07</td>\n",
       "      <td>3.85489e-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.28141e-09</td>\n",
       "      <td>3.50652e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.39779e-08</td>\n",
       "      <td>1.2804e-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.58723e-08</td>\n",
       "      <td>1.47993e-06</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>2165</th>\n",
       "      <td>8.38977e-09</td>\n",
       "      <td>3.10204e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2166</th>\n",
       "      <td>9.86981e-09</td>\n",
       "      <td>6.50224e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2167</th>\n",
       "      <td>3.85731e-08</td>\n",
       "      <td>2.27136e-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2168</th>\n",
       "      <td>2.37965e-08</td>\n",
       "      <td>1.1746e-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2169</th>\n",
       "      <td>8.59628e-09</td>\n",
       "      <td>7.02691e-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2170 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          deter_0      deter_1  prediction\n",
       "0     3.46777e-09  1.24989e-07           1\n",
       "1     5.14169e-07  3.85489e-06           1\n",
       "2     7.28141e-09  3.50652e-07           1\n",
       "3     2.39779e-08   1.2804e-06           1\n",
       "4     2.58723e-08  1.47993e-06           1\n",
       "...           ...          ...         ...\n",
       "2165  8.38977e-09  3.10204e-07           1\n",
       "2166  9.86981e-09  6.50224e-07           1\n",
       "2167  3.85731e-08  2.27136e-06           1\n",
       "2168  2.37965e-08   1.1746e-06           1\n",
       "2169  8.59628e-09  7.02691e-07           1\n",
       "\n",
       "[2170 rows x 3 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posterior_all = calculate_posteriors(all_dum, proll)\n",
    "posterior_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Predicted Travis</th>\n",
       "      <th>Predicted Simulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>True Travis</th>\n",
       "      <td>2</td>\n",
       "      <td>168</td>\n",
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       "    <tr>\n",
       "      <th>True Simulation</th>\n",
       "      <td>0</td>\n",
       "      <td>2000</td>\n",
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      "text/plain": [
       "                 Predicted Travis  Predicted Simulation\n",
       "True Travis                     2                   168\n",
       "True Simulation                 0                  2000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conf_matrix = pd.DataFrame(confusion_matrix(rodeo.deter, \n",
    "                                    posterior_all.prediction, \n",
    "                                    labels = [0,1]), \n",
    "                                columns = [\"Predicted Travis\", \"Predicted Simulation\"])\n",
    "conf_matrix.index = conf_matrix.index.to_series().replace({0: \"True Travis\", 1: \"True Simulation\"})\n",
    "conf_matrix"
   ]
  }
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