{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd, numpy as np\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline \n",
    "from catboost import *\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import metrics\n",
    "from sklearn.model_selection import train_test_split\n",
    "import shap\n",
    "from time import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# ! pip install plotly "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(32561, 15)\n"
     ]
    }
   ],
   "source": [
    "header = [\"age\",\n",
    "\"workclass\",\n",
    "\"fnlwgt\",\n",
    "\"education\",\n",
    "\"education-num\",\n",
    "\"marital-status\",\"occupation\",\"relationship\",\"race\",\n",
    "\"sex\",\"capital-gain\",\"capital-loss\",\"hours-per-week\",\n",
    "\"native-country\",\n",
    "\"income\"]\n",
    "\n",
    "train = pd.read_csv(\"adult_data\", names = header, index_col=False)\n",
    "\n",
    "print(train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>education</th>\n",
       "      <th>education-num</th>\n",
       "      <th>marital-status</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>capital-gain</th>\n",
       "      <th>capital-loss</th>\n",
       "      <th>hours-per-week</th>\n",
       "      <th>native-country</th>\n",
       "      <th>income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>77516</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>83311</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>215646</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age          workclass  fnlwgt   education  education-num  \\\n",
       "0   39          State-gov   77516   Bachelors             13   \n",
       "1   50   Self-emp-not-inc   83311   Bachelors             13   \n",
       "2   38            Private  215646     HS-grad              9   \n",
       "\n",
       "        marital-status          occupation    relationship    race    sex  \\\n",
       "0        Never-married        Adm-clerical   Not-in-family   White   Male   \n",
       "1   Married-civ-spouse     Exec-managerial         Husband   White   Male   \n",
       "2             Divorced   Handlers-cleaners   Not-in-family   White   Male   \n",
       "\n",
       "   capital-gain  capital-loss  hours-per-week  native-country  income  \n",
       "0          2174             0              40   United-States   <=50K  \n",
       "1             0             0              13   United-States   <=50K  \n",
       "2             0             0              40   United-States   <=50K  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32561, 15)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"income\"] = train[\"income\"].apply(lambda x: 0 if x == \" <=50K\" else 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def log_loss(m, X, y): \n",
    "    return metrics.log_loss(y,m.predict_proba(X)[:,1])\n",
    "    \n",
    "def permutation_importances(model, X, y, metric):\n",
    "    baseline = metric(model, X, y)\n",
    "    imp = []\n",
    "    for col in X.columns:\n",
    "        save = X[col].copy()\n",
    "        X[col] = np.random.permutation(X[col])\n",
    "        m = metric(model, X, y)\n",
    "        X[col] = save\n",
    "        imp.append(m-baseline)\n",
    "    return np.array(imp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def baseline_importance(model, X, y, X_test, y_test, metric):\n",
    "    \n",
    "    model = CatBoostClassifier(one_hot_max_size = 10, iterations = 500)\n",
    "    model.fit(X, y, cat_features = categorical_features_indices, verbose = False)\n",
    "    baseline = metric(model, X_test, y_test)\n",
    "    \n",
    "    imp = []\n",
    "    for col in X.columns:\n",
    "        \n",
    "        save = X[col].copy()\n",
    "        X[col] = np.random.permutation(X[col])\n",
    "        \n",
    "        model.fit(X, y, cat_features = categorical_features_indices, verbose = False)\n",
    "        m = metric(model, X_test, y_test)\n",
    "        X[col] = save\n",
    "        imp.append(m-baseline)\n",
    "    return np.array(imp)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training Standard Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(train.drop(\"income\", axis = 1), train[\"income\"], \\\n",
    "                                                    train_size=0.7, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "categorical_features_indices = [1, 3, 5, 6, 7, 8, 9, 13]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "age 73\n",
      "workclass 9\n",
      "fnlwgt 16640\n",
      "education 16\n",
      "education-num 16\n",
      "marital-status 7\n",
      "occupation 15\n",
      "relationship 6\n",
      "race 5\n",
      "sex 2\n",
      "capital-gain 116\n",
      "capital-loss 88\n",
      "hours-per-week 93\n",
      "native-country 41\n"
     ]
    }
   ],
   "source": [
    "for col in X_train.columns:\n",
    "    print(col, X_train[col].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50\n",
      "100\n",
      "150\n",
      "200\n",
      "250\n",
      "300\n",
      "350\n",
      "400\n",
      "450\n",
      "500\n",
      "550\n",
      "600\n",
      "650\n",
      "700\n",
      "750\n",
      "800\n"
     ]
    }
   ],
   "source": [
    "iteration = [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800]\n",
    "loss = []\n",
    "for i in iteration:\n",
    "    model = CatBoostClassifier(one_hot_max_size = 10, iterations = i)\n",
    "    model.fit(\n",
    "    X_train, y_train,\n",
    "    cat_features = categorical_features_indices,\n",
    "    verbose = False\n",
    "    )\n",
    "    loss.append((i, log_loss(model, X_test, y_test), log_loss(model, X_train, y_train)))\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([i[0] for i in loss],[i[1] for i in loss]) \n",
    "plt.plot([i[0] for i in loss],[i[2] for i in loss]) \n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<catboost.core.CatBoostClassifier at 0x1c283ca0b8>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = CatBoostClassifier(one_hot_max_size = 10, iterations = 500)\n",
    "model.fit(\n",
    "    X_train, y_train,\n",
    "    cat_features = categorical_features_indices,\n",
    "    verbose = False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model.get_feature_importance??"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Shap Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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r={topAbort:null,topAnimationEnd:null,topAnimationIteration:null,topAnimationStart:null,topBlur:null,topCanPlay:null,topCanPlayThrough:null,topChange:null,topClick:null,topCompositionEnd:null,topCompositionStart:null,topCompositionUpdate:null,topContextMenu:null,topCopy:null,topCut:null,topDoubleClick:null,topDrag:null,topDragEnd:null,topDragEnter:null,topDragExit:null,topDragLeave:null,topDragOver:null,topDragStart:null,topDrop:null,topDurationChange:null,topEmptied:null,topEncrypted:null,topEnded:null,topError:null,topFocus:null,topInput:null,topInvalid:null,topKeyDown:null,topKeyPress:null,topKeyUp:null,topLoad:null,topLoadedData:null,topLoadedMetadata:null,topLoadStart:null,topMouseDown:null,topMouseMove:null,topMouseOut:null,topMouseOver:null,topMouseUp:null,topPaste:null,topPause:null,topPlay:null,topPlaying:null,topProgress:null,topRateChange:null,topReset:null,topScroll:null,topSeeked:null,topSeeking:null,topSelectionChange:null,topStalled:null,topSubmit:null,topSuspend:null,topTextInput:null,topTimeUpdate:null,topTouchCancel:null,topTouchEnd:null,topTouchMove:null,topTouchStart:null,topTransitionEnd:null,topVolumeChange:null,topWaiting:null,topWheel:null},i={topLevelTypes:r};t.exports=i},function(t,e,n){\"use 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RegExp(\"^(data|aria)-[\"+r.ATTRIBUTE_NAME_CHAR+\"]*$\")),Properties:{accept:0,acceptCharset:0,accessKey:0,action:0,allowFullScreen:o,allowTransparency:0,alt:0,as:0,async:o,autoComplete:0,autoPlay:o,capture:o,cellPadding:0,cellSpacing:0,charSet:0,challenge:0,checked:i|o,cite:0,classID:0,className:0,cols:u,colSpan:0,content:0,contentEditable:0,contextMenu:0,controls:o,controlsList:0,coords:0,crossOrigin:0,data:0,dateTime:0,default:o,defer:o,dir:0,disabled:o,download:c,draggable:0,encType:0,form:0,formAction:0,formEncType:0,formMethod:0,formNoValidate:o,formTarget:0,frameBorder:0,headers:0,height:0,hidden:o,high:0,href:0,hrefLang:0,htmlFor:0,httpEquiv:0,icon:0,id:0,inputMode:0,integrity:0,is:0,keyParams:0,keyType:0,kind:0,label:0,lang:0,list:0,loop:o,low:0,manifest:0,marginHeight:0,marginWidth:0,max:0,maxLength:0,media:0,mediaGroup:0,method:0,min:0,minLength:0,multiple:i|o,muted:i|o,name:0,nonce:0,noValidate:o,open:o,optimum:0,pattern:0,placeholder:0,playsInline:o,poster:0,preload:0,profile:0,radioGroup:0,readOnly:o,referrerPolicy:0,rel:0,required:o,reversed:o,role:0,rows:u,rowSpan:a,sandbox:0,scope:0,scoped:o,scrolling:0,seamless:o,selected:i|o,shape:0,size:u,sizes:0,span:u,spellCheck:0,src:0,srcDoc:0,srcLang:0,srcSet:0,start:a,step:0,style:0,summary:0,tabIndex:0,target:0,title:0,type:0,useMap:0,value:0,width:0,wmode:0,wrap:0,about:0,datatype:0,inlist:0,prefix:0,property:0,resource:0,typeof:0,vocab:0,autoCapitalize:0,autoCorrect:0,autoSave:0,color:0,itemProp:0,itemScope:o,itemType:0,itemID:0,itemRef:0,results:0,security:0,unselectable:0},DOMAttributeNames:{acceptCharset:\"accept-charset\",className:\"class\",htmlFor:\"for\",httpEquiv:\"http-equiv\"},DOMPropertyNames:{},DOMMutationMethods:{value:function(t,e){if(null==e)return t.removeAttribute(\"value\");\"number\"!==t.type||!1===t.hasAttribute(\"value\")?t.setAttribute(\"value\",\"\"+e):t.validity&&!t.validity.badInput&&t.ownerDocument.activeElement!==t&&t.setAttribute(\"value\",\"\"+e)}}};t.exports=s},function(t,e,n){\"use strict\";(function(e){function r(t,e,n,r){var i=void 0===t[n];null!=e&&i&&(t[n]=o(e,!0))}var i=n(24),o=n(174),a=(n(85),n(96)),u=n(177);n(2);void 0!==e&&e.env;var c={instantiateChildren:function(t,e,n,i){if(null==t)return null;var o={};return u(t,r,o),o},updateChildren:function(t,e,n,r,u,c,s,l,f){if(e||t){var p,h;for(p in e)if(e.hasOwnProperty(p)){h=t&&t[p];var d=h&&h._currentElement,v=e[p];if(null!=h&&a(d,v))i.receiveComponent(h,v,u,l),e[p]=h;else{h&&(r[p]=i.getHostNode(h),i.unmountComponent(h,!1));var g=o(v,!0);e[p]=g;var m=i.mountComponent(g,u,c,s,l,f);n.push(m)}}for(p in t)!t.hasOwnProperty(p)||e&&e.hasOwnProperty(p)||(h=t[p],r[p]=i.getHostNode(h),i.unmountComponent(h,!1))}},unmountChildren:function(t,e){for(var n in t)if(t.hasOwnProperty(n)){var r=t[n];i.unmountComponent(r,e)}}};t.exports=c}).call(e,n(156))},function(t,e,n){\"use strict\";var r=n(82),i=n(364),o={processChildrenUpdates:i.dangerouslyProcessChildrenUpdates,replaceNodeWithMarkup:r.dangerouslyReplaceNodeWithMarkup};t.exports=o},function(t,e,n){\"use strict\";function r(t){}function i(t){return!(!t.prototype||!t.prototype.isReactComponent)}function o(t){return!(!t.prototype||!t.prototype.isPureReactComponent)}var a=n(1),u=n(3),c=n(26),s=n(87),l=n(15),f=n(88),p=n(39),h=(n(9),n(168)),d=n(24),v=n(51),g=(n(0),n(81)),m=n(96),y=(n(2),{ImpureClass:0,PureClass:1,StatelessFunctional:2});r.prototype.render=function(){var t=p.get(this)._currentElement.type,e=t(this.props,this.context,this.updater);return e};var _=1,b={construct:function(t){this._currentElement=t,this._rootNodeID=0,this._compositeType=null,this._instance=null,this._hostParent=null,this._hostContainerInfo=null,this._updateBatchNumber=null,this._pendingElement=null,this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1,this._renderedNodeType=null,this._renderedComponent=null,this._context=null,this._mountOrder=0,this._topLevelWrapper=null,this._pendingCallbacks=null,this._calledComponentWillUnmount=!1},mountComponent:function(t,e,n,u){this._context=u,this._mountOrder=_++,this._hostParent=e,this._hostContainerInfo=n;var s,l=this._currentElement.props,f=this._processContext(u),h=this._currentElement.type,d=t.getUpdateQueue(),g=i(h),m=this._constructComponent(g,l,f,d);g||null!=m&&null!=m.render?o(h)?this._compositeType=y.PureClass:this._compositeType=y.ImpureClass:(s=m,null===m||!1===m||c.isValidElement(m)||a(\"105\",h.displayName||h.name||\"Component\"),m=new r(h),this._compositeType=y.StatelessFunctional);m.props=l,m.context=f,m.refs=v,m.updater=d,this._instance=m,p.set(m,this);var b=m.state;void 0===b&&(m.state=b=null),(\"object\"!=typeof b||Array.isArray(b))&&a(\"106\",this.getName()||\"ReactCompositeComponent\"),this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1;var x;return x=m.unstable_handleError?this.performInitialMountWithErrorHandling(s,e,n,t,u):this.performInitialMount(s,e,n,t,u),m.componentDidMount&&t.getReactMountReady().enqueue(m.componentDidMount,m),x},_constructComponent:function(t,e,n,r){return this._constructComponentWithoutOwner(t,e,n,r)},_constructComponentWithoutOwner:function(t,e,n,r){var i=this._currentElement.type;return t?new i(e,n,r):i(e,n,r)},performInitialMountWithErrorHandling:function(t,e,n,r,i){var o,a=r.checkpoint();try{o=this.performInitialMount(t,e,n,r,i)}catch(u){r.rollback(a),this._instance.unstable_handleError(u),this._pendingStateQueue&&(this._instance.state=this._processPendingState(this._instance.props,this._instance.context)),a=r.checkpoint(),this._renderedComponent.unmountComponent(!0),r.rollback(a),o=this.performInitialMount(t,e,n,r,i)}return o},performInitialMount:function(t,e,n,r,i){var o=this._instance,a=0;o.componentWillMount&&(o.componentWillMount(),this._pendingStateQueue&&(o.state=this._processPendingState(o.props,o.context))),void 0===t&&(t=this._renderValidatedComponent());var u=h.getType(t);this._renderedNodeType=u;var c=this._instantiateReactComponent(t,u!==h.EMPTY);this._renderedComponent=c;var s=d.mountComponent(c,r,e,n,this._processChildContext(i),a);return s},getHostNode:function(){return d.getHostNode(this._renderedComponent)},unmountComponent:function(t){if(this._renderedComponent){var e=this._instance;if(e.componentWillUnmount&&!e._calledComponentWillUnmount)if(e._calledComponentWillUnmount=!0,t){var n=this.getName()+\".componentWillUnmount()\";f.invokeGuardedCallback(n,e.componentWillUnmount.bind(e))}else e.componentWillUnmount();this._renderedComponent&&(d.unmountComponent(this._renderedComponent,t),this._renderedNodeType=null,this._renderedComponent=null,this._instance=null),this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1,this._pendingCallbacks=null,this._pendingElement=null,this._context=null,this._rootNodeID=0,this._topLevelWrapper=null,p.remove(e)}},_maskContext:function(t){var e=this._currentElement.type,n=e.contextTypes;if(!n)return v;var r={};for(var i in n)r[i]=t[i];return r},_processContext:function(t){var e=this._maskContext(t);return e},_processChildContext:function(t){var e,n=this._currentElement.type,r=this._instance;if(r.getChildContext&&(e=r.getChildContext()),e){\"object\"!=typeof n.childContextTypes&&a(\"107\",this.getName()||\"ReactCompositeComponent\");for(var i in e)i in n.childContextTypes||a(\"108\",this.getName()||\"ReactCompositeComponent\",i);return u({},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?d.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&&a(\"136\",this.getName()||\"ReactCompositeComponent\");var u,c=!1;this._context===i?u=o.context:(u=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,u);var f=this._processPendingState(l,u),p=!0;this._pendingForceUpdate||(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,u):this._compositeType===y.PureClass&&(p=!g(s,l)||!g(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,u,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=u)},_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=u({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var c=r[a];u(o,\"function\"==typeof c?c.call(n,o,t,e):c)}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(m(r,i))d.receiveComponent(n,i,t,this._processChildContext(e));else{var a=d.getHostNode(n);d.unmountComponent(n,!1);var u=h.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==h.EMPTY);this._renderedComponent=c;var s=d.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){s.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t=this._instance;return t.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==y.StatelessFunctional){l.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{l.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t||!1===t||c.isValidElement(t)||a(\"109\",this.getName()||\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n&&a(\"110\");var r=e.getPublicInstance();(n.refs===v?n.refs={}:n.refs)[t]=r},detachRef:function(t){delete this.getPublicInstance().refs[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===y.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=b},function(t,e,n){\"use strict\";var r=n(4),i=n(372),o=n(167),a=n(24),u=n(12),c=n(385),s=n(401),l=n(171),f=n(408);n(2);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&&($[t._tag]&&(null!=e.children||null!=e.dangerouslySetInnerHTML)&&g(\"137\",t._tag,t._currentElement._owner?\" Check the render method of 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Y)Y.hasOwnProperty(n)&&t._wrapperState.listeners.push(M.trapBubbledEvent(n,Y[n],e));break;case\"source\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topError\",\"error\",e),M.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topReset\",\"reset\",e),M.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[M.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function p(){P.postUpdateWrapper(this)}function h(t){Z.call(Q,t)||(X.test(t)||g(\"65\",t),Q[t]=!0)}function d(t,e){return t.indexOf(\"-\")>=0||null!=e.is}function v(t){var e=t.type;h(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 g=n(1),m=n(3),y=n(346),_=n(348),b=n(20),x=n(83),w=n(21),C=n(160),k=n(22),E=n(84),M=n(53),T=n(161),S=n(4),N=n(365),A=n(366),P=n(162),O=n(369),I=(n(9),n(378)),D=n(383),R=(n(11),n(56)),L=(n(0),n(95),n(81),n(173)),U=(n(97),n(2),T),F=k.deleteListener,j=S.getNodeFromInstance,B=M.listenTo,V=E.registrationNameModules,W={string:!0,number:!0},z=\"__html\",H={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},q=11,Y={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\"},K={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},G={listing:!0,pre:!0,textarea:!0},$=m({menuitem:!0},K),X=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]*$/,Q={},Z={}.hasOwnProperty,J=1;v.displayName=\"ReactDOMComponent\",v.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=J++,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(f,this);break;case\"input\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this),t.getReactMountReady().enqueue(f,this);break;case\"option\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o);break;case\"select\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o),t.getReactMountReady().enqueue(f,this);break;case\"textarea\":O.mountWrapper(this,o,e),o=O.getHostProps(this,o),t.getReactMountReady().enqueue(l,this),t.getReactMountReady().enqueue(f,this)}i(this,o);var a,p;null!=e?(a=e._namespaceURI,p=e._tag):n._tag&&(a=n._namespaceURI,p=n._tag),(null==a||a===x.svg&&\"foreignobject\"===p)&&(a=x.html),a===x.html&&(\"svg\"===this._tag?a=x.svg:\"math\"===this._tag&&(a=x.mathml)),this._namespaceURI=a;var h;if(t.useCreateElement){var d,v=n._ownerDocument;if(a===x.html)if(\"script\"===this._tag){var g=v.createElement(\"div\"),m=this._currentElement.type;g.innerHTML=\"<\"+m+\"></\"+m+\">\",d=g.removeChild(g.firstChild)}else d=o.is?v.createElement(this._currentElement.type,o.is):v.createElement(this._currentElement.type);else d=v.createElementNS(a,this._currentElement.type);S.precacheNode(this,d),this._flags|=U.hasCachedChildNodes,this._hostParent||C.setAttributeForRoot(d),this._updateDOMProperties(null,o,t);var _=b(d);this._createInitialChildren(t,o,r,_),h=_}else{var w=this._createOpenTagMarkupAndPutListeners(t,o),k=this._createContentMarkup(t,o,r);h=!k&&K[this._tag]?w+\"/>\":w+\">\"+k+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(y.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(y.focusDOMComponent,this);break;case\"select\":case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(y.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return h},_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(V.hasOwnProperty(r))i&&o(this,r,i,t);else{\"style\"===r&&(i&&(i=this._previousStyleCopy=m({},e.style)),i=_.createMarkupForStyles(i,this));var a=null;null!=this._tag&&d(this._tag,e)?H.hasOwnProperty(r)||(a=C.createMarkupForCustomAttribute(r,i)):a=C.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent||(n+=\" \"+C.createMarkupForRoot()),n+=\" \"+C.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=W[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=R(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return G[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&&b.queueHTML(r,i.__html);else{var o=W[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&b.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)b.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=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"option\":o=A.getHostProps(this,o),a=A.getHostProps(this,a);break;case\"select\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"textarea\":o=O.getHostProps(this,o),a=O.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":N.updateWrapper(this),L.updateValueIfChanged(this);break;case\"textarea\":O.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(p,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(\"style\"===r){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a||{},a[i]=\"\");this._previousStyleCopy=null}else V.hasOwnProperty(r)?t[r]&&F(this,r):d(this._tag,t)?H.hasOwnProperty(r)||C.deleteValueForAttribute(j(this),r):(w.properties[r]||w.isCustomAttribute(r))&&C.deleteValueForProperty(j(this),r);for(r in e){var c=e[r],s=\"style\"===r?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c||null!=s))if(\"style\"===r)if(c?c=this._previousStyleCopy=m({},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(V.hasOwnProperty(r))c?o(this,r,c,n):s&&F(this,r);else if(d(this._tag,e))H.hasOwnProperty(r)||C.setValueForAttribute(j(this),r,c);else if(w.properties[r]||w.isCustomAttribute(r)){var l=j(this);null!=c?C.setValueForProperty(l,r,c):C.deleteValueForProperty(l,r)}}a&&_.setValueForStyles(j(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=W[typeof t.children]?t.children:null,o=W[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 j(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\"input\":case\"textarea\":L.stopTracking(this);break;case\"html\":case\"head\":case\"body\":g(\"66\",this._tag)}this.unmountChildren(t),S.uncacheNode(this),k.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return j(this)}},m(v.prototype,v.Mixin,I.Mixin),t.exports=v},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(97),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+\" 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c=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<c.length;p++){var h=c[p];if(h!==o&&h.form===o.form){var d=l.getInstanceFromNode(h);d||a(\"90\"),f.asap(r,d)}}}return n}var a=n(1),u=n(3),c=n(160),s=n(86),l=n(4),f=n(12),p=(n(0),n(2),{getHostProps:function(t,e){var n=s.getValue(e),r=s.getChecked(e);return u({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})},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:o.bind(t),controlled:i(e)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&c.setValueForProperty(l.getNodeFromInstance(t),\"checked\",n||!1);var r=l.getNodeFromInstance(t),i=s.getValue(e);if(null!=i)if(0===i&&\"\"===r.value)r.value=\"0\";else if(\"number\"===e.type){var o=parseFloat(r.value,10)||0;(i!=o||i==o&&r.value!=i)&&(r.value=\"\"+i)}else r.value!==\"\"+i&&(r.value=\"\"+i);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=l.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=p},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(162),c=(n(2),!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){a.getNodeFromInstance(t).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;return{start:o,end:o+r}}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(405),l=n(172),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(1),i=n(3),o=n(82),a=n(20),u=n(4),c=n(56),s=(n(0),n(97),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+\" \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var s=n._ownerDocument,l=s.createComment(o),f=s.createComment(\" /react-text \"),p=a(s.createDocumentFragment());return a.queueChild(p,a(l)),this._stringText&&a.queueChild(p,a(s.createTextNode(this._stringText))),a.queueChild(p,a(f)),u.precacheNode(this,l),this._closingComment=f,p}var h=c(this._stringText);return t.renderToStaticMarkup?h:\"\\x3c!--\"+o+\"--\\x3e\"+h+\"\\x3c!-- /react-text --\\x3e\"},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),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(1),a=n(3),u=n(86),c=n(4),s=n(12),l=(n(0),n(2),{getHostProps:function(t,e){return null!=e.dangerouslySetInnerHTML&&o(\"91\"),a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange})},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\"),Array.isArray(c)&&(c.length<=1||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===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t||c(\"33\"),\"_hostNode\"in e||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 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i=n(345),o=n(347),a=n(349),u=n(351),c=n(352),s=n(355),l=n(357),f=n(360),p=n(4),h=n(362),d=n(370),v=n(368),g=n(371),m=n(375),y=n(376),_=n(381),b=n(386),x=n(387),w=n(388),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof Symbol&&Symbol.for&&Symbol.for(\"react.element\")||60103;t.exports=r},function(t,e,n){\"use strict\";function r(t){i.enqueueEvents(t),i.processEventQueue(!1)}var i=n(22),o={handleTopLevel:function(t,e,n,o){r(i.extractEvents(t,e,n,o))}};t.exports=o},function(t,e,n){\"use strict\";function r(t){for(;t._hostParent;)t=t._hostParent;var e=f.getNodeFromInstance(t),n=e.parentNode;return f.getClosestInstanceFromNode(n)}function i(t,e){this.topLevelType=t,this.nativeEvent=e,this.ancestors=[]}function o(t){var e=h(t.nativeEvent),n=f.getClosestInstanceFromNode(e),i=n;do{t.ancestors.push(i),i=i&&r(i)}while(i);for(var o=0;o<t.ancestors.length;o++)n=t.ancestors[o],v._handleTopLevel(t.topLevelType,n,t.nativeEvent,h(t.nativeEvent))}function 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       "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
       "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
       "  user you must also trust this notebook (File -> Trust notebook). If you are viewing\n",
       "  this notebook on github the Javascript has been stripped for security. If you are using\n",
       "  JupyterLab this error is because a JupyterLab extension has not yet been written.\n",
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       "   if (window.SHAP) SHAP.ReactDom.render(\n",
       "    SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"output value\"], \"baseValue\": -2.3759839875515256, \"outValue\": -0.31255189477495193, \"link\": \"identity\", \"featureNames\": [\"age\", \"workclass\", \"fnlwgt\", \"education\", \"education-num\", \"marital-status\", \"occupation\", \"relationship\", \"race\", \"sex\", \"capital-gain\", \"capital-loss\", \"hours-per-week\", \"native-country\"], \"features\": {\"0\": {\"effect\": 0.1409365489559666, \"value\": 33.0}, \"1\": {\"effect\": 0.04534379397588993, \"value\": \" Private\"}, \"2\": {\"effect\": 0.2831523014103928, \"value\": 511517.0}, \"3\": {\"effect\": -0.15609021572885212, \"value\": \" HS-grad\"}, \"4\": {\"effect\": -0.21049050035744407, \"value\": 9.0}, \"5\": {\"effect\": 1.3594787648843762, \"value\": \" Married-civ-spouse\"}, \"6\": {\"effect\": 0.7251545549548793, \"value\": \" Prof-specialty\"}, \"7\": {\"effect\": 0.1383010742673121, \"value\": \" Husband\"}, \"8\": {\"effect\": 0.03404246254758132, \"value\": \" White\"}, \"9\": {\"effect\": 0.06926627579686319, \"value\": \" Male\"}, \"10\": {\"effect\": -0.3211008146241599, \"value\": 0.0}, \"11\": {\"effect\": -0.06445113540230059, \"value\": 0.0}, \"12\": {\"effect\": -0.0011135821744897847, \"value\": 40.0}, \"13\": {\"effect\": 0.021002564270557876, \"value\": \" United-States\"}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n",
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   ],
   "source": [
    "shap_values = model.get_feature_importance(Pool(X_test, label=y_test,cat_features=categorical_features_indices), \n",
    "                                                                     type=\"ShapValues\")\n",
    "expected_value = shap_values[0,-1]\n",
    "shap_values = shap_values[:,:-1]\n",
    "\n",
    "shap.initjs()\n",
    "shap.force_plot(expected_value, shap_values[3,:], X_test.iloc[3,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x511.2 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "shap_values = model.get_feature_importance(Pool(X_test, label=y_test,cat_features=categorical_features_indices), \n",
    "                                                                     type=\"ShapValues\")\n",
    "shap_values = shap_values[:,:-1]\n",
    "\n",
    "shap.summary_plot(shap_values, X_test) \n",
    "elapsed = time.time() - start_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.246151924133301"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elapsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "770830.962590046"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "timeit.default_timer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_feature_imp_plot(method):\n",
    "    \n",
    "    if method == \"Permutation\":\n",
    "        fi =  permutation_importances(model, X_test, y_test, log_loss)\n",
    "    \n",
    "    elif method == \"Baseline\":\n",
    "        fi = baseline_importance(model, X_train, y_train, X_test, y_test, log_loss)\n",
    "    \n",
    "    elif method == \"ShapeValues\":\n",
    "        shap_values = model.get_feature_importance(Pool(X_test, label=y_test,cat_features=categorical_features_indices), \n",
    "                                                                     type=\"ShapValues\")\n",
    "        shap_values = shap_values[:,:-1]\n",
    "        shap.summary_plot(shap_values, X_test) \n",
    "        \n",
    "    else:\n",
    "        fi = model.get_feature_importance(Pool(X_test, label=y_test,cat_features=categorical_features_indices), \n",
    "                                                                     type=method)\n",
    "        \n",
    "    if method != \"ShapeValues\":\n",
    "        feature_score = pd.DataFrame(list(zip(X_test.dtypes.index, fi )),\n",
    "                                        columns=['Feature','Score'])\n",
    "\n",
    "        feature_score = feature_score.sort_values(by='Score', ascending=False, inplace=False, kind='quicksort', na_position='last')\n",
    "\n",
    "        plt.rcParams[\"figure.figsize\"] = (12,7)\n",
    "        ax = feature_score.plot('Feature', 'Score', kind='bar', color='c')\n",
    "        ax.set_title(\"Feature Importance using {}\".format(method), fontsize = 14)\n",
    "        ax.set_xlabel(\"features\")\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 281 ms, sys: 27.2 ms, total: 308 ms\n",
      "Wall time: 313 ms\n"
     ]
    }
   ],
   "source": [
    "%time get_feature_imp_plot(method=\"PredictionValuesChange\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.03 s, sys: 31.3 ms, total: 2.06 s\n",
      "Wall time: 514 ms\n"
     ]
    }
   ],
   "source": [
    "%time get_feature_imp_plot(method=\"LossFunctionChange\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.27 s, sys: 137 ms, total: 1.4 s\n",
      "Wall time: 1.08 s\n"
     ]
    }
   ],
   "source": [
    "%time get_feature_imp_plot(method=\"Permutation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x511.2 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.86 s, sys: 50.1 ms, total: 3.91 s\n",
      "Wall time: 2.29 s\n"
     ]
    }
   ],
   "source": [
    "%time get_feature_imp_plot(method=\"ShapeValues\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 25min 19s, sys: 6min 25s, total: 31min 45s\n",
      "Wall time: 5min 32s\n"
     ]
    }
   ],
   "source": [
    "%time get_feature_imp_plot(method=\"Baseline\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interaction Feature Importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset is provided, but Interaction feature importance don't use it.\n"
     ]
    }
   ],
   "source": [
    "fi = model.get_feature_importance(Pool(X_test, label=y_test,cat_features=categorical_features_indices), \n",
    "                                                                     type=\"Interaction\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[5, 10, 4.879359239300689],\n",
       " [7, 11, 4.211308589799566],\n",
       " [1, 7, 3.596972913690984],\n",
       " [6, 10, 3.56524055924632],\n",
       " [5, 6, 3.4918909052689524]]"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fi[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "fi_new = []\n",
    "for k,item in enumerate(fi):  \n",
    "    first = X_test.dtypes.index[fi[k][0]]\n",
    "    second = X_test.dtypes.index[fi[k][1]]\n",
    "    if first != second:\n",
    "        fi_new.append([first + \"_\" + second, fi[k][2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['marital-status_capital-gain', 4.879359239300689],\n",
       " ['relationship_capital-loss', 4.211308589799566],\n",
       " ['workclass_relationship', 3.596972913690984],\n",
       " ['occupation_capital-gain', 3.56524055924632],\n",
       " ['marital-status_occupation', 3.4918909052689524]]"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fi_new[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "feature_score = pd.DataFrame(fi_new,columns=['Feature-Pair','Score'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YPiD/21rn03rEXS7p50onNp6oGpdjL1IaIvKdiPhby3Nvioiv9bUS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\nFAo/l7RZBm8RVHy676IBX6ttMx1UXEXaOr1eT3r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a2Z3pehruJtVGF5jZTrjmXK13T6RI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\nDoXyoAF3Rylnks4ETjaza1rdqQhS1YqcS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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa774dcc2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_score = feature_score.sort_values(by='Score', ascending=False, inplace=False, kind='quicksort', na_position='last')\n",
    "plt.rcParams[\"figure.figsize\"] = (16,7)\n",
    "ax = feature_score.plot('Feature-Pair', 'Score', kind='bar', color='c')\n",
    "ax.set_title(\"Pairwise Feature Importance\", fontsize = 14)\n",
    "ax.set_xlabel(\"features Pair\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Plots for Model Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Numerical Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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   "source": [
    "feature = 'hours-per-week'\n",
    "res = model.get_feature_statistics(X_train, y_train, feature, plot=True)"
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   "metadata": {},
   "source": [
    "#### One-Hot Feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
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    {
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      "text/plain": [
       "{'binarized_feature': array([8, 0, 1, ..., 0, 6, 0]),\n",
       " 'mean_target': array([0.22366841, 0.1033411 , 0.2920592 , 0.        , 0.3948949 ,\n",
       "        0.        , 0.29469123, 0.28923768, 0.57639754], dtype=float32),\n",
       " 'mean_prediction': array([0.22334838, 0.10167585, 0.3016555 , 0.05339337, 0.37704837,\n",
       "        0.01450176, 0.30424172, 0.2946237 , 0.56375426], dtype=float32),\n",
       " 'objects_per_bin': array([15827,  1287,  1486,     9,   666,     5,   923,  1784,   805],\n",
       "       dtype=uint32),\n",
       " 'predictions_on_varying_feature': array([0.25023816, 0.24915191, 0.23332911, 0.18895106, 0.28084712,\n",
       "        0.22534325, 0.24529697, 0.21784215, 0.2707088 , 0.        ]),\n",
       " 'cat_values': array([' Private', ' ?', ' Local-gov', ' Without-pay', ' Federal-gov',\n",
       "        ' Never-worked', ' State-gov', ' Self-emp-not-inc',\n",
       "        ' Self-emp-inc'], dtype='<U17')}"
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     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature = 'workclass'\n",
    "model.get_feature_statistics(X_train, y_train, feature, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "feature = 'sex'\n",
    "res = titanic_model.calc_feature_statistics(titanic_train, titanic_train_target, feature, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.get_feature_statistics?"
   ]
  },


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