Predict Spectral KNN Clusters - XGB UMAP with Shapley Values.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1bc794da",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "\n",
    "import xgboost as xgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ceb513d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "np.set_printoptions(precision=3, suppress = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "84aac384",
   "metadata": {},
   "outputs": [],
   "source": [
    "imp_unscaled = pd.read_csv(\"Data/imputed_unscaled.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "585b0419",
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   "outputs": [
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       "   Unnamed: 0  veteran   age  age_group 2  sex  housing 2  education 2  \\\n",
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       "\n",
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       "   avg_elix_op  avg_elix_ed  HSCS_ed   HSCS_op  extreme_days  ed_visit_group  \\\n",
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       "\n",
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    "imp_unscaled.shape"
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       "   veteran   age  age_group 2  sex  housing 2  education 2  si_race 2  \\\n",
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       "\n",
       "   si_ethnicity 2  language  insured  ...  avg_ip_interval  mf_provider 2  \\\n",
       "0             0.0       0.0      1.0  ...       248.132289            0.0   \n",
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       "\n",
       "   mf_mhprovider 2  avg_elix_op  avg_elix_ed  HSCS_ed   HSCS_op  extreme_days  \\\n",
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       "4             10.0     2.947368     4.222222      8.0  2.363636           2.0   \n",
       "\n",
       "   ed_visit_group  op_visit_group  \n",
       "0             1.0             5.0  \n",
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       "\n",
       "[5 rows x 83 columns]"
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     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PATIENT_IDS = imp_unscaled[\"patient_id\"]\n",
    "imp_unscaled.drop(columns=[\"Unnamed: 0\", \"patient_id\", \"KM_UMAP\"], axis=1, inplace=True, errors=\"ignore\")\n",
    "imp_unscaled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "11e5f8c5",
   "metadata": {},
   "outputs": [
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       "2         4\n",
       "3         5\n",
       "4         3"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spectral_clusters = pd.read_csv(\"Data/Spectral_Clusters.csv\")\n",
    "spectral_clusters.drop(columns=[\"Unnamed: 0\", \"orig_RBF\", \"ISO_RBF\", \"orig_KNN\", \"UMAP_RBF\", \"ISO_KNN\"], axis=1, inplace=True)\n",
    "spectral_clusters.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a321a6ac",
   "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>SUKNN_0</th>\n",
       "      <th>SUKNN_1</th>\n",
       "      <th>SUKNN_2</th>\n",
       "      <th>SUKNN_3</th>\n",
       "      <th>SUKNN_4</th>\n",
       "      <th>SUKNN_5</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",
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       "      <td>1</td>\n",
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       "    <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",
       "    </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>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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SUKNN_0  SUKNN_1  SUKNN_2  SUKNN_3  SUKNN_4  SUKNN_5\n",
       "0        0        0        0        0        0        1\n",
       "1        0        0        0        0        0        1\n",
       "2        0        0        0        0        1        0\n",
       "3        0        0        0        0        0        1\n",
       "4        0        0        0        1        0        0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umap_cluster_labels = pd.get_dummies(spectral_clusters[\"UMAP_KNN\"])\n",
    "umap_cluster_labels.columns = [\"SUKNN_0\", \"SUKNN_1\", \"SUKNN_2\", \"SUKNN_3\", \"SUKNN_4\", \"SUKNN_5\"]\n",
    "umap_cluster_labels.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "80423895",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Proportion of records with 5: 0.12 (282 / 2265)\n",
      "Proportion of records with 4: 0.099 (225 / 2265)\n",
      "Proportion of records with 3: 0.14 (328 / 2265)\n",
      "Proportion of records with 0: 0.45 (1014 / 2265)\n",
      "Proportion of records with 1: 0.11 (258 / 2265)\n",
      "Proportion of records with 2: 0.07 (158 / 2265)\n"
     ]
    }
   ],
   "source": [
    "def test_stratified(df, col):\n",
    "    classes=list(df[col].unique())\n",
    "    \n",
    "    for c in classes:\n",
    "        print(f'Proportion of records with {c}: {len(df[df[col]==c])*1./len(df):0.2} ({len(df[df[col]==c])} / {len(df)})')\n",
    "        \n",
    "        \n",
    "test_stratified(spectral_clusters, \"UMAP_KNN\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f81c9462",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = imp_unscaled.copy()\n",
    "X = StandardScaler().fit(X).transform(X)\n",
    "\n",
    "y = spectral_clusters[\"UMAP_KNN\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d0482a49",
   "metadata": {},
   "outputs": [],
   "source": [
    "from xgboost import XGBClassifier\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f892754c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 192 candidates, totalling 960 fits\n",
      "[10:00:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.3.0/src/learner.cc:541: \n",
      "Parameters: { scale_pos_weight } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
      "[10:00:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.3.0/src/learner.cc:1061: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'multi:softprob' was changed from 'merror' to 'mlogloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "Best: [0.907 0.915 0.916 0.917 0.917 0.919 0.919 0.92  0.913 0.918 0.919 0.919\n",
      " 0.92  0.918 0.919 0.919 0.914 0.918 0.918 0.918 0.918 0.917 0.918 0.919\n",
      " 0.915 0.915 0.916 0.916 0.916 0.915 0.914 0.915 0.917 0.915 0.917 0.917\n",
      " 0.917 0.917 0.917 0.918 0.917 0.916 0.914 0.914 0.914 0.914 0.915 0.915\n",
      " 0.914 0.916 0.916 0.917 0.917 0.917 0.915 0.917 0.914 0.915 0.915 0.916\n",
      " 0.916 0.916 0.917 0.916 0.86  0.866 0.869 0.874 0.879 0.884 0.89  0.893\n",
      " 0.874 0.88  0.887 0.891 0.894 0.898 0.901 0.905 0.886 0.889 0.892 0.898\n",
      " 0.901 0.905 0.91  0.911 0.893 0.895 0.898 0.901 0.905 0.909 0.912 0.914\n",
      " 0.895 0.896 0.899 0.902 0.907 0.909 0.912 0.913 0.896 0.896 0.9   0.903\n",
      " 0.907 0.909 0.911 0.912 0.899 0.898 0.901 0.903 0.908 0.908 0.91  0.912\n",
      " 0.899 0.898 0.901 0.904 0.907 0.909 0.91  0.911 0.896 0.906 0.909 0.913\n",
      " 0.917 0.918 0.918 0.92  0.907 0.91  0.914 0.919 0.92  0.922 0.923 0.921\n",
      " 0.914 0.916 0.917 0.919 0.919 0.919 0.919 0.919 0.914 0.916 0.916 0.917\n",
      " 0.917 0.918 0.917 0.918 0.916 0.916 0.918 0.919 0.919 0.919 0.919 0.919\n",
      " 0.913 0.916 0.914 0.917 0.916 0.915 0.916 0.916 0.913 0.915 0.916 0.917\n",
      " 0.917 0.916 0.916 0.917 0.912 0.915 0.914 0.915 0.917 0.916 0.916 0.916], using {'learning_rate': 0.05, 'max_depth': 3, 'n_estimators': 400}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "\n",
    "params = {\n",
    "    'learning_rate'     : [0.1, 0.01, 0.05],\n",
    "    'n_estimators'      : range(100,500,50),\n",
    "    'max_depth'         : range (2, 10, 1)\n",
    "}\n",
    "\n",
    "\n",
    "cv = StratifiedShuffleSplit(n_splits=5, test_size=0.3, random_state=121)\n",
    "xgb1 = xgb1 = XGBClassifier(\n",
    "             min_child_weight=1,\n",
    "             gamma=0,\n",
    "             subsample=0.8,\n",
    "             colsample_bytree=0.8,\n",
    "             objective= 'multi:softmax',\n",
    "             nthread=4,\n",
    "             scale_pos_weight=1,\n",
    "             seed=121)\n",
    "grid = GridSearchCV(estimator=xgb1, param_grid=params, scoring='f1_micro', n_jobs=-1, verbose=5, cv = cv)\n",
    "grid_results = grid.fit(X, y)\n",
    "\n",
    "# Summarize the results in a readable format\n",
    "print(\"Best: {0}, using {1}\".format(grid_results.cv_results_['mean_test_score'], grid_results.best_params_))\n",
    "#results_df = pd.DataFrame(grid_results.cv_results_)\n",
    "#results_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8006d366",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = imp_unscaled.copy()\n",
    "y = spectral_clusters[\"UMAP_KNN\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7c5ee098",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9977924944812362\n",
      "0.9249448123620307\n"
     ]
    }
   ],
   "source": [
    "clf = XGBClassifier(\n",
    "             learning_rate=0.05,\n",
    "             max_depth=2,\n",
    "             n_estimators=400,\n",
    "             min_child_weight=1,\n",
    "             gamma=0,\n",
    "             subsample=0.8,\n",
    "             colsample_bytree=0.8,\n",
    "             objective= 'multi:softmax',\n",
    "             eval_metric=\"mlogloss\",\n",
    "             nthread=4,\n",
    "             seed=121)\n",
    "\n",
    "cv = StratifiedKFold(n_splits=5, random_state=121, shuffle=True)\n",
    "results = pd.DataFrame(columns=['training_score', 'test_score'])\n",
    "train_scores = []\n",
    "test_scores = []\n",
    "    \n",
    "for (train, test), i in zip(cv.split(X, y), range(5)):\n",
    "    x_train = X.iloc[train]\n",
    "    x_train = StandardScaler().fit(x_train).transform(x_train)\n",
    "    y_train = y.iloc[train]\n",
    " \n",
    "    clf.fit(x_train, y_train)\n",
    "    train_scores.append(clf.score(x_train, y_train))\n",
    "    \n",
    "    x_test = X.iloc[test]\n",
    "    x_test = StandardScaler().fit(x_test).transform(x_test)\n",
    "    y_test = y.iloc[test]\n",
    "    test_scores.append(clf.score(x_test, y_test))\n",
    "\n",
    "print(np.mean(train_scores))\n",
    "print(np.mean(test_scores))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ec3ab06",
   "metadata": {},
   "source": [
    "Permutation importances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fd575379",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1584x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.inspection import permutation_importance\n",
    "\n",
    "result = permutation_importance(\n",
    "    clf, x_test, y_test, n_repeats=10, random_state=121, n_jobs=2\n",
    ")\n",
    "\n",
    "xgb_importances = pd.Series(result.importances_mean, index=X.columns)\n",
    "xgb_importances.sort_values(ascending=False, inplace=True)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(22,20))\n",
    "xgb_importances.plot.bar(yerr=result.importances_std, ax=ax)\n",
    "ax.set_title(\"Feature importances using permutation on full model\")\n",
    "ax.set_ylabel(\"Mean accuracy decrease\")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94d94b23",
   "metadata": {},
   "source": [
    "Confusion Matrix - Multiclass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1bd4e757",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.95  0.    0.    0.025 0.015 0.01 ]\n",
      " [0.    0.942 0.    0.    0.    0.058]\n",
      " [0.094 0.    0.906 0.    0.    0.   ]\n",
      " [0.    0.    0.    0.939 0.    0.061]\n",
      " [0.    0.    0.    0.022 0.956 0.022]\n",
      " [0.054 0.018 0.    0.071 0.054 0.804]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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Cc7QJuthGRLhz3AhuefIePl128Q/iG0P/j5c/eY9rH+7CuNmTGPfQEyWaO7eSeEaBu3j8mJqIDBWRGBGJSUlxOKKIQ8bkfRa0O/9S5Ldsk2vQzonzZlC1UhU2f/g9I3o9wM6D+8iwZNCtRQdOnDrJ9ri9bsuXn9JeR4W5HPPk/h3Jrw9HOZa+/Slr3p/L1+OnMHvR1/y8JxaAT5bMY8Lg0ez5dDmvDxnNE++PL9Hc9lku0y01ZxljZhhjoo0x0SEhwUVeTmRwGPEpObeckoioVr0kIuYrITWJGsE5/6qHkpjrL+7p82cZNvlFWj/el0HvPkvwFVdyOCmeGxs3o2erjuyf8yP/fm4SHZq2Zs7od9yW9WLG0l1HmieviKBQEnL0kZiaTFg1+13FiOBQEnLsBSSmXWwTHmTNE1K1Gj1uvIXY36yHrL/8cSG92lgPf/S9qXP25+5Rco/IcwePF7WSEt2wCXGJhzmcdIwL6ReYt3YxPXId4ypJMb/tpl5kbaJCaxAYEEj/dj1Y/MtquzZXVKxMYEAgAAO79GfDnhhOnz/LuM8mUe+h9jR65FYefOtp1uzazCMT/89tWbOU9jrSPHk1a3ANhxKPciQpgQvp6cxft5yurdrbtenWqj1zVy/CGMPW/buoUqESYdVCOPvP+ezjZmf/Oc9P2zdxdVQ9AMKqhbBxt/X5Jut2bqFuRK0SzZ2bN+9++sx1agH+Abz36Dh6jRmEJdPCQ5370bh2/cJnLCJLpoWnPn6Vha/Nwt/Pn89Wfsu+o3EM7jYAgFlL59KoZl1mPf0WlsxM9h+LY/j7YwpZqnuV9jrSPPn38fbw5+k3bgSWzEzu69SHq6Pq8cmSeQAM7N6fTtE3szJmA82H9KJ82XJ8NMq6K5nyVxoPvP40ABmZGfRr343bmrcF4P3Hx/HCjLfJsFgoW6YM7z3+Uonmzs2b7yiQ/PbfS2TBIl9iffhoMJAMvGyMme1onubRzczGX/QReY542yPyVOG86RF5HdvcxvbYHcWqSOVrXWFqP9PWqbb7Ry2NdfA0Kbdw25aaMeYedy1bKeVZ3ryl5jO7n0qp0uPFNU2LmlLKVTpIpFLKh2Rdp+attKgppVzmxTVNi5pSynW6paaU8i1a1JRSPsPLB4nUoqaUcok+eEUp5XO0qCmlfIoWNaWUT/HimqZFTSnlIg8OAOkMrypqGZkWTl3409MxsnnjiBjlB1zr6Qh2zs8tlefqXNLKB1TwdIRsflL825sE9DYppZRv0S01pZTv8OCots7QoqaUcpluqSmlfIbg3ScKvPdon1LKa5XUI/JEpKuIHBCROBF5voA2HURkh4jsFZG1hS1Tt9SUUq4RSuTeTxHxB6YAnYB4YKuI/GCM+TVHm6rAVKCrMeaoiBT6zELdUlNKua5knpHXEogzxhwyxlwA5gJ9crW5F5hvjDkKYIw5QSG0qCmlXObC7mewiMTkeA3NsZhI4FiO9/G2z3JqAFwpImtEJFZEHiwsm+5+KqVcIoALe5+pDh6Rl99Scj+zMwBoDtwKlAc2ichmY8xvBXWoRU0p5aISO/sZD9TM8b4GkJhPm1RjzFngrIisA64DCixquvuplHKJCPj7+Tn1KsRWoL6I1BGRMsAA4IdcbRYAN4tIgIhUAFoB+xwtVLfUlFIuK4mtIWNMhoiMBJYD/sAcY8xeERlumz7NGLNPRJYBu4BMYJYxxuENx1rUlFIu8yuhi2+NMUuAJbk+m5br/TvAO05nK2iCiHwoIh8U9HI1fFGtjt1E2xH9aT30Tj785rM8040xjJnxLq2H3sktj9/HroP7s6fN/GEu7UfeQ7vHBjBjwZd55p363X8J692KtL//ckv2FTHraDqoC9cMvI13vprulj5y63RdW3ZOWsieyUsY3XtQnulVK1bhq6ffZ8tb81n/+pc0rlEve9q0Ya9xZPpaYt75rlSygmfWkeYpnqzhvEvi4lt3cLQVGQPEOng5JCI1ReQnEdlnuxL4SVfDWSwWXpj+Dl+8PJl1U+by3boVHDh6yK7Nj7E/cyjxGJumf8PEx57nuY/fBmDfkYP8d8UClr77Cas/+C8rYzZyKPFo9nwJKcms27GFyJAwV2M5nX3UlPEseH0m22csYd6aRew7EueWvrL4iR+THxlLnzdHcMMzvenftjuNIq+ya/Ns3yHsPLKfls/dwaCpLzLx4YsXcf9n7ff0+ddwt2bMyRPrSPOUBMFPnHt5QoFFzRjzWc4X8E2u94XJAJ4xxlwNtAYeE5HGroTb/vuv1AmvQVRYJGUCA+l7cyeW/7LOrs3yX9Zx1y3dEBGaN2rC32dPk3wyld+PHaZ5w2upULYcAf4B3HjNDSzZdPEOi3Gz3+Olh0e67a/J1gO7qBseRZ3wWpQJLEP/9j1YtGmVW/rK0qJeEw4mHeXwiXjSLRnM+3kpPaM72rVpFFmXNXs2A/Bb4h9EhURS/YogADbuj+Xk2VNuzZiTJ9aR5ikBculuqQEgIjeKyK/YzjiIyHUiMrWw+Ywxx40x22xfn7bNn/vCOoeOp50gIjg0+314cHWOp6XkapNCREiONkHWNo2irmLz3u2c/PsU5/73Dz/G/kxiajJgLYThQSFcU6eBK3FckpiWTI0cW4GRwWEkpCW7rT+AiGrViU9Lyn6fcDKZyGr2d5XsPnqAPi1vAyC67rXUCg4nsloonuCJdaR5ik+AABGnXp7gzImCyUAXbKdajTE7RaSdK52ISG3gBuCXfKYNBYYC1KhpX/NM7svwyDvkiclzrZ71lHODmnUYeceD3D3ucSqWK881deoT4O/Puf/9w+R5n/LVePceFjT5hHf3Xy7J51rG3DkmLpjFxIeeZ/Ob37D32O/sPLyfDIvFrbkK4ol15IjmcZ635MiPU2c/jTHHcn0TTv8rEJFKwLfAKGPM3/ksewYwA+C6ZtfZ/RQjgqtnb10BHE89QVi1YLv5I4Kqk5iSo03aCcKqhQBwb+fe3Nu5NwBv/Hsq4cHVOXI8nqPJiXR88v7sZXYe9SBL3/2E6lcGOfttFSoyOIz4lBxbTalJRFQr9F7cYkk4mUyNoBx/2auFkvin/Zbt6fNnGTbtpez3+z9czuGUeLfmKogn1pHmKT7rHQXeW9ScudzkmIi0AYyIlBGR0RRy8VsWEQnEWtA+N8bMdzXc9fWv5lDiMY4kJXIhPZ3v16+kcyv7jcTOLW/m65+WYowhdv9uKleoRKit8KX8dRKA+JQklmxaw+3tOnN17Xrs/c8yYmZ9T8ys7wkPrs6Kyf8u0YIGEN2wCXGJhzmcdIwL6ReYt3YxPVrfWqJ95BZzcA/1wmoRFRJJoH8A/dt0Y3HsT3ZtrqhQmUB/69+ygR3vZMO+WE6fP+vWXAXxxDrSPCVDnHx5gjNbasOB97EeD0vAeqHcY4XNJNZNu9nAPmPMpCKF8w/gjWGjueeVJ7BkZnLPbb1oVOsqPltqrY8PdbuD26Lb8mPsz7Qedifly5Zj8hMXt0IGv/k8J0+fItA/gH8N/z+qVqpSlBhFEuAfwHuPjqPXmEFYMi081LkfjWvXd2uflkwLT33yBgtfnI6/nz+f/fQd++IPMvi2uwCYteprGkVexaxH38CSaWF/wiGGTx+XPf9nj7/NzY1bEFy5KnFTVvHaN1P57CeX/xY5zRPrSPOUBM+d2XSG5LffXiILFrkJWA/sxnolMMCLtovt8nVds+vMio0FTi51V5S50tMR8tCnSaniaNvqJmJjthWrIgU1qG66fdjfqbafd50a6+CGdrcodEtNRK7CuqXWGusd9JuAp4wxhxzNZ4zZgOe2QJVSbuTNW2rOHFP7AvgaCAcigHlA3svzlVKXBWePp3mq7DlT1MQY8x9jTIbt9V/yjnmklLqMePMdBQXufopINduXP9keiDAXazG7G1hcCtmUUl7Ju08UODqmFou1iGWlH5ZjmgFec1copZT3ErlEL741xtQpzSBKqUuH/6VY1HISkWuBxkC5rM+MMf92VyillPfy9jsKnLmk42WgA9aitgToBmwAtKgpdZny5qLmzNnPflif5JJkjBmI9aEHZd2aSinlxZwbdshTx92c2f08b4zJFJEMEakCnACuKmwmpZRvErz7iU3OFLUY26PfZ2I9I3oG2OLOUEopL3apnv3MYox51PblNNtTXaoYY3a5N5ZSylsJEFD44+88xtHFt80cTcsa1VYpdfm5VLfU3nUwzQAdHUwvkgA/f68cGcObeNuoGOV7NfJ0BDvnF+4vvFEpO5fhmfHq8mMxmYU3KpTg58VjVTi6+PaW0gyilLp0XKpbakoplYeId1+npkVNKeUyP7kETxQopVR+xMtH6XDmuZ8iIveLyDjb+1oi0tL90ZRS3sp6qqDwlyc40+tU4EbgHtv708AUtyVSSnm9S3KQyBxaGWOaich2AGPMnyJSxs25lFJe7FI/+5kuIv7YhvAWkRAuPh1KKXWZEdt/3sqZovYB8B1QXUQmYB21Y6xbUymlvJeA/6V4m1QWY8znIhKLdfghAfoaY5x6QrtSyvdYR+m4hIuaiNQCzgELc35mjDnqzmBKKW/lubHSnOHM7udiLj6ApRxQBzgAXOPGXEopL3ZJFzVjTJOc722jdwwroLlS6jLgzTe0u7xjbBtyqIUbshTbiph1NB3UhWsG3sY7X033dByvywOln6lTs5vY+fFS9kxfzuh+Q/JMr1qxCl+9+CFbPljA+ne/pnGt+nbT/fz82DR5Pt+Om+b2rFA66+fH2I20HNaX6CG9mTxvTp7pxhien/4W0UN6c/PIu9gZd/EQ9qkzp3n4jdG0Gn47rYffwdZ9OwFYsGElbR69k+Bezdj++1635M4i4NXDeTtzR8HTOV6jReQLIMWJ+cqJyBYR2Skie0VkfIkkLoDFYmHUlPEseH0m22csYd6aRew7EufOLi+pPJ7I5Ofnx+Th4+jzyhBueKwn/dv1oFHNunZtnr1rGDsP7aflE30Y9N5zTBz6ot30kb0e5ED8IbdlzKk01o/FYuHZj9/k6/Ef8fPUb5m/dhn7jx60a7MqZgOHEo+ydcYCJo0cy+ipb2RPe2HG29zavA2/TPuOdR9+RYOa1pH1G0XV5bMX36XNNQUOg1hyRPAXP6dehS9KuorIARGJsz00vaB2LUTEIiL9ClumM1tqlXO8ymI9xtbHifn+B3Q0xlwHXA90FZHWTsxXJFsP7KJueBR1wmtRJrAM/dv3YNGmVe7q7pLL44lMLeo35eDxoxxOjic9I51565bQs9Wtdm0a1azLml2bAPgt/g+iqkdSvWoQAJFBoXRt0Z5PVsxzW8acSmP9bPttD3XCa1I7rAZlAgO5vV0Xlm5eY9dm6S9rubtjT0SEFo2acursaZJOpvD3uTNs2ruN+zvfDkCZwECuqFQZgIY1r6J+jdolmrUg1kfk+Tn1crgc6/WvU7A+oa4xcI+INC6g3VvAcmfyOezVtrBKxpjxttcEY8znxph/CluwsTpjextoexlnQhVFYloyNULCst9HBoeRkJbsru4uuTxQ+pkigkKJTz2e/T4hLYnIoFC7Nrv/OECfGzsDEF2/CbWqRxAZZM34zpAXGfPJRDIz3fZrY6c01s/xtBNEhlxcBxHBoRxPS8nbJvhijoigUI6nneBIUgJBVa5k5OSX6fDEAJ78YDxn/zlfovmcVUK7ny2BOGPMIWPMBWAu+W8wPQ58i/WhT4UqsKiJSIAxxgIUeXtWRPxFZIctzEpjzC/5tBkqIjEiEpOSklrUrjAm7y++J8/QeFseKP1M+S06d4aJ38ygaqUqbH7/O0b0up+dh/aRYcmgW4sOnDiVxvaD7j0+5CgblPz6ya885+6ioBwZlgx2HdzPwO79WfPBXCqULc/7+RyTKw3i5H9AcNa/b9traI7FRALHcryPt312sR+RSOB2wOmDqo7Ofm7BWtB2iMgPwDwge1xiY8z8whZuK4rX255G9Z2IXGuM2ZOrzQxgBkDz6GZF/pMcGRxGfEpS9vuE1CQiqlUv6uKKzdvyQOlnSkhNpkZw+MX+g8JIPGn/x/b0+bMMe//icbT9s37kcHI8/dv1oGfLjnRt3p6yZcpQpUIl5jz9No9MetZteUtj/UQEVSch5eLWX2JqMmHVQuzbBIeSkHoxR2KatY2IEBFcneiG1gsSere9jfe/+aRE8znHpZvVU40x0QUuKK/cNWAy8JwxxuLsHxhnjqlVA9KwPpOgJ9DL9n+nGWP+AtYAXV2ZzxXRDZsQl3iYw0nHuJB+gXlrF9Oj9a2Fz3iZ5PFEppjfd1MvIoqo0EgCAwLp3647i7estmtzRcXKBAYEAjCwc3827N3K6fNnGffvSdQb2IFGg2/lwbefYc2uX9xa0KB01s8NDa7hUOJRjiQlcCE9ne/WLadbqw52bbq2as9XqxdhjGHr/l1UqVCJsGohhF4ZTGRwGL/HHwZg3c4tNKxV+o/gFSipEwXxQM0c72sAibnaRANzReQw1ls0p4pIX0cLdbSlVl1Engb2cPHi2yyFblHZbnxPN8b8JSLlgduwHuxziwD/AN57dBy9xgzCkmnhoc79aFy7fuEzXiZ5PJHJkmnhqWmvsXD8bPz9/Phs1bfsOxrH4K53AzBr2Vc0qlGXWU+/iSUzk/1H4xj+geduKy6N9RPgH8Bbw5+j/7hHsWRmcm+nPjSKqssnS6wnQwZ270+n6JtYGbOB6CG9KV+2HB+OeiV7/jeHP8ewiS+SnpFBVFgkH42yXlSw6OfVPD/9LdJO/ck945/g2joN+ea1qSWaPZuAlMzIt1uB+iJSB0gABgD35mxgjKmT3a3Ip8AiY8z3DuPlt/9uW8Bx4GMK2EQ0xrzqcMEiTYHPAH+sW4RfFzZP8+hmZuMvGxw1UV5GnyZVOG96mlTHNp3YEbujWAcKo66NMmO+fs6ptsOueSzWwe4nItId6y6mPzDHGDNBRIYDGGOm5Wr7Kdai9o2jPh1tqR0vrAg5Ynvg8Q1FnV8p5Z2sl3SUzAkUY8wSYEmuz/I9KWCMediZZToqat57H4RSyqM8fSbfEUdFzbNHtZVSXsub7/109DDjk6UZRCl1aRAEPz9/T8cokD4iTynlsktyS00ppfIjcukeU1NKqXxd6g9eUUqpHC794byVUsqOHlNTSvkMQfATPfuplPIhuvuplPIpeqJAKeVTdEtN+awzC/YU3qgUle/awNMR8jiz5FdPR8hWEgf4pYSW4y5a1JRSrhE9UaCU8jG6+6mU8hmCnihQSvkUlx68Uuq0qCmlXKZbakopn6LH1JRSPkNvk1JK+Ry9Tk0p5Tt0kEillC/RSzqUUj5Ht9SUUj5E8NcTBUopX+Htu59+ng5QklbErKPpoC5cM/A23vlquqfjeF0eKJ1MK2PWc8OQ7jQd1IV3v56ZZ7oxhtHTJtB0UBdaPdqXHXHWUSziU47T7fmHaTasJ9HDezHl+/9kzzNm9jvcMLQHrR7ty4DXHuevM38XKVun5jezc9Yy9sxZyei7huaZXrVSFb56aQpbPv6B9e9/Q+Oo+tnTrqhYmS/GfMCOmcvYPmMpra6+vkgZvHn9OEtEnHp5gtuLmoj4i8h2EVnkzn4sFgujpoxnwesz2T5jCfPWLGLfkTh3dnlJ5SmtTBaLhaenvs78V6cTM20h89YuYd9R+z5WxKzjYMIRds5axodPjGfUR+MBCPAP4F+Dn2Xb9EX8NGkuMxd9kT1vxxvasPXjBfwy9XvqR9bOtxgUxs/Pj8mPvUyfsUO4YWh3+nfoSaNade3aPDtgODsP7aPliN4MeudZJg4fmz1t4vCxrIhdz/VDutLy0d7sP3rQ5QzevH6cJ07/5wmlsaX2JLDP3Z1sPbCLuuFR1AmvRZnAMvRv34NFm1a5u9tLJk9pZYr5bTdXRdSiTnhNygSWoV+7bizetNquzaLNq7nn1j6ICC0bXceps6dJOplCWLUQrq/XGIDKFSrSsNZVHE89AcCtzdoS4G89WtKi0XUkpCa5nK1Fw6YcPH6Ew0nHSM9IZ97axfS88Ta7No1q1WPNjk0A/BZ/iKjQSKpXDaJyhYrc1CSaT5fNAyA9I51TZ0+7nMGb148rLtstNRGpAfQAZrmzH4DEtGRqhIRlv48MDiMhLdnd3V4yeaB0MiWmJVMj2L6PxLQTdm2Op56wyxERHEpiqn2OI8kJ7Dy4j+hGTfP08Z8V8+kcfbPL2SKCQolPufiPPSE1icigULs2uw/tp0/bzgBEN2hKrdAIIoPDqBNWi9RTfzLjmTfZ9NH3TB01gQply7ucwZvXj7Osg0Q6958nuLvXycCzQGZBDURkqIjEiEhMSkpqkTsyxuS37CIvr7i8LQ+UTqb8+8jVBsc5zpw/y30TnuStoS9QpUIlu3Zvz52Gv78/d9/Sy+Vs+X2vufNO/Ho6VStVYfOUBYzo8wA7D+4jw2IhwN+f6+s1ZuaiL7hxZF/O/XOO0XfnPSZXGG9eP04TwU/8nHp5gtvOfopIT+CEMSZWRDoU1M4YMwOYAdA8ulnen6aTIoPD8vwVjqhWvaiLKzZvywOlkykyOIz4VPs+wnP1ERFsv8WUmJpMeJC1TXpGOvdNGMXdHXrSp20nu/k+X/U9y7asZdEbc4pUjBNSk/JsqSaetN9KOn3uLMMmvZD9fv9nqzmcfIwKZcuTkJrE1gO7APhu/XKeKUJR8+b14wpP/4F2xJ2ltC3QW0QOA3OBjiLyX3d1Ft2wCXGJhzmcdIwL6ReYt3YxPVrf6q7uLrk8pZWpeYNrOZh4hMNJ8VxIv8A365bSvfUtdm16tOrIlz8uwBjDlv07qVKxMmHVQjDG8Ojkl2hY8yoev+Nhu3lWxqxn0rxZfPXyFCqUc323DyDmwG7qRdQmKrQGgQGB9G/fg8Wbf7Rrc0XFygQGBAIwsOtdbNgdw+lzZ0n+M5X4lCTq16gDQIcbbmT/UddPsnjz+nGFN58ocNuWmjHmBeAFANuW2mhjzP3u6i/AP4D3Hh1HrzGDsGRaeKhzPxrXrl/4jJdJntLKFOAfwLsjxtB37BAsmZk80Pl2GkfVZ9biuQAM7jGALi3asXzrOpoO6kr5suWY9tQEADb9uo0vV//ANbUbcOPI2wF45aFRdGnRnmc+fp3/pafTe8wgAFo0vI4PHn/FpWyWTAtPTX2VhRNm4+/nz2crvmHfkTgGdx8AwKwlc2lUqy6zRr+NJTOT/UfjGP7ei9nzPz31NT55diJlAgM5fDyeoZOe96n14yxvv05N8tvHL/FOLha1no7aNY9uZjb+ssHteVTJsWRmeDqCnUrdG3s6Qh7e9DSpm1u3Z1vs9mJVpMbXNzL/XjXHqbYtQtrGGmOii9Ofq0rljgJjzBpgTWn0pZRyN8/tWjrDp+4oUEqVjpI6+ykiXUXkgIjEiUie/XkRuU9EdtleP4vIdYUtU+/9VEq5rCS21ETEH5gCdALiga0i8oMxJuf++h9Ae2PMnyLSDeuVEq0cLVeLmlLKJUKJXdLREogzxhzCusy5QB8gu6gZY37O0X4zUKOwherup1LKRS7d+xmcdXG97ZXz4r5I4FiO9/G2zwoyCFhaWDrdUlNKucyF3c9UB2c/81tIvpdjiMgtWIvaTYV1qEVNKeUaoaRugYoHauZ4XwNIzNOdSFOs9493M8akFbZQ3f1USrkk65haCYzSsRWoLyJ1RKQMMAD4wa4vkVrAfOABY8xvzuTTLTWllItK5jo1Y0yGiIwElgP+wBxjzF4RGW6bPg0YBwQBU21FMqOwi3m1qCmlXFZSF98aY5YAS3J9Ni3H14OBwa4sU4uaUspl3jxKhxY1pZTLvPk2KS1qSimXCOKxASCdoUVNKVUEuqXmlEyTyT8Z5zwdI1ugf1lPR8jD2x4i+4/lvKcj2Plz0Q5PR8gj+MVbCm9USv6X4NRVEY6JHlNTSvkYPaamlPIpWtSUUj5D8NwzPZ2hRU0p5TJPPdPTGVrUlFIu0y01pZRP0WNqSimfocfUlFI+R7fUlFI+RYuaUsqn6O6nUsrHaFFTSvkQ7y1pWtSUUi4TvLmsee9lwTarYjfSYlgfmg3pxXvz5uSZbozhuelv0WxIL9qO7M/OuH3Z05o+0o02j/Xj5sfv4pZR9+aZ98P5n3Flz+tJO/Wn03lWxqznhsHdaPpIF979ema+eUZ/PIGmj3Sh1Yg+7Ijbmz1txKQx1B7QlhbDe9nNs+vgPm4ZdTc3PnY7Nz/Rj5gDu5zO46oVMetoOqgL1wy8jXe+mu6WPn6M/ZlWw++gxdA+vD/vkzzTjTG8MP1tWgztQ7vH787+mf0ef5gOT9yT/ap9VzumLfgCgAUbVtL20f6E9I5m+++/5lmmI972O+TIrQ1asuWZz4kd/SWj2t+XZ3qVshX58qE3Wf/kJ/z81L+5t3n3EunXFSIl9uAVt3DrlpqIHAZOAxaceGBCbhaLhf/7+F989/o0IoJC6fjUfXRr1Z5Gtepmt1kZs4GDiUeJnfEDMQd288zUCaya9N/s6QvfmEnQFVfmWXZ8ShJrtm+mRki4S3menvIaP7wxm8jgUNo9eRfdW93C1VH1stus2LqOg4lH2Dl7GVv372TUR6+yZvJXANzXqS/Det/LkInP2y137OyJvHDfY3Ru0Y7lW9YydvZElr39b6dzuZJ/1JTxLH7jEyKDw7jpiTvp2fpWu/wl0cdz097km9emEhEUSqenH6Brq/Y0rHVVdptVsRs5lHiMLdO/J/bAHv7v43+x4t1/U79GbdZ88GX2cpo83I0eN1qH7bk6qh6fvvgOz0x5w+U83vQ75Iif+PFOn6e5ffZTJJ5KYfXImSzdt5EDJw5ntxl84x0cSD7MPZ89T1DFqmx95nPm7VhBuiWjRDI4y5vPfpbGltotxpjrXS1oALG/7eGq8JrUDqtBmcBA7mjXhSWb19i1WfLLGgZ07ImI0KJRU06dPU3SyZRClz1m5kReGTgKV/6YxPy2i6sialEnvCZlAsvQr313Fm9ebddm0ebV3HNrH0SElldfz6kzf5N08gQANzVpwZWVq+ZZrojw97kzAJw6d4bwoOrOh3LB1gO7qBseRZ3wWpQJLEP/9j1YtGlVifax7fe91MnxM7u9XWeW/rLGrs3SzWu5q2MPRIToRk04dfZMnp/Zup1bqB1eg5rVrQWjQc061K9R2+U83vY75EjzmldzKC2BIyePk27JYP7OH+ne2P7ZvQZDpbIVAKhYpjx/nvubjExLyQRwgQtPaC91Xr37eTztBJEhYdnvI4JDOZ52Im+b4Bxtgi62ERHuGDeCDk/ew6fLvslus+SXNYQHhdDkqoYu5UlMPUGNHHkig0NJTEvOlSeZGjnzBIeRmGqfObe3hr3A2NkTafjALYyZ9TbjH37KpVzOSkxLzpU/jIRc+YvreNoJIoJDs99bfx4pedpE2rWpnqfNd+tXcEe7LiWSx5t+hxwJrxJCwqmL2RJPpRBeJdiuzcyfv6VB9Sj2vfg9G0d9ygsLP8CYfB9qftly94kCA6wQEQNMN8bMyN1ARIYCQwFq1KyRa+a8P6zc++n5/UCz2ix7+1PCg6qT8tdJbh87nPo16nBDvcZM+moW3772cRG+mXz6wvk8BZm1eC5vDn2evjd15tt1S3l08lgW/SvvsajiKko2d/RR2M/1Qno6y35Zy9gHRxY/j5f9DjmS348id7KODVqx+3gcvWc+SZ2gSL4bNIlN7+/k9P9Kd8Rob75Ozd1bam2NMc2AbsBjItIudwNjzAxjTLQxJjo4JMhuWkRQKAkpSdnvE1OTCasWYt8mOJSE1Bxt0i62ydqNC6lajZ433sK23/bwR1I8R5ITuPnxu2j6SDcSU0/QftQ9JP+ZWug3ExkcSnyOPAmpyXl2FSOCw4jPmSc1ifAg+8y5fbHqe/q07QTAHTd3JfbA7kKzFEVkcFiu/ElEVCvZXd2I4FASUy9u/Vl/HvZbGxFBoSTYtTlh12ZV7Eaa1m1E9Svtfx+KlMfLfoccSTyVQuQVF38eEVeEkPS3/TLvi+7Ooj1rAfgjLYEjfx6nfkhUsfr1NW4tasaYRNv/TwDfAS1dmb9Zg2s4mHiUI0kJXEhPZ/665XRr1d6uTbdW7Zm7ehHGGLbu30WVCpUIqxbC2X/Oc/rcWQDO/nOe1ds3cXVUPa6pXZ/fP/+JXXOWsmvOUiKCq7N28peEXhmcXwQ7zRs04WDiEQ4nxXMh/QLfrF1C99b248/3aH0LX/64AGMMW/btoErFyoQVUjjCgqqzfvdWANbs2EzdSPf8kkY3bEJc4mEOJx3jQvoF5q1dTI/Wt5ZoHzfUb8yhxGPZP7Pv1q2ga0v7n1nXVu34evVijDHE7N+d/TPLMn/dcu5o37VE8njb75Aj2+L3UzeoBrWuDCfQP4A7rruVpb9usGsT/1cy7eo1ByCk0pXUC67F4ZOJxerXdc4eUfOxs58iUhHwM8actn3dGXjVlWUE+Afw9vDnuXPcCCyZmdzXqQ9XR9VjzpJ5ADzSvT+do29mZcwGmg3pRfmy5ZgyajwAKX+lcf/rTwNgyczgzvbduK1522J9TwH+Abw7Yix9xw7GYsnkgc530DiqPrMWzwVgcI8BdGnRnuVb19H0kS6UL1eOaU9dPFv38JvPsH7XFtL+/osG93dgzAMjeahLPz564lWenf4GGRYL5cqU5cMnXFpNLuV/79Fx9BozCEumhYc696Nx7fol3sebw5+l/8sjycy0cO9tfWgUVZdPllqPRw3s1o9O0TexKmYjLYb2oXzZcnzw5CvZ85/75zxrd/zCpMdetFvu4k2reX76O6Sd+pN7X32Sa+s0YN6rU5zK402/Q45YMi08+8N7fPvIu/j7+fF5zGL2nzjMwFZ9APjklwW88+OnTOn/IhtHfYogjF86jZPnTrktU36sV6l57+6nuOsgo4hchXXrDKzF8wtjzARH89zQ/Hrz088lezauOPRpUoU7m37a0xHseNv6AQgfW/wTHiXlf//ZT2bS2WJVpBuaX29+cvKs+ZVlQ2KLcuVDcbhtS80Ycwi4zl3LV0p5kvduqeltUkopl3lvSdOippQqEu8ta1rUlFIu0uG8lVI+xNvPfmpRU0oVgRY1pZQP8d6SpkVNKVUEekxNKeVDvHvkWy1qSimXefOJAq8eT00p5YVKcDhvEekqIgdEJE5Ens9nuojIB7bpu0SkWWHL1KKmlPIIEfEHpmAdmqwxcI+INM7VrBtQ3/YaChQ6iJ0WNaWUS7KuUyuBoYdaAnHGmEPGmAvAXKBPrjZ9gH8bq81AVRFx+FAIrzqmtmPbztQry4UcKYFFBQPFG7GvZGkex7wtD3hfppLKU+zB+rbFbl9ePqCis4PHlRORmBzvZ+QYATsSOJZjWjzQKtf8+bWJBI4X1KFXFTVjjOMhYp0kIjGlPdyJI5rHMW/LA96XyZvyGGNKZgTP/E+h5h4LzZk2dnT3UynlKfFAzRzvawC5h/F1po0dLWpKKU/ZCtQXkToiUgYYAPyQq80PwIO2s6CtgVPGmAJ3PcHLdj9LUJ6nVnmY5nHM2/KA92XytjzFZozJEJGRwHLAH5hjjNkrIsNt06cBS4DuQBxwDhhY2HLdNpy3Ukp5gu5+KqV8ihY1pZRP8amiVtgtFx7IM0dETojIHk9nARCRmiLyk4jsE5G9IvKkh/OUE5EtIrLTlme8J/NkERF/EdkuIos8nQVARA6LyG4R2ZHrmi+VD585pma75eI3oBPW08BbgXuMMb96MFM74AzWK6Kv9VSOHHnCgXBjzDYRqQzEAn09tY7EenNgRWPMGREJBDYAT9quHPcYEXkaiAaqGGN6ejKLLc9hINoY400XA3stX9pSc+aWi1JljFkHnPRkhpyMMceNMdtsX58G9mG9OttTeYwx5oztbaDt5dG/siJSA+gBzPJkDlV0vlTUCrqdQuVDRGoDNwC/eDiHv4jsAE4AK40xHs0DTAaeBTI9nCMnA6wQkVgRGerpMN7Ol4qay7dTXK5EpBLwLTDKGPO3J7MYYyzGmOuxXineUkQ8tpsuIj2BE8aYWE9lKEBbY0wzrCNWPGY7rKEK4EtFzeXbKS5HtmNX3wKfG2PmezpPFmPMX8AaoKTuKyyKtkBv2zGsuUBHEfmvB/MAYIxJtP3/BPAd1kMtqgC+VNScueXismY7MD8b2GeMmeQFeUJEpKrt6/LAbcB+T+UxxrxgjKlhjKmN9fdntTHmfk/lARCRiraTOohIRaAz4BVn072VzxQ1Y0wGkHXLxT7ga2PMXk9mEpEvgU1AQxGJF5FBnsyDdUvkAaxbIDtsr+4ezBMO/CQiu7D+UVppjPGKyyi8SCiwQUR2AluAxcaYZR7O5NV85pIOpZQCH9pSU0op0KKmlPIxWtSUUj5Fi5pSyqdoUVNK+RQtapcQEbHYLsPYIyLzRKRCMZb1qYj0s309K5/nLeZs20FE2hShj8MikuepQwV9nqvNGUfT82n/ioiMdjWj8j1a1C4t540x19tG/LgADM850TZSicuMMYMLGamjA+ByUVPKE7SoXbrWA/VsW1E/icgXwG7bDeLviMhWEdklIsPAejeBiHwkIr+KyGKgetaCRGSNiETbvu4qIttsY5z9aLvxfTjwlG0r8WbbnQDf2vrYKiJtbfMGicgK21hk08n/flw7IvK97Ubtvblv1haRd21ZfhSRENtndUVkmW2e9SLSqETWpvIZvvrgFZ8mIgFYb27OurK8JXCtMeYPW2E4ZYxpISJlgY0isgLriBwNgSZYr1L/FZiTa7khwEygnW1Z1YwxJ0VkGnDGGDPR1u4L4D1jzAYRqYX1Lo6rgZeBDcaYV0WkB+DMiBKP2PooD2wVkW+NMWlARWCbMeYZERlnW/ZIrA8gGW6M+V1EWgFTgY5FWI3KR2lRu7SUtw3TA9YttdlYdwu3GGP+sH3eGWiadbwMuAKoD7QDvjTGWIBEEVmdz/JbA+uylmWMKWgsuNuAxtZbSQGoYrs/sR1wh23exSLypxPf0xMicrvt65q2rGlYh/75yvb5f4H5ttFF2gDzcvRd1ok+1GVEi9ql5bxtmJ5stn/cZ3N+BDxujFmeq113Ch+KSZxoA9bDFjcaY87nk8Xp++5EpAPWAnmjMeaciKwByhXQ3Nj6/Sv3OlAqJz2m5nuWAyNsQwwhIg1sozusAwbYjrmFA7fkM+8moL2I1LHNW832+Wmgco52K7DuCmJrd73ty3XAfbbPugFXFpL1CuBPW0FrhHVLMYsfkLW1eS/W3dq/gT9EpL+tDxGR6wrpQ11mtKj5nllYj5dtE+sDX6Zj3SL/Dvgd2A18DKzNPaMxJgXrcbD5tlEhsnb/FgK3Z50oAJ4Aom0nIn7l4lnY8UA7EdmGdTf4aCFZlwEBtlE6XgNyPpvgLHCNiMRiPWb2qu3z+4BBtnx78fCQ7cr76CgdSimfoltqSimfokVNKeVTtKgppXyKFjWllE/RoqaU8ila1JRSPkWLmlLKp/w/gcY71I6nT2QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import plot_confusion_matrix\n",
    "from sklearn.metrics import confusion_matrix, plot_confusion_matrix\n",
    "\n",
    "y_pred = clf.predict(x_test)\n",
    "conf_mat = confusion_matrix(y_test, y_pred, normalize='true')\n",
    "print(conf_mat)\n",
    "\n",
    "\n",
    "disp = plot_confusion_matrix(clf, x_test, y_test, \n",
    "                             display_labels=[0,1,2,3,4,5], cmap=plt.cm.Greens, normalize='true')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ed08ac7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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n.childContextTypes?u(\"107\",this.getName()||\"ReactCompositeComponent\"):void 0;for(var i in e)i in n.childContextTypes?void 0:u(\"108\",this.getName()||\"ReactCompositeComponent\",i);return c({},t,e)}return t},_checkContextTypes:function(t,e,n){},receiveComponent:function(t,e,n){var r=this._currentElement,i=this._context;this._pendingElement=null,this.updateComponent(e,r,t,i,n)},performUpdateIfNecessary:function(t){null!=this._pendingElement?v.receiveComponent(this,this._pendingElement,t,this._context):null!==this._pendingStateQueue||this._pendingForceUpdate?this.updateComponent(t,this._currentElement,this._currentElement,this._context,this._context):this._updateBatchNumber=null},updateComponent:function(t,e,n,r,i){var o=this._instance;null==o?u(\"136\",this.getName()||\"ReactCompositeComponent\"):void 0;var a,c=!1;this._context===i?a=o.context:(a=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,a);var f=this._processPendingState(l,a),p=!0;this._pendingForceUpdate||(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,a):this._compositeType===_.PureClass&&(p=!m(s,l)||!m(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,a,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=a)},_processPendingState:function(t,e){var n=this._instance,r=this._pendingStateQueue,i=this._pendingReplaceState;if(this._pendingReplaceState=!1,this._pendingStateQueue=null,!r)return n.state;if(i&&1===r.length)return r[0];for(var o=c({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var u=r[a];c(o,\"function\"==typeof u?u.call(n,o,t,e):u)}return o},_performComponentUpdate:function(t,e,n,r,i,o){var a,u,c,s=this._instance,l=Boolean(s.componentDidUpdate);l&&(a=s.props,u=s.state,c=s.context),s.componentWillUpdate&&s.componentWillUpdate(e,n,r),this._currentElement=t,this._context=o,s.props=e,s.state=n,s.context=r,this._updateRenderedComponent(i,o),l&&i.getReactMountReady().enqueue(s.componentDidUpdate.bind(s,a,u,c),s)},_updateRenderedComponent:function(t,e){var n=this._renderedComponent,r=n._currentElement,i=this._renderValidatedComponent(),o=0;if(y(r,i))v.receiveComponent(n,i,t,this._processChildContext(e));else{var a=v.getHostNode(n);v.unmountComponent(n,!1);var u=d.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==d.EMPTY);this._renderedComponent=c;var s=v.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){l.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t,e=this._instance;return t=e.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==_.StatelessFunctional){f.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{f.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t||t===!1||s.isValidElement(t)?void 0:u(\"109\",this.getName()||\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n?u(\"110\"):void 0;var r=e.getPublicInstance(),i=n.refs===g?n.refs={}:n.refs;i[t]=r},detachRef:function(t){var e=this.getPublicInstance().refs;delete e[t]},getName:function(){var t=this._currentElement.type,e=this._instance&&this._instance.constructor;return t.displayName||e&&e.displayName||t.name||e&&e.name||null},getPublicInstance:function(){var t=this._instance;return this._compositeType===_.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=x},function(t,e,n){\"use strict\";var r=n(4),i=n(358),o=n(163),a=n(24),u=n(11),c=n(371),s=n(387),l=n(167),f=n(395);n(1);i.inject();var p={findDOMNode:s,render:o.render,unmountComponentAtNode:o.unmountComponentAtNode,version:c,unstable_batchedUpdates:u.batchedUpdates,unstable_renderSubtreeIntoContainer:f};\"undefined\"!=typeof __REACT_DEVTOOLS_GLOBAL_HOOK__&&\"function\"==typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.inject&&__REACT_DEVTOOLS_GLOBAL_HOOK__.inject({ComponentTree:{getClosestInstanceFromNode:r.getClosestInstanceFromNode,getNodeFromInstance:function(t){return t._renderedComponent&&(t=l(t)),t?r.getNodeFromInstance(t):null}},Mount:o,Reconciler:a});t.exports=p},function(t,e,n){\"use strict\";function r(t){if(t){var e=t._currentElement._owner||null;if(e){var n=e.getName();if(n)return\" This DOM node was rendered by `\"+n+\"`.\"}}return\"\"}function i(t,e){e&&(G[t._tag]&&(null!=e.children||null!=e.dangerouslySetInnerHTML?v(\"137\",t._tag,t._currentElement._owner?\" Check the render method of \"+t._currentElement._owner.getName()+\".\":\"\"):void 0),null!=e.dangerouslySetInnerHTML&&(null!=e.children?v(\"60\"):void 0,\"object\"==typeof e.dangerouslySetInnerHTML&&V in e.dangerouslySetInnerHTML?void 0:v(\"61\")),null!=e.style&&\"object\"!=typeof e.style?v(\"62\",r(t)):void 0)}function o(t,e,n,r){if(!(r instanceof I)){var i=t._hostContainerInfo,o=i._node&&i._node.nodeType===H,u=o?i._node:i._ownerDocument;F(e,u),r.getReactMountReady().enqueue(a,{inst:t,registrationName:e,listener:n})}}function a(){var t=this;C.putListener(t.inst,t.registrationName,t.listener)}function u(){var t=this;S.postMountWrapper(t)}function c(){var t=this;A.postMountWrapper(t)}function s(){var t=this;P.postMountWrapper(t)}function l(){var t=this;t._rootNodeID?void 0:v(\"63\");var e=U(t);switch(e?void 0:v(\"64\"),t._tag){case\"iframe\":case\"object\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"video\":case\"audio\":t._wrapperState.listeners=[];for(var n in q)q.hasOwnProperty(n)&&t._wrapperState.listeners.push(k.trapBubbledEvent(n,q[n],e));break;case\"source\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e),k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topReset\",\"reset\",e),k.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function f(){N.postUpdateWrapper(this)}function p(t){Z.call(X,t)||($.test(t)?void 0:v(\"65\",t),X[t]=!0)}function h(t,e){return t.indexOf(\"-\")>=0||null!=e.is}function d(t){var e=t.type;p(e),this._currentElement=t,this._tag=e.toLowerCase(),this._namespaceURI=null,this._renderedChildren=null,this._previousStyle=null,this._previousStyleCopy=null,this._hostNode=null,this._hostParent=null,this._rootNodeID=0,this._domID=0,this._hostContainerInfo=null,this._wrapperState=null,this._topLevelWrapper=null,this._flags=0}var v=n(2),g=n(3),m=n(332),y=n(334),_=n(20),b=n(82),x=n(21),w=n(156),C=n(22),M=n(83),k=n(51),E=n(157),T=n(4),S=n(351),P=n(352),N=n(158),A=n(355),O=(n(9),n(364)),I=n(369),D=(n(8),n(54)),R=(n(0),n(94),n(80),n(96),n(1),E),L=C.deleteListener,U=T.getNodeFromInstance,F=k.listenTo,j=M.registrationNameModules,B={string:!0,number:!0},W=\"style\",V=\"__html\",z={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},H=11,q={topAbort:\"abort\",topCanPlay:\"canplay\",topCanPlayThrough:\"canplaythrough\",topDurationChange:\"durationchange\",topEmptied:\"emptied\",topEncrypted:\"encrypted\",topEnded:\"ended\",topError:\"error\",topLoadedData:\"loadeddata\",topLoadedMetadata:\"loadedmetadata\",topLoadStart:\"loadstart\",topPause:\"pause\",topPlay:\"play\",topPlaying:\"playing\",topProgress:\"progress\",topRateChange:\"ratechange\",topSeeked:\"seeked\",topSeeking:\"seeking\",topStalled:\"stalled\",topSuspend:\"suspend\",topTimeUpdate:\"timeupdate\",topVolumeChange:\"volumechange\",topWaiting:\"waiting\"},Y={area:!0,base:!0,br:!0,col:!0,embed:!0,hr:!0,img:!0,input:!0,keygen:!0,link:!0,meta:!0,param:!0,source:!0,track:!0,wbr:!0},K={listing:!0,pre:!0,textarea:!0},G=g({menuitem:!0},Y),$=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]*$/,X={},Z={}.hasOwnProperty,Q=1;d.displayName=\"ReactDOMComponent\",d.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=Q++,this._domID=n._idCounter++,this._hostParent=e,this._hostContainerInfo=n;var o=this._currentElement.props;switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":this._wrapperState={listeners:null},t.getReactMountReady().enqueue(l,this);break;case\"input\":S.mountWrapper(this,o,e),o=S.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"option\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o);break;case\"select\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"textarea\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o),t.getReactMountReady().enqueue(l,this)}i(this,o);var a,f;null!=e?(a=e._namespaceURI,f=e._tag):n._tag&&(a=n._namespaceURI,f=n._tag),(null==a||a===b.svg&&\"foreignobject\"===f)&&(a=b.html),a===b.html&&(\"svg\"===this._tag?a=b.svg:\"math\"===this._tag&&(a=b.mathml)),this._namespaceURI=a;var p;if(t.useCreateElement){var h,d=n._ownerDocument;if(a===b.html)if(\"script\"===this._tag){var v=d.createElement(\"div\"),g=this._currentElement.type;v.innerHTML=\"<\"+g+\"></\"+g+\">\",h=v.removeChild(v.firstChild)}else h=o.is?d.createElement(this._currentElement.type,o.is):d.createElement(this._currentElement.type);else h=d.createElementNS(a,this._currentElement.type);T.precacheNode(this,h),this._flags|=R.hasCachedChildNodes,this._hostParent||w.setAttributeForRoot(h),this._updateDOMProperties(null,o,t);var y=_(h);this._createInitialChildren(t,o,r,y),p=y}else{var x=this._createOpenTagMarkupAndPutListeners(t,o),C=this._createContentMarkup(t,o,r);p=!C&&Y[this._tag]?x+\"/>\":x+\">\"+C+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"select\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return p},_createOpenTagMarkupAndPutListeners:function(t,e){var n=\"<\"+this._currentElement.type;for(var r in e)if(e.hasOwnProperty(r)){var i=e[r];if(null!=i)if(j.hasOwnProperty(r))i&&o(this,r,i,t);else{r===W&&(i&&(i=this._previousStyleCopy=g({},e.style)),i=y.createMarkupForStyles(i,this));var a=null;null!=this._tag&&h(this._tag,e)?z.hasOwnProperty(r)||(a=w.createMarkupForCustomAttribute(r,i)):a=w.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent||(n+=\" \"+w.createMarkupForRoot()),n+=\" \"+w.createMarkupForID(this._domID))},_createContentMarkup:function(t,e,n){var r=\"\",i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&(r=i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=D(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return K[this._tag]&&\"\\n\"===r.charAt(0)?\"\\n\"+r:r},_createInitialChildren:function(t,e,n,r){var i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&_.queueHTML(r,i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&_.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)_.queueChild(r,u[c])}},receiveComponent:function(t,e,n){var r=this._currentElement;this._currentElement=t,this.updateComponent(e,r,t,n)},updateComponent:function(t,e,n,r){var o=e.props,a=this._currentElement.props;switch(this._tag){case\"input\":o=S.getHostProps(this,o),a=S.getHostProps(this,a);break;case\"option\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"select\":o=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"textarea\":o=A.getHostProps(this,o),a=A.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":S.updateWrapper(this);break;case\"textarea\":A.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(f,this)}},_updateDOMProperties:function(t,e,n){var r,i,a;for(r in t)if(!e.hasOwnProperty(r)&&t.hasOwnProperty(r)&&null!=t[r])if(r===W){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a||{},a[i]=\"\");this._previousStyleCopy=null}else j.hasOwnProperty(r)?t[r]&&L(this,r):h(this._tag,t)?z.hasOwnProperty(r)||w.deleteValueForAttribute(U(this),r):(x.properties[r]||x.isCustomAttribute(r))&&w.deleteValueForProperty(U(this),r);for(r in e){var c=e[r],s=r===W?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c||null!=s))if(r===W)if(c?c=this._previousStyleCopy=g({},c):this._previousStyleCopy=null,s){for(i in s)!s.hasOwnProperty(i)||c&&c.hasOwnProperty(i)||(a=a||{},a[i]=\"\");for(i in c)c.hasOwnProperty(i)&&s[i]!==c[i]&&(a=a||{},a[i]=c[i])}else a=c;else if(j.hasOwnProperty(r))c?o(this,r,c,n):s&&L(this,r);else if(h(this._tag,e))z.hasOwnProperty(r)||w.setValueForAttribute(U(this),r,c);else if(x.properties[r]||x.isCustomAttribute(r)){var l=U(this);null!=c?w.setValueForProperty(l,r,c):w.deleteValueForProperty(l,r)}}a&&y.setValueForStyles(U(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=B[typeof t.children]?t.children:null,o=B[typeof e.children]?e.children:null,a=t.dangerouslySetInnerHTML&&t.dangerouslySetInnerHTML.__html,u=e.dangerouslySetInnerHTML&&e.dangerouslySetInnerHTML.__html,c=null!=i?null:t.children,s=null!=o?null:e.children,l=null!=i||null!=a,f=null!=o||null!=u;null!=c&&null==s?this.updateChildren(null,n,r):l&&!f&&this.updateTextContent(\"\"),null!=o?i!==o&&this.updateTextContent(\"\"+o):null!=u?a!==u&&this.updateMarkup(\"\"+u):null!=s&&this.updateChildren(s,n,r)},getHostNode:function(){return U(this)},unmountComponent:function(t){switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":var e=this._wrapperState.listeners;if(e)for(var n=0;n<e.length;n++)e[n].remove();break;case\"html\":case\"head\":case\"body\":v(\"66\",this._tag)}this.unmountChildren(t),T.uncacheNode(this),C.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return U(this)}},g(d.prototype,d.Mixin,O.Mixin),t.exports=d},function(t,e,n){\"use strict\";function r(t,e){var n={_topLevelWrapper:t,_idCounter:1,_ownerDocument:e?e.nodeType===i?e:e.ownerDocument:null,_node:e,_tag:e?e.nodeName.toLowerCase():null,_namespaceURI:e?e.namespaceURI:null};return n}var i=(n(96),9);t.exports=r},function(t,e,n){\"use strict\";var r=n(3),i=n(20),o=n(4),a=function(t){this._currentElement=null,this._hostNode=null,this._hostParent=null,this._hostContainerInfo=null,this._domID=0};r(a.prototype,{mountComponent:function(t,e,n,r){var a=n._idCounter++;this._domID=a,this._hostParent=e,this._hostContainerInfo=n;var u=\" react-empty: \"+this._domID+\" \";if(t.useCreateElement){var c=n._ownerDocument,s=c.createComment(u);return o.precacheNode(this,s),i(s)}return t.renderToStaticMarkup?\"\":\"<!--\"+u+\"-->\"},receiveComponent:function(){},getHostNode:function(){return o.getNodeFromInstance(this)},unmountComponent:function(){o.uncacheNode(this)}}),t.exports=a},function(t,e,n){\"use strict\";var r={useCreateElement:!0,useFiber:!1};t.exports=r},function(t,e,n){\"use strict\";var r=n(81),i=n(4),o={dangerouslyProcessChildrenUpdates:function(t,e){var n=i.getNodeFromInstance(t);r.processUpdates(n,e)}};t.exports=o},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&f.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=c.executeOnChange(e,t);l.asap(r,this);var i=e.name;if(\"radio\"===e.type&&null!=i){for(var a=s.getNodeFromInstance(this),u=a;u.parentNode;)u=u.parentNode;for(var f=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<f.length;p++){var h=f[p];if(h!==a&&h.form===a.form){var d=s.getInstanceFromNode(h);d?void 0:o(\"90\"),l.asap(r,d)}}}return n}var o=n(2),a=n(3),u=n(156),c=n(85),s=n(4),l=n(11),f=(n(0),n(1),{getHostProps:function(t,e){var n=c.getValue(e),r=c.getChecked(e),i=a({type:void 0,step:void 0,min:void 0,max:void 0},e,{defaultChecked:void 0,defaultValue:void 0,value:null!=n?n:t._wrapperState.initialValue,checked:null!=r?r:t._wrapperState.initialChecked,onChange:t._wrapperState.onChange});return i},mountWrapper:function(t,e){var n=e.defaultValue;t._wrapperState={initialChecked:null!=e.checked?e.checked:e.defaultChecked,initialValue:null!=e.value?e.value:n,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&u.setValueForProperty(s.getNodeFromInstance(t),\"checked\",n||!1);var r=s.getNodeFromInstance(t),i=c.getValue(e);if(null!=i){var o=\"\"+i;o!==r.value&&(r.value=o)}else null==e.value&&null!=e.defaultValue&&r.defaultValue!==\"\"+e.defaultValue&&(r.defaultValue=\"\"+e.defaultValue),null==e.checked&&null!=e.defaultChecked&&(r.defaultChecked=!!e.defaultChecked)},postMountWrapper:function(t){var e=t._currentElement.props,n=s.getNodeFromInstance(t);switch(e.type){case\"submit\":case\"reset\":break;case\"color\":case\"date\":case\"datetime\":case\"datetime-local\":case\"month\":case\"time\":case\"week\":n.value=\"\",n.value=n.defaultValue;break;default:n.value=n.value}var r=n.name;\"\"!==r&&(n.name=\"\"),n.defaultChecked=!n.defaultChecked,n.defaultChecked=!n.defaultChecked,\"\"!==r&&(n.name=r)}});t.exports=f},function(t,e,n){\"use strict\";function r(t){var e=\"\";return o.Children.forEach(t,function(t){null!=t&&(\"string\"==typeof t||\"number\"==typeof t?e+=t:c||(c=!0))}),e}var i=n(3),o=n(26),a=n(4),u=n(158),c=(n(1),!1),s={mountWrapper:function(t,e,n){var i=null;if(null!=n){var o=n;\"optgroup\"===o._tag&&(o=o._hostParent),null!=o&&\"select\"===o._tag&&(i=u.getSelectValueContext(o))}var a=null;if(null!=i){var c;if(c=null!=e.value?e.value+\"\":r(e.children),a=!1,Array.isArray(i)){for(var s=0;s<i.length;s++)if(\"\"+i[s]===c){a=!0;break}}else a=\"\"+i===c}t._wrapperState={selected:a}},postMountWrapper:function(t){var e=t._currentElement.props;if(null!=e.value){var n=a.getNodeFromInstance(t);n.setAttribute(\"value\",e.value)}},getHostProps:function(t,e){var n=i({selected:void 0,children:void 0},e);null!=t._wrapperState.selected&&(n.selected=t._wrapperState.selected);var o=r(e.children);return o&&(n.children=o),n}};t.exports=s},function(t,e,n){\"use strict\";function r(t,e,n,r){return t===n&&e===r}function i(t){var e=document.selection,n=e.createRange(),r=n.text.length,i=n.duplicate();i.moveToElementText(t),i.setEndPoint(\"EndToStart\",n);var o=i.text.length,a=o+r;return{start:o,end:a}}function o(t){var e=window.getSelection&&window.getSelection();if(!e||0===e.rangeCount)return null;var n=e.anchorNode,i=e.anchorOffset,o=e.focusNode,a=e.focusOffset,u=e.getRangeAt(0);try{u.startContainer.nodeType,u.endContainer.nodeType}catch(t){return null}var c=r(e.anchorNode,e.anchorOffset,e.focusNode,e.focusOffset),s=c?0:u.toString().length,l=u.cloneRange();l.selectNodeContents(t),l.setEnd(u.startContainer,u.startOffset);var f=r(l.startContainer,l.startOffset,l.endContainer,l.endOffset),p=f?0:l.toString().length,h=p+s,d=document.createRange();d.setStart(n,i),d.setEnd(o,a);var v=d.collapsed;return{start:v?h:p,end:v?p:h}}function a(t,e){var n,r,i=document.selection.createRange().duplicate();void 0===e.end?(n=e.start,r=n):e.start>e.end?(n=e.end,r=e.start):(n=e.start,r=e.end),i.moveToElementText(t),i.moveStart(\"character\",n),i.setEndPoint(\"EndToStart\",i),i.moveEnd(\"character\",r-n),i.select()}function u(t,e){if(window.getSelection){var n=window.getSelection(),r=t[l()].length,i=Math.min(e.start,r),o=void 0===e.end?i:Math.min(e.end,r);if(!n.extend&&i>o){var a=o;o=i,i=a}var u=s(t,i),c=s(t,o);if(u&&c){var f=document.createRange();f.setStart(u.node,u.offset),n.removeAllRanges(),i>o?(n.addRange(f),n.extend(c.node,c.offset)):(f.setEnd(c.node,c.offset),n.addRange(f))}}}var c=n(6),s=n(392),l=n(168),f=c.canUseDOM&&\"selection\"in document&&!(\"getSelection\"in window),p={getOffsets:f?i:o,setOffsets:f?a:u};t.exports=p},function(t,e,n){\"use strict\";var r=n(2),i=n(3),o=n(81),a=n(20),u=n(4),c=n(54),s=(n(0),n(96),function(t){this._currentElement=t,this._stringText=\"\"+t,this._hostNode=null,this._hostParent=null,this._domID=0,this._mountIndex=0,this._closingComment=null,this._commentNodes=null});i(s.prototype,{mountComponent:function(t,e,n,r){var i=n._idCounter++,o=\" react-text: \"+i+\" \",s=\" /react-text \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var l=n._ownerDocument,f=l.createComment(o),p=l.createComment(s),h=a(l.createDocumentFragment());return a.queueChild(h,a(f)),this._stringText&&a.queueChild(h,a(l.createTextNode(this._stringText))),a.queueChild(h,a(p)),u.precacheNode(this,f),this._closingComment=p,h}var d=c(this._stringText);return t.renderToStaticMarkup?d:\"<!--\"+o+\"-->\"+d+\"<!--\"+s+\"-->\"},receiveComponent:function(t,e){if(t!==this._currentElement){this._currentElement=t;var n=\"\"+t;if(n!==this._stringText){this._stringText=n;var r=this.getHostNode();o.replaceDelimitedText(r[0],r[1],n)}}},getHostNode:function(){var t=this._commentNodes;if(t)return t;if(!this._closingComment)for(var e=u.getNodeFromInstance(this),n=e.nextSibling;;){if(null==n?r(\"67\",this._domID):void 0,8===n.nodeType&&\" /react-text \"===n.nodeValue){this._closingComment=n;break}n=n.nextSibling}return t=[this._hostNode,this._closingComment],this._commentNodes=t,t},unmountComponent:function(){this._closingComment=null,this._commentNodes=null,u.uncacheNode(this)}}),t.exports=s},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&l.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=u.executeOnChange(e,t);return s.asap(r,this),n}var o=n(2),a=n(3),u=n(85),c=n(4),s=n(11),l=(n(0),n(1),{getHostProps:function(t,e){null!=e.dangerouslySetInnerHTML?o(\"91\"):void 0;var n=a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange});return n},mountWrapper:function(t,e){var n=u.getValue(e),r=n;if(null==n){var a=e.defaultValue,c=e.children;null!=c&&(null!=a?o(\"92\"):void 0,Array.isArray(c)&&(c.length<=1?void 0:o(\"93\"),c=c[0]),a=\"\"+c),null==a&&(a=\"\"),r=a}t._wrapperState={initialValue:\"\"+r,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=c.getNodeFromInstance(t),r=u.getValue(e);if(null!=r){var i=\"\"+r;i!==n.value&&(n.value=i),null==e.defaultValue&&(n.defaultValue=i)}null!=e.defaultValue&&(n.defaultValue=e.defaultValue)},postMountWrapper:function(t){var e=c.getNodeFromInstance(t),n=e.textContent;\n",
       "n===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t?void 0:c(\"33\"),\"_hostNode\"in e?void 0:c(\"33\");for(var n=0,r=t;r;r=r._hostParent)n++;for(var i=0,o=e;o;o=o._hostParent)i++;for(;n-i>0;)t=t._hostParent,n--;for(;i-n>0;)e=e._hostParent,i--;for(var a=n;a--;){if(t===e)return t;t=t._hostParent,e=e._hostParent}return null}function i(t,e){\"_hostNode\"in t?void 0:c(\"35\"),\"_hostNode\"in e?void 0:c(\"35\");for(;e;){if(e===t)return!0;e=e._hostParent}return!1}function o(t){return\"_hostNode\"in t?void 0:c(\"36\"),t._hostParent}function a(t,e,n){for(var r=[];t;)r.push(t),t=t._hostParent;var i;for(i=r.length;i-- >0;)e(r[i],\"captured\",n);for(i=0;i<r.length;i++)e(r[i],\"bubbled\",n)}function u(t,e,n,i,o){for(var a=t&&e?r(t,e):null,u=[];t&&t!==a;)u.push(t),t=t._hostParent;for(var c=[];e&&e!==a;)c.push(e),e=e._hostParent;var s;for(s=0;s<u.length;s++)n(u[s],\"bubbled\",i);for(s=c.length;s-- 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r(){C||(C=!0,y.EventEmitter.injectReactEventListener(m),y.EventPluginHub.injectEventPluginOrder(u),y.EventPluginUtils.injectComponentTree(p),y.EventPluginUtils.injectTreeTraversal(d),y.EventPluginHub.injectEventPluginsByName({SimpleEventPlugin:w,EnterLeaveEventPlugin:c,ChangeEventPlugin:a,SelectEventPlugin:x,BeforeInputEventPlugin:o}),y.HostComponent.injectGenericComponentClass(f),y.HostComponent.injectTextComponentClass(v),y.DOMProperty.injectDOMPropertyConfig(i),y.DOMProperty.injectDOMPropertyConfig(s),y.DOMProperty.injectDOMPropertyConfig(b),y.EmptyComponent.injectEmptyComponentFactory(function(t){return new h(t)}),y.Updates.injectReconcileTransaction(_),y.Updates.injectBatchingStrategy(g),y.Component.injectEnvironment(l))}var i=n(331),o=n(333),a=n(335),u=n(337),c=n(338),s=n(341),l=n(343),f=n(346),p=n(4),h=n(348),d=n(356),v=n(354),g=n(357),m=n(361),y=n(362),_=n(367),b=n(372),x=n(373),w=n(374),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof 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v={_enabled:!0,_handleTopLevel:null,WINDOW_HANDLE:s.canUseDOM?window:null,setHandleTopLevel:function(t){v._handleTopLevel=t},setEnabled:function(t){v._enabled=!!t},isEnabled:function(){return v._enabled},trapBubbledEvent:function(t,e,n){return n?c.listen(n,e,v.dispatchEvent.bind(null,t)):null},trapCapturedEvent:function(t,e,n){return n?c.capture(n,e,v.dispatchEvent.bind(null,t)):null},monitorScrollValue:function(t){var e=a.bind(null,t);c.listen(window,\"scroll\",e)},dispatchEvent:function(t,e){if(v._enabled){var n=i.getPooled(t,e);try{p.batchedUpdates(o,n)}finally{i.release(n)}}}};t.exports=v},function(t,e,n){\"use strict\";var r=n(21),i=n(22),o=n(50),a=n(86),u=n(159),c=n(51),s=n(161),l=n(11),f={Component:a.injection,DOMProperty:r.injection,EmptyComponent:u.injection,EventPluginHub:i.injection,EventPluginUtils:o.injection,EventEmitter:c.injection,HostComponent:s.injection,Updates:l.injection};t.exports=f},function(t,e,n){\"use strict\";var r=n(385),i=/\\/?>/,o=/^<\\!\\-\\-/,a={CHECKSUM_ATTR_NAME:\"data-react-checksum\",addChecksumToMarkup:function(t){var e=r(t);return o.test(t)?t:t.replace(i,\" \"+a.CHECKSUM_ATTR_NAME+'=\"'+e+'\"$&')},canReuseMarkup:function(t,e){var n=e.getAttribute(a.CHECKSUM_ATTR_NAME);n=n&&parseInt(n,10);var i=r(t);return i===n}};t.exports=a},function(t,e,n){\"use strict\";function r(t,e,n){return{type:\"INSERT_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:n,afterNode:e}}function i(t,e,n){return{type:\"MOVE_EXISTING\",content:null,fromIndex:t._mountIndex,fromNode:p.getHostNode(t),toIndex:n,afterNode:e}}function o(t,e){return{type:\"REMOVE_NODE\",content:null,fromIndex:t._mountIndex,fromNode:e,toIndex:null,afterNode:null}}function a(t){return{type:\"SET_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function u(t){return{type:\"TEXT_CONTENT\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function c(t,e){return e&&(t=t||[],t.push(e)),t}function s(t,e){f.processChildrenUpdates(t,e)}var l=n(2),f=n(86),p=(n(40),n(9),n(15),n(24)),h=n(342),d=(n(8),n(388)),v=(n(0),{Mixin:{_reconcilerInstantiateChildren:function(t,e,n){return h.instantiateChildren(t,e,n)},_reconcilerUpdateChildren:function(t,e,n,r,i,o){var a,u=0;return a=d(e,u),h.updateChildren(t,a,n,r,i,this,this._hostContainerInfo,o,u),a},mountChildren:function(t,e,n){var r=this._reconcilerInstantiateChildren(t,e,n);this._renderedChildren=r;var i=[],o=0;for(var a in r)if(r.hasOwnProperty(a)){var u=r[a],c=0,s=p.mountComponent(u,e,this,this._hostContainerInfo,n,c);u._mountIndex=o++,i.push(s)}return i},updateTextContent:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[u(t)];s(this,r)},updateMarkup:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[a(t)];s(this,r)},updateChildren:function(t,e,n){this._updateChildren(t,e,n)},_updateChildren:function(t,e,n){var r=this._renderedChildren,i={},o=[],a=this._reconcilerUpdateChildren(r,t,o,i,e,n);if(a||r){var u,l=null,f=0,h=0,d=0,v=null;for(u in a)if(a.hasOwnProperty(u)){var g=r&&r[u],m=a[u];g===m?(l=c(l,this.moveChild(g,v,f,h)),h=Math.max(g._mountIndex,h),g._mountIndex=f):(g&&(h=Math.max(g._mountIndex,h)),l=c(l,this._mountChildAtIndex(m,o[d],v,f,e,n)),d++),f++,v=p.getHostNode(m)}for(u in i)i.hasOwnProperty(u)&&(l=c(l,this._unmountChild(r[u],i[u])));l&&s(this,l),this._renderedChildren=a}},unmountChildren:function(t){var e=this._renderedChildren;h.unmountChildren(e,t),this._renderedChildren=null},moveChild:function(t,e,n,r){if(t._mountIndex<r)return i(t,e,n)},createChild:function(t,e,n){return r(n,e,t._mountIndex)},removeChild:function(t,e){return o(t,e)},_mountChildAtIndex:function(t,e,n,r,i,o){return t._mountIndex=r,this.createChild(t,n,e)},_unmountChild:function(t,e){var n=this.removeChild(t,e);return t._mountIndex=null,n}}});t.exports=v},function(t,e,n){\"use strict\";function r(t){return!(!t||\"function\"!=typeof t.attachRef||\"function\"!=typeof t.detachRef)}var i=n(2),o=(n(0),{addComponentAsRefTo:function(t,e,n){r(n)?void 0:i(\"119\"),n.attachRef(e,t)},removeComponentAsRefFrom:function(t,e,n){r(n)?void 0:i(\"120\");var o=n.getPublicInstance();o&&o.refs[e]===t.getPublicInstance()&&n.detachRef(e)}});t.exports=o},function(t,e,n){\"use strict\";var r=\"SECRET_DO_NOT_PASS_THIS_OR_YOU_WILL_BE_FIRED\";t.exports=r},function(t,e,n){\"use strict\";function r(t){this.reinitializeTransaction(),this.renderToStaticMarkup=!1,this.reactMountReady=o.getPooled(null),this.useCreateElement=t}var i=n(3),o=n(155),a=n(17),u=n(51),c=n(162),s=(n(9),n(53)),l=n(88),f={initialize:c.getSelectionInformation,close:c.restoreSelection},p={initialize:function(){var t=u.isEnabled();return u.setEnabled(!1),t},close:function(t){u.setEnabled(t)}},h={initialize:function(){this.reactMountReady.reset()},close:function(){this.reactMountReady.notifyAll()}},d=[f,p,h],v={getTransactionWrappers:function(){return d},getReactMountReady:function(){return this.reactMountReady},getUpdateQueue:function(){return l},checkpoint:function(){return this.reactMountReady.checkpoint()},rollback:function(t){this.reactMountReady.rollback(t)},destructor:function(){o.release(this.reactMountReady),this.reactMountReady=null}};i(r.prototype,s,v),a.addPoolingTo(r),t.exports=r},function(t,e,n){\"use strict\";function r(t,e,n){\"function\"==typeof t?t(e.getPublicInstance()):o.addComponentAsRefTo(e,t,n)}function i(t,e,n){\"function\"==typeof t?t(null):o.removeComponentAsRefFrom(e,t,n)}var o=n(365),a={};a.attachRefs=function(t,e){if(null!==e&&\"object\"==typeof e){var n=e.ref;null!=n&&r(n,t,e._owner)}},a.shouldUpdateRefs=function(t,e){var n=null,r=null;null!==t&&\"object\"==typeof 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import shap\n",
    "shap.initjs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4011c56e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute SHAP values\n",
    "explainer = shap.Explainer(clf)\n",
    "shap_values = explainer.shap_values(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "74caf51b",
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 576x684 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values, X.values, plot_type=\"bar\", class_names=clf.classes_, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a177d9f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2613412228796844"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[\"patient_id\"] = PATIENT_IDS.copy()\n",
    "imp_unscaled[\"UMAP_KNN\"] = spectral_clusters[\"UMAP_KNN\"].copy()\n",
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==0][\"ed_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "05a1d55b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.9339250493096647"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==0][\"op_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "24cf298b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1014.000000\n",
       "mean       39.311637\n",
       "std        11.772252\n",
       "min         9.000000\n",
       "25%        31.000000\n",
       "50%        37.000000\n",
       "75%        47.000000\n",
       "max        85.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==0][\"age\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e9b5994e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values[0], X.values, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dccfe881",
   "metadata": {},
   "source": [
    "This first group of 1,014 patients (45% of the sample) are low-utilizers with a mean of 2 outpatient / clinic visits per person during the two-year period, and 0.26 ED visits per person.  The age range of the cluster is 9 years to 85 years and the median age is 37.  The majority of people in this group are under age 47.  They are English-speaking, and many identify as Hispanic or Latino.  There are more who are not insured or who have unknown insurance in this group.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "16ead655",
   "metadata": {},
   "outputs": [],
   "source": [
    "zero = imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==0].copy()\n",
    "admitted = zero[zero[\"admitted\"]>0].copy().reset_index()\n",
    "ed_visits = zero[zero[\"ed_visit_count\"]>0].copy().reset_index()\n",
    "op_visits = zero[zero[\"op_visit_count\"]>0].copy().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "16716898",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_ed_conditions(df, item):\n",
    "    cvd = hf = htn = dm = sens = uri = copd = neuro = cog = sud = mhd = inf = pain = ren = liv = acc = tob = 0\n",
    "    num_patients = 0\n",
    "    num_item = 0\n",
    "    for i in range(len(df)):\n",
    "        num_patients += 1\n",
    "        num_item += df.at[i, item]\n",
    "        if df.at[i, \"CVD_ed\"] > 0:\n",
    "            cvd += 1\n",
    "        if df.at[i, \"HF_ed\"] > 0:\n",
    "            hf += 1\n",
    "        if df.at[i, \"HTN_ed\"] > 0:\n",
    "            htn += 1\n",
    "        if df.at[i, \"DM_ed\"] > 0:\n",
    "            dm += 1\n",
    "        if df.at[i, \"SENS_ed\"] > 0:\n",
    "            sens += 1\n",
    "        if df.at[i, \"URI/PNA_ed\"] > 0:\n",
    "            uri += 1\n",
    "        if df.at[i, \"AS/COPD_ed\"] > 0:\n",
    "            copd += 1\n",
    "        if df.at[i, \"NEURO_ed\"] > 0:\n",
    "            neuro += 1\n",
    "        if df.at[i, \"COG_ed\"] > 0:\n",
    "            cog += 1\n",
    "        if df.at[i, \"SUD_ed\"] > 0:\n",
    "            sud += 1\n",
    "        if df.at[i, \"MHD_ed\"] > 0:\n",
    "            mhd += 1\n",
    "        if df.at[i, \"INF_ed\"] > 0:\n",
    "            inf += 1\n",
    "        if df.at[i, \"PAIN_ed\"] > 0:\n",
    "            pain += 1\n",
    "        if df.at[i, \"REN_ed\"] > 0:\n",
    "            ren += 1\n",
    "        if df.at[i, \"LIV_ed\"] > 0:\n",
    "            liv += 1\n",
    "        if df.at[i, \"ACC/INJ_ed\"] > 0:\n",
    "            acc += 1\n",
    "        if df.at[i, \"TOB_ed\"] > 0:\n",
    "            tob += 1\n",
    "            \n",
    "    print(\"Total # of patients: \")\n",
    "    print(num_patients)\n",
    "    print(\"Total # of \" + item + \" for these patients: \")\n",
    "    print(num_item)\n",
    "\n",
    "    print(\"Proportion with: \")\n",
    "    print(\"Cardiovascular diseases: \")\n",
    "    print(cvd/num_patients)\n",
    "    print(\"Heart failure: \")\n",
    "    print(hf/num_patients)\n",
    "    print(\"Hypertension: \")\n",
    "    print(htn/num_patients)\n",
    "    print(\"Diabetes: \")\n",
    "    print(dm/num_patients)\n",
    "    print(\"Upper Resp Inf/PNA: \")\n",
    "    print(uri/num_patients)\n",
    "    print(\"Chronic Resp/COPD: \")\n",
    "    print(copd/num_patients)\n",
    "    print(\"Sensory: \")\n",
    "    print(sens/num_patients)\n",
    "    print(\"Cognitive: \")\n",
    "    print(cog/num_patients)\n",
    "    print(\"Neurological: \")\n",
    "    print(neuro/num_patients)\n",
    "    print(\"Substance Use: \")\n",
    "    print(sud/num_patients)\n",
    "    print(\"Mental Health: \")\n",
    "    print(mhd/num_patients)\n",
    "    print(\"Infections: \")\n",
    "    print(inf/num_patients)\n",
    "    print(\"Pain: \")\n",
    "    print(pain/num_patients)\n",
    "    print(\"Renal: \")\n",
    "    print(ren/num_patients)\n",
    "    print(\"Liver, Gallbladder or Pancreatic: \")\n",
    "    print(liv/num_patients)\n",
    "    print(\"Accidents & Injuries: \")\n",
    "    print(acc/num_patients)\n",
    "    print(\"Tobacco: \")\n",
    "    print(tob/num_patients)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6e16ba70",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_op_conditions(df, item):\n",
    "    cvd = hf = htn = dm = sens = uri = copd = neuro = cog = sud = mhd = inf = pain = ren = liv = acc = ca = preg = 0\n",
    "    num_patients = 0\n",
    "    num_item = 0\n",
    "    for i in range(len(df)):\n",
    "        num_patients += 1\n",
    "        num_item += df.at[i, item]\n",
    "        if df.at[i, \"CVD_op\"] > 0:\n",
    "            cvd += 1\n",
    "        if df.at[i, \"HF_op\"] > 0:\n",
    "            hf += 1\n",
    "        if df.at[i, \"HTN_op\"] > 0:\n",
    "            htn += 1\n",
    "        if df.at[i, \"DM_op\"] > 0:\n",
    "            dm += 1\n",
    "        if df.at[i, \"SENS_op\"] > 0:\n",
    "            sens += 1\n",
    "        if df.at[i, \"URI/PNA_op\"] > 0:\n",
    "            uri += 1\n",
    "        if df.at[i, \"AS/COPD_op\"] > 0:\n",
    "            copd += 1\n",
    "        if df.at[i, \"NEURO_op\"] > 0:\n",
    "            neuro += 1\n",
    "        if df.at[i, \"COG_op\"] > 0:\n",
    "            cog += 1\n",
    "        if df.at[i, \"SUD_op\"] > 0:\n",
    "            sud += 1\n",
    "        if df.at[i, \"MHD_op\"] > 0:\n",
    "            mhd += 1\n",
    "        if df.at[i, \"INF_op\"] > 0:\n",
    "            inf += 1\n",
    "        if df.at[i, \"PAIN_op\"] > 0:\n",
    "            pain += 1\n",
    "        if df.at[i, \"REN_op\"] > 0:\n",
    "            ren += 1\n",
    "        if df.at[i, \"LIV_op\"] > 0:\n",
    "            liv += 1\n",
    "        if df.at[i, \"ACC/INJ_op\"] > 0:\n",
    "            acc += 1\n",
    "        if df.at[i, \"CA_op\"] > 0:\n",
    "            ca += 1\n",
    "        if df.at[i, \"PREG_op\"] > 0:\n",
    "            preg += 1\n",
    "            \n",
    "    print(\"Total # of patients with OP visits: \")\n",
    "    print(num_patients)\n",
    "    print(\"Total # of \" + item + \" for these patients: \")\n",
    "    print(num_item)\n",
    "\n",
    "    print(\"Proportion with: \")\n",
    "    print(\"Cardiovascular diseases: \")\n",
    "    print(cvd/num_patients)\n",
    "    print(\"Heart failure: \")\n",
    "    print(hf/num_patients)\n",
    "    print(\"Hypertension: \")\n",
    "    print(htn/num_patients)\n",
    "    print(\"Diabetes: \")\n",
    "    print(dm/num_patients)\n",
    "    print(\"Upper Resp Inf/PNA: \")\n",
    "    print(uri/num_patients)\n",
    "    print(\"Chronic Resp/COPD: \")\n",
    "    print(copd/num_patients)\n",
    "    print(\"Sensory: \")\n",
    "    print(sens/num_patients)\n",
    "    print(\"Cognitive: \")\n",
    "    print(cog/num_patients)\n",
    "    print(\"Neurological: \")\n",
    "    print(neuro/num_patients)\n",
    "    print(\"Substance Use: \")\n",
    "    print(sud/num_patients)\n",
    "    print(\"Mental Health: \")\n",
    "    print(mhd/num_patients)\n",
    "    print(\"Infections: \")\n",
    "    print(inf/num_patients)\n",
    "    print(\"Pain: \")\n",
    "    print(pain/num_patients)\n",
    "    print(\"Renal: \")\n",
    "    print(ren/num_patients)\n",
    "    print(\"Liver, Gallbladder or Pancreatic: \")\n",
    "    print(liv/num_patients)\n",
    "    print(\"Accidents & Injuries: \")\n",
    "    print(acc/num_patients)\n",
    "    print(\"Cancer: \")\n",
    "    print(ca/num_patients)\n",
    "    print(\"Pregnancy-related: \")\n",
    "    print(preg/num_patients)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cd96c81d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "14\n",
      "Total # of admitted for these patients: \n",
      "16.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.0\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.07142857142857142\n",
      "Diabetes: \n",
      "0.0\n",
      "Upper Resp Inf/PNA: \n",
      "0.2857142857142857\n",
      "Chronic Resp/COPD: \n",
      "0.07142857142857142\n",
      "Sensory: \n",
      "0.07142857142857142\n",
      "Cognitive: \n",
      "0.0\n",
      "Neurological: \n",
      "0.0\n",
      "Substance Use: \n",
      "0.2857142857142857\n",
      "Mental Health: \n",
      "0.07142857142857142\n",
      "Infections: \n",
      "0.21428571428571427\n",
      "Pain: \n",
      "0.14285714285714285\n",
      "Renal: \n",
      "0.0\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.07142857142857142\n",
      "Accidents & Injuries: \n",
      "0.14285714285714285\n",
      "Tobacco: \n",
      "0.21428571428571427\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(admitted, \"admitted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "674a0467",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "152\n",
      "Total # of ed_visit_count for these patients: \n",
      "265.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.013157894736842105\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.05263157894736842\n",
      "Diabetes: \n",
      "0.019736842105263157\n",
      "Upper Resp Inf/PNA: \n",
      "0.1513157894736842\n",
      "Chronic Resp/COPD: \n",
      "0.039473684210526314\n",
      "Sensory: \n",
      "0.046052631578947366\n",
      "Cognitive: \n",
      "0.006578947368421052\n",
      "Neurological: \n",
      "0.02631578947368421\n",
      "Substance Use: \n",
      "0.2894736842105263\n",
      "Mental Health: \n",
      "0.11842105263157894\n",
      "Infections: \n",
      "0.17763157894736842\n",
      "Pain: \n",
      "0.21710526315789475\n",
      "Renal: \n",
      "0.0\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.019736842105263157\n",
      "Accidents & Injuries: \n",
      "0.2236842105263158\n",
      "Tobacco: \n",
      "0.32894736842105265\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(ed_visits, \"ed_visit_count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "01fec672",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients with OP visits: \n",
      "1014\n",
      "Total # of op_visit_count for these patients: \n",
      "1961.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.027613412228796843\n",
      "Heart failure: \n",
      "0.0029585798816568047\n",
      "Hypertension: \n",
      "0.09861932938856016\n",
      "Diabetes: \n",
      "0.05226824457593689\n",
      "Upper Resp Inf/PNA: \n",
      "0.07593688362919132\n",
      "Chronic Resp/COPD: \n",
      "0.046351084812623275\n",
      "Sensory: \n",
      "0.03648915187376726\n",
      "Cognitive: \n",
      "0.005917159763313609\n",
      "Neurological: \n",
      "0.04437869822485207\n",
      "Substance Use: \n",
      "0.4437869822485207\n",
      "Mental Health: \n",
      "0.14792899408284024\n",
      "Infections: \n",
      "0.11143984220907298\n",
      "Pain: \n",
      "0.14398422090729784\n",
      "Renal: \n",
      "0.0029585798816568047\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.008875739644970414\n",
      "Accidents & Injuries: \n",
      "0.047337278106508875\n",
      "Cancer: \n",
      "0.006903353057199211\n",
      "Pregnancy-related: \n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "calc_op_conditions(op_visits, \"op_visit_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e2ca746",
   "metadata": {},
   "source": [
    "In this low-utilization group, 100% (1,014) had some OP / clinic visits (1,961 visits - 12% of all OP visits during the period), and 15% (152) had some ED visits (265 total visits - 7% of all ED visits during the period). A few had inpatient admissions - 14 people were admitted 16 times.\n",
    "\n",
    "#### Most Common Inpatient Diagnosis Categories, Group Zero (n=16):\n",
    "\n",
    "- Substance use, 29%\n",
    "- Upper Respiratory Infections & Pneumonia, 29%\n",
    "- Infections, 21%\n",
    "- Accidents & Injuries, 14%\n",
    "- Pain, 14%\n",
    "\n",
    "#### Most Common ED Visit Diagnosis Categories, Group Zero (n=265):\n",
    "\n",
    "- Substance use, 29%\n",
    "- Pain, 22%\n",
    "- Accidents & Injuries, 22%\n",
    "- Infections, 18%\n",
    "- Upper Respiratory Infections & Pneumonia, 15%\n",
    "- Mental health, 12%\n",
    "\n",
    "#### Most Common OP Visit Diagnosis Categories, Group Zero (n=1961):\n",
    "\n",
    "- Substance use, 44%\n",
    "- Mental health, 15%\n",
    "- Pain, 14%\n",
    "- Infections, 11%\n",
    "- Hypertension, 10%\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "81a1f768",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3178294573643411"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==1][\"ed_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "30445dab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.135658914728682"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==1][\"op_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "1df7e775",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    258.000000\n",
       "mean      60.279070\n",
       "std       13.897052\n",
       "min       24.000000\n",
       "25%       51.000000\n",
       "50%       61.500000\n",
       "75%       71.000000\n",
       "max       94.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==1][\"age\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2cc74229",
   "metadata": {},
   "outputs": [],
   "source": [
    "one = imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==1].copy()\n",
    "admitted2 = one[one[\"admitted\"]==1].copy().reset_index()\n",
    "ed_visits2 = one[one[\"ed_visit_count\"]>0].copy().reset_index()\n",
    "op_visits2 = one[one[\"op_visit_count\"]>0].copy().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "592472df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values[1], X.values, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b601ae79",
   "metadata": {},
   "source": [
    "This second group of 258 patients (11% of the sample) are higher clinic / OP visit users.  They tend to be older, have more outpatient diagnoses and few ED visits.  They go to the clinic more often (low op intervals), and to the ED less often (high ed intervals), identify as not white, and primarily non-English speaking.  They have low NIDA ascores.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "db9612f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "10\n",
      "Total # of admitted for these patients: \n",
      "10.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.4\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.4\n",
      "Diabetes: \n",
      "0.2\n",
      "Upper Resp Inf/PNA: \n",
      "0.2\n",
      "Chronic Resp/COPD: \n",
      "0.2\n",
      "Sensory: \n",
      "0.1\n",
      "Cognitive: \n",
      "0.1\n",
      "Neurological: \n",
      "0.2\n",
      "Substance Use: \n",
      "0.0\n",
      "Mental Health: \n",
      "0.0\n",
      "Infections: \n",
      "0.3\n",
      "Pain: \n",
      "0.1\n",
      "Renal: \n",
      "0.1\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.1\n",
      "Accidents & Injuries: \n",
      "0.1\n",
      "Tobacco: \n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(admitted2, \"admitted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "8b6f6254",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "52\n",
      "Total # of ed_visit_count for these patients: \n",
      "82.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.11538461538461539\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.3269230769230769\n",
      "Diabetes: \n",
      "0.17307692307692307\n",
      "Upper Resp Inf/PNA: \n",
      "0.3269230769230769\n",
      "Chronic Resp/COPD: \n",
      "0.07692307692307693\n",
      "Sensory: \n",
      "0.1346153846153846\n",
      "Cognitive: \n",
      "0.038461538461538464\n",
      "Neurological: \n",
      "0.09615384615384616\n",
      "Substance Use: \n",
      "0.0\n",
      "Mental Health: \n",
      "0.0\n",
      "Infections: \n",
      "0.15384615384615385\n",
      "Pain: \n",
      "0.4230769230769231\n",
      "Renal: \n",
      "0.019230769230769232\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.057692307692307696\n",
      "Accidents & Injuries: \n",
      "0.25\n",
      "Tobacco: \n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(ed_visits2, \"ed_visit_count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "b605df02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients with OP visits: \n",
      "258\n",
      "Total # of op_visit_count for these patients: \n",
      "2615.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.15891472868217055\n",
      "Heart failure: \n",
      "0.015503875968992248\n",
      "Hypertension: \n",
      "0.5232558139534884\n",
      "Diabetes: \n",
      "0.35271317829457366\n",
      "Upper Resp Inf/PNA: \n",
      "0.29069767441860467\n",
      "Chronic Resp/COPD: \n",
      "0.05426356589147287\n",
      "Sensory: \n",
      "0.20155038759689922\n",
      "Cognitive: \n",
      "0.08527131782945736\n",
      "Neurological: \n",
      "0.12015503875968993\n",
      "Substance Use: \n",
      "0.1434108527131783\n",
      "Mental Health: \n",
      "0.18992248062015504\n",
      "Infections: \n",
      "0.26744186046511625\n",
      "Pain: \n",
      "0.5426356589147286\n",
      "Renal: \n",
      "0.031007751937984496\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.023255813953488372\n",
      "Accidents & Injuries: \n",
      "0.12015503875968993\n",
      "Cancer: \n",
      "0.05813953488372093\n",
      "Pregnancy-related: \n",
      "0.007751937984496124\n"
     ]
    }
   ],
   "source": [
    "calc_op_conditions(op_visits2, \"op_visit_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8162b65b",
   "metadata": {},
   "source": [
    "In this group of outpatient / clinic users, 100% (258) had some clinic visits, and 20% (52) had some ED visits.  Those who went to the ED sometimes went more than once, with 52 patients accounting for 82 ED visits.  Ten patients (4%) were admitted to the hospital once after an ED visit. These 258 people had a total of 2,615 clinic visits, approximately 16% of all of the clinic visits for all of the patients for the period.\n",
    "\n",
    "#### Most Common Inpatient Diagnosis Categories, Group One (n=10):\n",
    "\n",
    "- Cardiovascular disease, Hypertension, Diabetes, Upper Respiratory Infection/ Pneumonia, Asthma/ COPD, Sensory, Cognitive, and Infections\n",
    "\n",
    "#### Most Common ED Visit Diagnosis Categories, Group One:\n",
    "\n",
    "- Pain, 42%\n",
    "- Hypertension, 33%\n",
    "- Upper Respiratory Infections & Pneumonia, 33%\n",
    "- Accidents & Injuries, 25%\n",
    "- Diabetes, 17%\n",
    "- Infections, 15%\n",
    "- Cardiovascular disease, 12%\n",
    "\n",
    "#### Most Common OP Visit Diagnosis Categories, Group One:\n",
    "\n",
    "- Pain, 54%\n",
    "- Hypertension, 52%\n",
    "- Diabetes, 35%\n",
    "- Upper Respiratory Infections & Pneumonia, 29%\n",
    "- Infections, 27%\n",
    "- Sensory impairments, 20%\n",
    "- Mental health, 19%\n",
    "- Substance use, 14%\n",
    "- Accidents & Injuries, 12%\n",
    "- Neurological disease, 12%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7a97741a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.26582278481012656"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==2][\"ed_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8358e506",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.7278481012658227"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==2][\"op_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "cfcb8b5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    158.000000\n",
       "mean      15.544304\n",
       "std       10.032174\n",
       "min        2.000000\n",
       "25%        8.000000\n",
       "50%       13.000000\n",
       "75%       21.000000\n",
       "max       48.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==2][\"age\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "23f21ddc",
   "metadata": {},
   "outputs": [],
   "source": [
    "two = imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==2].copy()\n",
    "admitted3 = two[two[\"admitted\"]==1].copy().reset_index()\n",
    "ed_visits3 = two[two[\"ed_visit_count\"]>0].copy().reset_index()\n",
    "op_visits3 = two[two[\"op_visit_count\"]>0].copy().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "bd7fb9a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "1\n",
      "Total # of admitted for these patients: \n",
      "1.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.0\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.0\n",
      "Diabetes: \n",
      "0.0\n",
      "Upper Resp Inf/PNA: \n",
      "0.0\n",
      "Chronic Resp/COPD: \n",
      "0.0\n",
      "Sensory: \n",
      "0.0\n",
      "Cognitive: \n",
      "0.0\n",
      "Neurological: \n",
      "0.0\n",
      "Substance Use: \n",
      "0.0\n",
      "Mental Health: \n",
      "0.0\n",
      "Infections: \n",
      "0.0\n",
      "Pain: \n",
      "1.0\n",
      "Renal: \n",
      "0.0\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.0\n",
      "Accidents & Injuries: \n",
      "0.0\n",
      "Tobacco: \n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(admitted3, \"admitted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a7228940",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "26\n",
      "Total # of ed_visit_count for these patients: \n",
      "42.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.038461538461538464\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.0\n",
      "Diabetes: \n",
      "0.0\n",
      "Upper Resp Inf/PNA: \n",
      "0.38461538461538464\n",
      "Chronic Resp/COPD: \n",
      "0.038461538461538464\n",
      "Sensory: \n",
      "0.07692307692307693\n",
      "Cognitive: \n",
      "0.038461538461538464\n",
      "Neurological: \n",
      "0.15384615384615385\n",
      "Substance Use: \n",
      "0.0\n",
      "Mental Health: \n",
      "0.0\n",
      "Infections: \n",
      "0.19230769230769232\n",
      "Pain: \n",
      "0.34615384615384615\n",
      "Renal: \n",
      "0.038461538461538464\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.0\n",
      "Accidents & Injuries: \n",
      "0.3076923076923077\n",
      "Tobacco: \n",
      "0.038461538461538464\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(ed_visits3, \"ed_visit_count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "56e21dc6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients with OP visits: \n",
      "158\n",
      "Total # of op_visit_count for these patients: \n",
      "431.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.006329113924050633\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.0\n",
      "Diabetes: \n",
      "0.012658227848101266\n",
      "Upper Resp Inf/PNA: \n",
      "0.17721518987341772\n",
      "Chronic Resp/COPD: \n",
      "0.0\n",
      "Sensory: \n",
      "0.006329113924050633\n",
      "Cognitive: \n",
      "0.02531645569620253\n",
      "Neurological: \n",
      "0.0189873417721519\n",
      "Substance Use: \n",
      "0.012658227848101266\n",
      "Mental Health: \n",
      "0.0379746835443038\n",
      "Infections: \n",
      "0.12025316455696203\n",
      "Pain: \n",
      "0.08860759493670886\n",
      "Renal: \n",
      "0.0\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.006329113924050633\n",
      "Accidents & Injuries: \n",
      "0.05063291139240506\n",
      "Cancer: \n",
      "0.006329113924050633\n",
      "Pregnancy-related: \n",
      "0.006329113924050633\n"
     ]
    }
   ],
   "source": [
    "calc_op_conditions(op_visits3, \"op_visit_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a4b20d5",
   "metadata": {},
   "source": [
    "In this group of outpatient / clinic users, 100% (158) had some clinic visits, and 16% (26) had some ED visits.  Those who went to the ED sometimes went more than once, with 26 patients accounting for 42 ED visits.  One patient was admitted to the hospital once after an ED visit with Pain. These 158 people had a total of 431 clinic visits, approximately 2.5% of all of the clinic visits for all of the patients for the period.\n",
    "\n",
    "#### Most Common ED Visit Diagnosis Categories, Group Two:\n",
    "\n",
    "- Upper Respiratory Infections & Pneumonia, 38%\n",
    "- Pain, 35%\n",
    "- Accidents & Injuries, 31%\n",
    "- Infections, 19%\n",
    "- Neurological disease, 15%\n",
    "\n",
    "#### Most Common OP Visit Diagnosis Categories, Group Two:\n",
    "\n",
    "- Upper Respiratory Infections & Pneumonia, 18%\n",
    "- Infections, 12%\n",
    "- Pain, 8%\n",
    "- Accidents & Injuries, 5%\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "184731ed",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values[2], X.values, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "80b88be8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "op_visits3[op_visits3[\"avg_hark\"]>=1][\"avg_hark\"].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5e82444",
   "metadata": {},
   "source": [
    "This group of 158 patients (7% of the sample) had few ED visits and inpatient admissions and low to moderate clinic use. They range in age from 2-48 years old, and the median age is 13, the 75%ile is 21. These children are not tobacco users, and have low NIDA scores.  They have low BMI, but some had higher than average blood glucose readings (mean=167) and HARK scores (52/158 or 33%) - NOTE: some of this might be imputed values, so need to look back at orig. values.  Most (109 out of 158) identified as Black / African American, and 33 identified as Asian. They did not identify English as their primary language."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e0e9a614",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.777439024390244"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==3][\"ed_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6d59ecfa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.496951219512195"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==3][\"op_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ba717bcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    328.000000\n",
       "mean      44.618902\n",
       "std       12.135998\n",
       "min       22.000000\n",
       "25%       34.000000\n",
       "50%       43.000000\n",
       "75%       55.000000\n",
       "max       86.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==3][\"age\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "cf57aeef",
   "metadata": {},
   "outputs": [],
   "source": [
    "three = imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==3].copy()\n",
    "admitted4 = three[three[\"admitted\"]==1].copy().reset_index()\n",
    "ed_visits4 = three[three[\"ed_visit_count\"]>0].copy().reset_index()\n",
    "op_visits4 = three[three[\"op_visit_count\"]>0].copy().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "44504aec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "65\n",
      "Total # of admitted for these patients: \n",
      "65.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.27692307692307694\n",
      "Heart failure: \n",
      "0.03076923076923077\n",
      "Hypertension: \n",
      "0.24615384615384617\n",
      "Diabetes: \n",
      "0.1076923076923077\n",
      "Upper Resp Inf/PNA: \n",
      "0.6153846153846154\n",
      "Chronic Resp/COPD: \n",
      "0.24615384615384617\n",
      "Sensory: \n",
      "0.38461538461538464\n",
      "Cognitive: \n",
      "0.09230769230769231\n",
      "Neurological: \n",
      "0.24615384615384617\n",
      "Substance Use: \n",
      "0.8769230769230769\n",
      "Mental Health: \n",
      "0.5538461538461539\n",
      "Infections: \n",
      "0.5692307692307692\n",
      "Pain: \n",
      "0.6307692307692307\n",
      "Renal: \n",
      "0.046153846153846156\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.13846153846153847\n",
      "Accidents & Injuries: \n",
      "0.49230769230769234\n",
      "Tobacco: \n",
      "0.7076923076923077\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(admitted4, \"admitted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "69151f5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "328\n",
      "Total # of ed_visit_count for these patients: \n",
      "2879.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.25609756097560976\n",
      "Heart failure: \n",
      "0.036585365853658534\n",
      "Hypertension: \n",
      "0.24390243902439024\n",
      "Diabetes: \n",
      "0.10365853658536585\n",
      "Upper Resp Inf/PNA: \n",
      "0.573170731707317\n",
      "Chronic Resp/COPD: \n",
      "0.3323170731707317\n",
      "Sensory: \n",
      "0.3018292682926829\n",
      "Cognitive: \n",
      "0.06707317073170732\n",
      "Neurological: \n",
      "0.25\n",
      "Substance Use: \n",
      "0.8140243902439024\n",
      "Mental Health: \n",
      "0.5030487804878049\n",
      "Infections: \n",
      "0.5579268292682927\n",
      "Pain: \n",
      "0.6646341463414634\n",
      "Renal: \n",
      "0.039634146341463415\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.10060975609756098\n",
      "Accidents & Injuries: \n",
      "0.5701219512195121\n",
      "Tobacco: \n",
      "0.7591463414634146\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(ed_visits4, \"ed_visit_count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "46cf8114",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients with OP visits: \n",
      "328\n",
      "Total # of op_visit_count for these patients: \n",
      "2131.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.0975609756097561\n",
      "Heart failure: \n",
      "0.009146341463414634\n",
      "Hypertension: \n",
      "0.1951219512195122\n",
      "Diabetes: \n",
      "0.10365853658536585\n",
      "Upper Resp Inf/PNA: \n",
      "0.22560975609756098\n",
      "Chronic Resp/COPD: \n",
      "0.1951219512195122\n",
      "Sensory: \n",
      "0.08231707317073171\n",
      "Cognitive: \n",
      "0.024390243902439025\n",
      "Neurological: \n",
      "0.10365853658536585\n",
      "Substance Use: \n",
      "0.5304878048780488\n",
      "Mental Health: \n",
      "0.2865853658536585\n",
      "Infections: \n",
      "0.3048780487804878\n",
      "Pain: \n",
      "0.25914634146341464\n",
      "Renal: \n",
      "0.009146341463414634\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.04573170731707317\n",
      "Accidents & Injuries: \n",
      "0.16463414634146342\n",
      "Cancer: \n",
      "0.024390243902439025\n",
      "Pregnancy-related: \n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "calc_op_conditions(op_visits4, \"op_visit_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "148882f5",
   "metadata": {},
   "source": [
    "In this group of heavy ED and moderate clinic users, 100% (328) had both ED and clinic visits, and 20% (65) were admitted to the hospital after an ED visit once each during the period.  These 328 people had 8.7 mean ED visits per person during the period, and 6.5 mean OP / clinic visits per person during the period.  This group had a total of 2,879 ED visits - 79% of all of the ED visits for the sample for the period (3,636), and a total of 2,131 OP / clinic visits, 13% of all of the clinic visits for the sample for the period (16,665).  The high %s of visit diagnosis categories show how sick these people are - they had a great many diagnoses concomitantly for each visit.  \n",
    "\n",
    "#### Most Common Admission Visit Diagnosis Categories, Group Three (n=65 visits):\n",
    "\n",
    "- Substance use, 88%\n",
    "- Tobacco use, 70%\n",
    "- Pain, 63%\n",
    "- Upper Respiratory Infections & Pneumonia, 62%\n",
    "- Infections, 57%\n",
    "- Mental health, 55%\n",
    "- Accidents & Injuries, 49%\n",
    "- Cardiovascular disease, 28%\n",
    "- Hypertension, COPD, and Neurological diseases, 25% each\n",
    "- Liver, gallbladder & pancreatic disease, 14%\n",
    "\n",
    "#### Most Common ED Visit Diagnosis Categories, Group Three:\n",
    "\n",
    "- Substance use, 81%\n",
    "- Tobacco, 76%\n",
    "- Pain, 66%\n",
    "- Upper Respiratory Infections & Pneumonia, 57%\n",
    "- Accidents & Injuries 57%\n",
    "- Infections, 56%\n",
    "- Mental health, 50%\n",
    "- Asthma / COPD, 33%\n",
    "- Sensory disorders, 30%\n",
    "- Cardiovascular disease, 26%\n",
    "- Hypertension, 24%\n",
    "- Diabetes and Liver, gallbladder & pancreatic disease, 10% each\n",
    "\n",
    "#### Most Common OP Visit Diagnosis Categories, Group Three:\n",
    "\n",
    "- Substance use, 53%\n",
    "- Infections, 30%\n",
    "- Mental health, 29%\n",
    "- Pain, 26%\n",
    "- Upper Respiratory Infections & Pneumonia, 23%\n",
    "- Hypertension, 20%\n",
    "- Asthma / COPD, 20%\n",
    "- Accidents & Injuries, 16%\n",
    "- Hypertension and Neurological disease, 10% each\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b358eddd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values[3], X.values, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4765e317",
   "metadata": {},
   "source": [
    "This group of 328 patients range in age from 22 to 86 with the median age 43 years and 75%ile 55 years.  They ve end to identify as white, and English-speaking, have lots of diagnoses / chronic conditions and go to the ED and clinic quite a bit.  The mean # of ED visits per person for the period for this group was 8.7.  The most frequent diagnosis category for ALL visit types was Substance use disorders.  These people are tobacco users and have higher than average NIDA scores.  They are more likely to have non-emergent diagnoses in the ED.  They account for 79% of all of the ED visits for the period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "6a695ba3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.21777777777777776"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==4][\"ed_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "24478107",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.7822222222222224"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==4][\"op_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "933bb518",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    225.000000\n",
       "mean      46.835556\n",
       "std       11.091526\n",
       "min       28.000000\n",
       "25%       37.000000\n",
       "50%       48.000000\n",
       "75%       55.000000\n",
       "max       71.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==4][\"age\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "f84956cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "four = imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==4].copy()\n",
    "admitted5 = four[four[\"admitted\"]==1].copy().reset_index()\n",
    "ed_visits5 = four[four[\"ed_visit_count\"]>0].copy().reset_index()\n",
    "op_visits5 = four[four[\"op_visit_count\"]>0].copy().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "fe8fb68a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "1\n",
      "Total # of admitted for these patients: \n",
      "1.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.0\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.0\n",
      "Diabetes: \n",
      "0.0\n",
      "Upper Resp Inf/PNA: \n",
      "0.0\n",
      "Chronic Resp/COPD: \n",
      "0.0\n",
      "Sensory: \n",
      "0.0\n",
      "Cognitive: \n",
      "0.0\n",
      "Neurological: \n",
      "0.0\n",
      "Substance Use: \n",
      "1.0\n",
      "Mental Health: \n",
      "0.0\n",
      "Infections: \n",
      "1.0\n",
      "Pain: \n",
      "0.0\n",
      "Renal: \n",
      "0.0\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.0\n",
      "Accidents & Injuries: \n",
      "0.0\n",
      "Tobacco: \n",
      "1.0\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(admitted5, \"admitted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "530bbba2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "28\n",
      "Total # of ed_visit_count for these patients: \n",
      "49.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.0\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.10714285714285714\n",
      "Diabetes: \n",
      "0.0\n",
      "Upper Resp Inf/PNA: \n",
      "0.14285714285714285\n",
      "Chronic Resp/COPD: \n",
      "0.07142857142857142\n",
      "Sensory: \n",
      "0.10714285714285714\n",
      "Cognitive: \n",
      "0.03571428571428571\n",
      "Neurological: \n",
      "0.03571428571428571\n",
      "Substance Use: \n",
      "0.21428571428571427\n",
      "Mental Health: \n",
      "0.10714285714285714\n",
      "Infections: \n",
      "0.2857142857142857\n",
      "Pain: \n",
      "0.21428571428571427\n",
      "Renal: \n",
      "0.0\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.0\n",
      "Accidents & Injuries: \n",
      "0.2857142857142857\n",
      "Tobacco: \n",
      "0.42857142857142855\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(ed_visits5, \"ed_visit_count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "3abd8232",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients with OP visits: \n",
      "225\n",
      "Total # of op_visit_count for these patients: \n",
      "626.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.04\n",
      "Heart failure: \n",
      "0.0\n",
      "Hypertension: \n",
      "0.15555555555555556\n",
      "Diabetes: \n",
      "0.07111111111111111\n",
      "Upper Resp Inf/PNA: \n",
      "0.09333333333333334\n",
      "Chronic Resp/COPD: \n",
      "0.1111111111111111\n",
      "Sensory: \n",
      "0.05333333333333334\n",
      "Cognitive: \n",
      "0.0044444444444444444\n",
      "Neurological: \n",
      "0.04\n",
      "Substance Use: \n",
      "0.35555555555555557\n",
      "Mental Health: \n",
      "0.1111111111111111\n",
      "Infections: \n",
      "0.2\n",
      "Pain: \n",
      "0.17777777777777778\n",
      "Renal: \n",
      "0.0044444444444444444\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.013333333333333334\n",
      "Accidents & Injuries: \n",
      "0.07111111111111111\n",
      "Cancer: \n",
      "0.008888888888888889\n",
      "Pregnancy-related: \n",
      "0.0044444444444444444\n"
     ]
    }
   ],
   "source": [
    "calc_op_conditions(op_visits5, \"op_visit_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bb2cc0e",
   "metadata": {},
   "source": [
    "In this group of low ED users and low - moderate clinic users, 100% (225) had some clinic visits (626), and 12% (28) had some ED visits.  Those who went to the ED sometimes went more than once, with 28 patients accounting for 49 ED visits.  1 person was admitted to the hospital once, for Substance use. These 225 people had a total of 626 clinic visits, approximately 4% of all of the clinic visits for all of the patients for the period.\n",
    "\n",
    "\n",
    "#### Most Common ED Visit Diagnosis Categories, Group Four:\n",
    "\n",
    "- Tobacco use, 43%\n",
    "- Infections, 29%\n",
    "- Accidents & Injuries, 29%\n",
    "- Substance use, 21%\n",
    "- Pain, 21%\n",
    "- Upper Respiratory Infections & Pneumonia, 14%\n",
    "\n",
    "#### Most Common OP Visit Diagnosis Categories, Group Four:\n",
    "\n",
    "- Substance use, 36%\n",
    "- Infections, 20%\n",
    "- Pain, 18%\n",
    "- Hypertension, 16%\n",
    "- Mental health, 11%\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "12888950",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values[4], X.values, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d14d2aa",
   "metadata": {},
   "source": [
    "This group of 225 people is pretty similar to those in group 0 as far as utilization.  This singles out the previously incarcerated.   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "59b210fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0673758865248226"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==5][\"ed_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "286e08b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.23758865248227"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==5][\"op_visit_count\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "984f5bc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    282.000000\n",
       "mean      55.085106\n",
       "std       11.737029\n",
       "min       18.000000\n",
       "25%       48.000000\n",
       "50%       57.000000\n",
       "75%       62.750000\n",
       "max       87.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==5][\"age\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "cc491fae",
   "metadata": {},
   "outputs": [],
   "source": [
    "five = imp_unscaled[imp_unscaled[\"UMAP_KNN\"]==5].copy()\n",
    "admitted6 = five[five[\"admitted\"]==1].copy().reset_index()\n",
    "ed_visits6 = five[five[\"ed_visit_count\"]>0].copy().reset_index()\n",
    "op_visits6 = five[five[\"op_visit_count\"]>0].copy().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "557f2e11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "15\n",
      "Total # of admitted for these patients: \n",
      "15.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.3333333333333333\n",
      "Heart failure: \n",
      "0.06666666666666667\n",
      "Hypertension: \n",
      "0.5333333333333333\n",
      "Diabetes: \n",
      "0.2\n",
      "Upper Resp Inf/PNA: \n",
      "0.6\n",
      "Chronic Resp/COPD: \n",
      "0.4666666666666667\n",
      "Sensory: \n",
      "0.0\n",
      "Cognitive: \n",
      "0.0\n",
      "Neurological: \n",
      "0.06666666666666667\n",
      "Substance Use: \n",
      "0.2\n",
      "Mental Health: \n",
      "0.2\n",
      "Infections: \n",
      "0.2\n",
      "Pain: \n",
      "0.5333333333333333\n",
      "Renal: \n",
      "0.13333333333333333\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.06666666666666667\n",
      "Accidents & Injuries: \n",
      "0.13333333333333333\n",
      "Tobacco: \n",
      "0.2\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(admitted6, \"admitted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "6f1f2e5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients: \n",
      "134\n",
      "Total # of ed_visit_count for these patients: \n",
      "301.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.16417910447761194\n",
      "Heart failure: \n",
      "0.014925373134328358\n",
      "Hypertension: \n",
      "0.41044776119402987\n",
      "Diabetes: \n",
      "0.17164179104477612\n",
      "Upper Resp Inf/PNA: \n",
      "0.34328358208955223\n",
      "Chronic Resp/COPD: \n",
      "0.208955223880597\n",
      "Sensory: \n",
      "0.11194029850746269\n",
      "Cognitive: \n",
      "0.029850746268656716\n",
      "Neurological: \n",
      "0.06716417910447761\n",
      "Substance Use: \n",
      "0.26865671641791045\n",
      "Mental Health: \n",
      "0.17164179104477612\n",
      "Infections: \n",
      "0.23134328358208955\n",
      "Pain: \n",
      "0.48507462686567165\n",
      "Renal: \n",
      "0.03731343283582089\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.029850746268656716\n",
      "Accidents & Injuries: \n",
      "0.27611940298507465\n",
      "Tobacco: \n",
      "0.4253731343283582\n"
     ]
    }
   ],
   "source": [
    "calc_ed_conditions(ed_visits6, \"ed_visit_count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "669cac90",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total # of patients with OP visits: \n",
      "282\n",
      "Total # of op_visit_count for these patients: \n",
      "4297.0\n",
      "Proportion with: \n",
      "Cardiovascular diseases: \n",
      "0.24113475177304963\n",
      "Heart failure: \n",
      "0.010638297872340425\n",
      "Hypertension: \n",
      "0.549645390070922\n",
      "Diabetes: \n",
      "0.35106382978723405\n",
      "Upper Resp Inf/PNA: \n",
      "0.3971631205673759\n",
      "Chronic Resp/COPD: \n",
      "0.29432624113475175\n",
      "Sensory: \n",
      "0.2624113475177305\n",
      "Cognitive: \n",
      "0.028368794326241134\n",
      "Neurological: \n",
      "0.13829787234042554\n",
      "Substance Use: \n",
      "0.4397163120567376\n",
      "Mental Health: \n",
      "0.3404255319148936\n",
      "Infections: \n",
      "0.32978723404255317\n",
      "Pain: \n",
      "0.49645390070921985\n",
      "Renal: \n",
      "0.06028368794326241\n",
      "Liver, Gallbladder or Pancreatic: \n",
      "0.06028368794326241\n",
      "Accidents & Injuries: \n",
      "0.22340425531914893\n",
      "Cancer: \n",
      "0.08156028368794327\n",
      "Pregnancy-related: \n",
      "0.0070921985815602835\n"
     ]
    }
   ],
   "source": [
    "calc_op_conditions(op_visits6, \"op_visit_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8515dc9d",
   "metadata": {},
   "source": [
    "In this group of low ED users and high clinic users, 100% (282) had some clinic visits (4,297), and 48% (134) had some ED visits (301). 15 people were admitted to the hospital once each during the period. These 282 people had a total of 4,297 clinic visits, approximately 26% of all of the clinic visits for all of the patients for the period.\n",
    "\n",
    "#### Most Common Admission Visit Diagnosis Categories, Group Five:\n",
    "\n",
    "- Hypertension, 53%\n",
    "- Pain, 53%\n",
    "- Asthma & COPD, 47%\n",
    "- Cardiovascular disease, 33%\n",
    "- Substance use, 20%\n",
    "- Mental health, 20%\n",
    "- Diabetes, 20%\n",
    "- Tobacco, 20%\n",
    "- Infections, 20%\n",
    "- Renal, 13%\n",
    "\n",
    "#### Most Common ED Visit Diagnosis Categories, Group Five:\n",
    "\n",
    "- Pain, 49%\n",
    "- Tobacco use, 43%\n",
    "- Hypertension, 41%\n",
    "- Upper Respiratory Infections & Pneumonia, 34%\n",
    "- Accidents & Injuries, 28%\n",
    "- Substance use, 27%\n",
    "- Infections, 23%\n",
    "- Mental health, 17%\n",
    "- Diabetes, 17%\n",
    "- Cardiovascular disease, 16%\n",
    "\n",
    "#### Most Common OP Visit Diagnosis Categories, Group Five:\n",
    "\n",
    "- Hypertension, 55%\n",
    "- Infections, 50%\n",
    "- Substance use, 44%\n",
    "- Upper Respiratory Infections & Pneumonia, 40%\n",
    "- Diabetes, 35%\n",
    "- Mental health, 34%\n",
    "- Infections, 33%\n",
    "- Asthma / COPD, 29%\n",
    "- Sensory, 26%\n",
    "- Cardiovascular disease, 24%\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "321e66d1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.summary_plot(shap_values[5], X.values, feature_names = X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "73d31f8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    102\n",
       "4.0     78\n",
       "3.0     46\n",
       "1.0     37\n",
       "2.0     19\n",
       "Name: housing 2, dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "op_visits6[\"housing 2\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "777a44e7",
   "metadata": {},
   "source": [
    "This group of 282 patients is similar to some of the other clusters in certain ways, but it seems that because they have certain chronic conditions - Asthma / COPD and Hypertension - they get seen OP more frequently.  This may actually decrease their ED visit numbers, because these people also have multiple comorbidities, like the people in Group 3, but they go to the clinic more often and to the ED far less often."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "535fbffc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}