2721 lines
694 KiB
Plaintext
2721 lines
694 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "5901c138",
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"metadata": {},
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"source": [
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"\n",
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"# 📊 Introduction to Reading Data & Exploratory Data Analysis (EDA)\n",
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"\n",
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"This lab is your **first structured contact with real datasets**.\n",
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"\n",
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"Today you will:\n",
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"\n",
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"- Load data from an external file (.rda format)\n",
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"- Inspect the structure of a dataset\n",
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"- Identify variable types\n",
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"- Compute basic descriptive statistics\n",
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"- Use automated EDA tools to explore data visually\n",
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"- Reflect on why visualization matters\n",
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"\n",
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"⚠️ Today is about *understanding data*, not heavy coding.\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "60e41689",
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"metadata": {},
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"source": [
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"\n",
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"## 1️⃣ Install Required Libraries (Run Once)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "620c56a6",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: pyreadr in D:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages (0.5.4)\n",
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"Requirement already satisfied: retrying in D:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages (from dash<=2.18.2->dtale) (1.4.2)\n",
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"Requirement already satisfied: soupsieve>=1.6.1 in D:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages (from beautifulsoup4!=4.13.0b2->dtale) (2.8.3)\n",
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]
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}
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],
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"source": [
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"\n",
|
||
"# If needed, uncomment:\n",
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"!pip install pyreadr sweetviz dtale\n",
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"\n",
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||
"import pyreadr\n",
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"import pandas as pd\n",
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"import sweetviz as sv\n",
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"import dtale\n"
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]
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||
},
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{
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||
"cell_type": "markdown",
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||
"id": "7aa8d747",
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||
"metadata": {},
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||
"source": [
|
||
"\n",
|
||
"## 2️⃣ Load the .rda File\n",
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||
"\n",
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||
"Replace the file path if necessary.\n"
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||
]
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||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
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||
"id": "ba921fe7",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"odict_keys(['datasaurus_dozen'])"
|
||
]
|
||
},
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"result = pyreadr.read_r(\"../data/datasaurus_dozen.rda\")\n",
|
||
"result.keys()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "7bb3fc80",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"The file may contain multiple objects. Extract the dataframe:\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "10cb8cda",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "AttributeError",
|
||
"evalue": "'list' object has no attribute 'head'",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[11]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m df = \u001b[38;5;28mlist\u001b[39m(result.values())\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m \u001b[43mdf\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhead\u001b[49m()\n",
|
||
"\u001b[31mAttributeError\u001b[39m: 'list' object has no attribute 'head'"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"df = list(result.values())[0]\n",
|
||
"df.head()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6089afaa",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"## 3️⃣ First Contact With the Dataset\n",
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"\n",
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"Answer:\n",
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||
"\n",
|
||
"- How many rows?\n",
|
||
"- How many columns?\n",
|
||
"- What are the variable names?\n",
|
||
"- What types of variables exist?\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "fa82ffe1",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(1846, 3)"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"df.shape\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "64688f15",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"<class 'pandas.DataFrame'>\n",
|
||
"RangeIndex: 1846 entries, 0 to 1845\n",
|
||
"Data columns (total 3 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 dataset 1846 non-null str \n",
|
||
" 1 x 1846 non-null float64\n",
|
||
" 2 y 1846 non-null float64\n",
|
||
"dtypes: float64(2), str(1)\n",
|
||
"memory usage: 43.4 KB\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"df.info()\n"
|
||
]
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||
},
|
||
{
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||
"cell_type": "markdown",
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||
"id": "9141177c",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"## 4️⃣ Descriptive Statistics\n",
|
||
"\n",
|
||
"What do the summary statistics tell you?\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "1f84ca73",
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||
"metadata": {},
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||
"outputs": [
|
||
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||
"data": {
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"text/html": [
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"<style scoped>\n",
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" }\n",
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||
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|
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|
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|
||
" text-align: right;\n",
|
||
" }\n",
|
||
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|
||
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|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>x</th>\n",
|
||
" <th>y</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td>1846.000000</td>\n",
|
||
" <td>1846.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td>54.265695</td>\n",
|
||
" <td>47.835099</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td>16.713001</td>\n",
|
||
" <td>26.847766</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td>15.560750</td>\n",
|
||
" <td>0.015119</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td>41.073403</td>\n",
|
||
" <td>22.561073</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td>52.591269</td>\n",
|
||
" <td>47.594450</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td>67.277845</td>\n",
|
||
" <td>71.810778</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td>98.288123</td>\n",
|
||
" <td>99.694680</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" x y\n",
|
||
"count 1846.000000 1846.000000\n",
|
||
"mean 54.265695 47.835099\n",
|
||
"std 16.713001 26.847766\n",
|
||
"min 15.560750 0.015119\n",
|
||
"25% 41.073403 22.561073\n",
|
||
"50% 52.591269 47.594450\n",
|
||
"75% 67.277845 71.810778\n",
|
||
"max 98.288123 99.694680"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"df.describe()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "731fc39d",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"## 5️⃣ Automated Exploratory Data Analysis (Sweetviz)\n",
|
||
"\n",
|
||
"Generate a report:\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "0d86fa10",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
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||
"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "b3541d57f0994913b40d2e5a2f96c0e7",
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"version_major": 2,
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||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" | | [ 0%] 00:00 -> (? left)"
|
||
]
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},
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||
"metadata": {},
|
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"output_type": "display_data"
|
||
},
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{
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"data": {
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"text/html": [
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f&&1===e.nodeType&&(n.overflow=[h.overflow,h.overflowX,h.overflowY],null==(l=v&&v.display)&&(l=_.get(e,"display")),"none"===(c=ce.css(e,"display"))&&(l?c=l:(re([e],!0),l=e.style.display||l,c=ce.css(e,"display"),re([e]))),("inline"===c||"inline-block"===c&&null!=l)&&"none"===ce.css(e,"float")&&(u||(p.done(function(){h.display=l}),null==l&&(c=h.display,l="none"===c?"":c)),h.display="inline-block")),n.overflow&&(h.overflow="hidden",p.always(function(){h.overflow=n.overflow[0],h.overflowX=n.overflow[1],h.overflowY=n.overflow[2]})),u=!1,d)u||(v?"hidden"in v&&(g=v.hidden):v=_.access(e,"fxshow",{display:l}),o&&(v.hidden=!g),g&&re([e],!0),p.done(function(){for(r in g||re([e]),_.remove(e,"fxshow"),d)ce.style(e,r,d[r])})),u=vt(g?v[r]:0,r,p),r in v||(v[r]=u.start,g&&(u.end=u.start,u.start=0))}],prefilter:function(e,t){t?yt.prefilters.unshift(e):yt.prefilters.push(e)}}),ce.speed=function(e,t,n){var r=e&&"object"==typeof 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e,t=0,n=ce.timers;for(st=Date.now();t<n.length;t++)(e=n[t])()||n[t]!==e||n.splice(t--,1);n.length||ce.fx.stop(),st=void 0},ce.fx.timer=function(e){ce.timers.push(e),ce.fx.start()},ce.fx.interval=13,ce.fx.start=function(){ut||(ut=!0,dt())},ce.fx.stop=function(){ut=null},ce.fx.speeds={slow:600,fast:200,_default:400},ce.fn.delay=function(r,e){return r=ce.fx&&ce.fx.speeds[r]||r,e=e||"fx",this.queue(e,function(e,t){var n=ie.setTimeout(e,r);t.stop=function(){ie.clearTimeout(n)}})},lt=C.createElement("input"),ct=C.createElement("select").appendChild(C.createElement("option")),lt.type="checkbox",le.checkOn=""!==lt.value,le.optSelected=ct.selected,(lt=C.createElement("input")).value="t",lt.type="radio",le.radioValue="t"===lt.value;var mt,xt=ce.expr.attrHandle;ce.fn.extend({attr:function(e,t){return M(this,ce.attr,e,t,1<arguments.length)},removeAttr:function(e){return this.each(function(){ce.removeAttr(this,e)})}}),ce.extend({attr:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return"undefined"==typeof e.getAttribute?ce.prop(e,t,n):(1===o&&ce.isXMLDoc(e)||(i=ce.attrHooks[t.toLowerCase()]||(ce.expr.match.bool.test(t)?mt:void 0)),void 0!==n?null===n?void ce.removeAttr(e,t):i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:(e.setAttribute(t,n+""),n):i&&"get"in i&&null!==(r=i.get(e,t))?r:null==(r=ce.find.attr(e,t))?void 0:r)},attrHooks:{type:{set:function(e,t){if(!le.radioValue&&"radio"===t&&fe(e,"input")){var n=e.value;return e.setAttribute("type",t),n&&(e.value=n),t}}}},removeAttr:function(e,t){var n,r=0,i=t&&t.match(D);if(i&&1===e.nodeType)while(n=i[r++])e.removeAttribute(n)}}),mt={set:function(e,t,n){return!1===t?ce.removeAttr(e,n):e.setAttribute(n,n),n}},ce.each(ce.expr.match.bool.source.match(/\\w+/g),function(e,t){var a=xt[t]||ce.find.attr;xt[t]=function(e,t,n){var r,i,o=t.toLowerCase();return n||(i=xt[o],xt[o]=r,r=null!=a(e,t,n)?o:null,xt[o]=i),r}});var bt=/^(?:input|select|textarea|button)$/i,wt=/^(?:a|area)$/i;function Tt(e){return(e.match(D)||[]).join(" ")}function Ct(e){return e.getAttribute&&e.getAttribute("class")||""}function kt(e){return Array.isArray(e)?e:"string"==typeof e&&e.match(D)||[]}ce.fn.extend({prop:function(e,t){return M(this,ce.prop,e,t,1<arguments.length)},removeProp:function(e){return this.each(function(){delete this[ce.propFix[e]||e]})}}),ce.extend({prop:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return 1===o&&ce.isXMLDoc(e)||(t=ce.propFix[t]||t,i=ce.propHooks[t]),void 0!==n?i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:e[t]=n:i&&"get"in i&&null!==(r=i.get(e,t))?r:e[t]},propHooks:{tabIndex:{get:function(e){var t=ce.find.attr(e,"tabindex");return t?parseInt(t,10):bt.test(e.nodeName)||wt.test(e.nodeName)&&e.href?0:-1}}},propFix:{"for":"htmlFor","class":"className"}}),le.optSelected||(ce.propHooks.selected={get:function(e){var t=e.parentNode;return t&&t.parentNode&&t.parentNode.selectedIndex,null},set:function(e){var t=e.parentNode;t&&(t.selectedIndex,t.parentNode&&t.parentNode.selectedIndex)}}),ce.each(["tabIndex","readOnly","maxLength","cellSpacing","cellPadding","rowSpan","colSpan","useMap","frameBorder","contentEditable"],function(){ce.propFix[this.toLowerCase()]=this}),ce.fn.extend({addClass:function(t){var e,n,r,i,o,a;return v(t)?this.each(function(e){ce(this).addClass(t.call(this,e,Ct(this)))}):(e=kt(t)).length?this.each(function(){if(r=Ct(this),n=1===this.nodeType&&" "+Tt(r)+" "){for(o=0;o<e.length;o++)i=e[o],n.indexOf(" "+i+" ")<0&&(n+=i+" ");a=Tt(n),r!==a&&this.setAttribute("class",a)}}):this},removeClass:function(t){var e,n,r,i,o,a;return v(t)?this.each(function(e){ce(this).removeClass(t.call(this,e,Ct(this)))}):arguments.length?(e=kt(t)).length?this.each(function(){if(r=Ct(this),n=1===this.nodeType&&" "+Tt(r)+" "){for(o=0;o<e.length;o++){i=e[o];while(-1<n.indexOf(" "+i+" "))n=n.replace(" "+i+" "," 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n||(e.selectedIndex=-1),o}}}}),ce.each(["radio","checkbox"],function(){ce.valHooks[this]={set:function(e,t){if(Array.isArray(t))return e.checked=-1<ce.inArray(ce(e).val(),t)}},le.checkOn||(ce.valHooks[this].get=function(e){return null===e.getAttribute("value")?"on":e.value})});var Et=ie.location,jt={guid:Date.now()},At=/\\?/;ce.parseXML=function(e){var t,n;if(!e||"string"!=typeof e)return null;try{t=(new ie.DOMParser).parseFromString(e,"text/xml")}catch(e){}return n=t&&t.getElementsByTagName("parsererror")[0],t&&!n||ce.error("Invalid XML: "+(n?ce.map(n.childNodes,function(e){return e.textContent}).join("\\n"):e)),t};var Dt=/^(?:focusinfocus|focusoutblur)$/,Nt=function(e){e.stopPropagation()};ce.extend(ce.event,{trigger:function(e,t,n,r){var 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|
||
" <script> let g_snapped = "";\n",
|
||
"let g_lastHovered = "";\n",
|
||
"\n",
|
||
"function hideAllDetails()\n",
|
||
"{\n",
|
||
" $(".container-feature-detail").hide();\n",
|
||
" $(".container-df-associations").hide();\n",
|
||
" $("span.bg-tab-summary-rollover").hide();\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"// GLOBAL EVENTS\n",
|
||
"// ---------------------------------------------------------------------------------------------------------------------------\n",
|
||
"// EVENT: [ANYWHERE] RIGHT-CLICK REMOVES SELECTION\n",
|
||
"// $(document).contextmenu(function() {\n",
|
||
"// if (g_snapped != "")\n",
|
||
"// {\n",
|
||
"// g_snapped = "";\n",
|
||
"// hideAllDetails();\n",
|
||
"// }\n",
|
||
"// if (g_lastHovered != "")\n",
|
||
"// {\n",
|
||
"// $(g_lastHovered).show();\n",
|
||
"// //alert("#"+g_lastHovered);\n",
|
||
"// }\n",
|
||
"// return false;\n",
|
||
"// });\n",
|
||
"\n",
|
||
"$("span.bg-tab-summary-rollover").hide();\n",
|
||
"// hideAllDetails();\n",
|
||
"\n",
|
||
"$(document).ready(function() {\n",
|
||
"// INITIALIZATION\n",
|
||
"// --------------------------------------------------------\n",
|
||
"hideAllDetails();\n",
|
||
"$("span.bg-tab-summary-rollover").hide();\n",
|
||
"\n",
|
||
"// Make the detail column the same height, so the floating element has room\n",
|
||
"//$("#col2").height($("#col1").height());\n",
|
||
"$("#col1").height(g_height);\n",
|
||
"$("#col2").height(g_height);\n",
|
||
"//alert($("#col1").height());\n",
|
||
"\n",
|
||
"// SUMMARY AREA\n",
|
||
"// --------------------------------------------------------\n",
|
||
"// EVENT: SUMMARY ROLLOVER\n",
|
||
"// $(".selector, .container-feature-summary-target").hover(\n",
|
||
"$(".selector").hover(\n",
|
||
"// ENTER function\n",
|
||
"function(event) {\n",
|
||
" // Rollover start!\n",
|
||
" // $(".container-feature-detail").hide();\n",
|
||
" $("span.bg-tab-summary-rollover").hide();\n",
|
||
" $("#" + $(this).data("rollover-span")).removeClass("bg-tab-summary-rollover-locked");\n",
|
||
" $("#" + $(this).data("rollover-span")).addClass("bg-tab-summary-rollover-vertical");\n",
|
||
" $("#" + $(this).data("rollover-span")).show();\n",
|
||
" g_lastHovered = "#" + $(this).data("detail-div");\n",
|
||
" },\n",
|
||
"// EXIT function\n",
|
||
"function(event) {\n",
|
||
" // Rollover end!\n",
|
||
" // hideAllDetails();\n",
|
||
" //FBFB $("#" + $(this).data("detail-div")).hide();\n",
|
||
" }\n",
|
||
");\n",
|
||
"\n",
|
||
"// EVENT: SUMMARY CLICK\n",
|
||
"// $(".container-feature-summary, .container-feature-summary-target").click(function(event) {\n",
|
||
"$(".selector").click(function(event) {\n",
|
||
" if ($(this).parent().parent().data('expanded') != 'true')\n",
|
||
" {\n",
|
||
" // EXPAND\n",
|
||
" // --------------------------------------------------------\n",
|
||
" $("#" + $(this).data("detail-div")).show();\n",
|
||
" $(this).parent().parent().data('expanded', 'true');\n",
|
||
" //alert($(this).parent().attr('id').substring(8) );\n",
|
||
"\n",
|
||
" var feature_index_str = $(this).parent().attr('id').substring(8);\n",
|
||
" if ($(this).parent().attr('id') == "summary-target") {\n",
|
||
" // Special feature name for target, so use common index notation for the following tasks\n",
|
||
" feature_index_str = "f-1";\n",
|
||
" }\n",
|
||
" if ($('#cat-assoc-window-'+feature_index_str).length) {\n",
|
||
" // CATEGORICAL feature: use variable-height window\n",
|
||
" var $el = $('#detail_breakdown-' + feature_index_str); //record the elem so you don't crawl the DOM everytime\n",
|
||
" // HACK: BUG IN BROWSERS? DIVING BY SCALE HERE...\n",
|
||
" var bottom = ($el.position().top / g_scale) + $el.outerHeight(true); // passing "true" will also include the top and bottom margin\n",
|
||
" var desiredBottomBreakdown = bottom + 157;\n",
|
||
"\n",
|
||
" $el = $('#cat-assoc-window-' + feature_index_str); //record the elem so you don't crawl the DOM everytime\n",
|
||
" var bottomAssoc = $el.position().top + $el.outerHeight(true); // passing "true" will also include the top and bottom margin\n",
|
||
" var desiredBottomAssoc = bottomAssoc + 166;\n",
|
||
"\n",
|
||
" var finalHeight = Math.max(desiredBottomBreakdown, desiredBottomAssoc);\n",
|
||
" if ($(this).parent().attr('id') == "summary-target")\n",
|
||
" {\n",
|
||
" // More special processing for the target: change its background and limit its height (so it doesn't show through others below)\n",
|
||
" // (Here, make the Height a bit taller so the black background shows through)\n",
|
||
" $(this).parent().css('height', String((finalHeight + 50))+ 'px');\n",
|
||
" $("#summary-target").css("overflow", "hidden");\n",
|
||
" }\n",
|
||
" $(this).parent().parent().css('height', String(finalHeight) + 'px');\n",
|
||
" }\n",
|
||
" else\n",
|
||
" {\n",
|
||
" // NON-CATEGORICAL feature: use fixed height window\n",
|
||
" $(this).parent().parent().css('height', '1030px');\n",
|
||
" }\n",
|
||
" // Use the "big" background image for the target\n",
|
||
" if ($(this).parent().attr('id') == "summary-target")\n",
|
||
" {\n",
|
||
" $("#summary-target-bg").addClass("bg-tab-summary-target-full");\n",
|
||
" $("#summary-target-bg").removeClass("bg-tab-summary-target");\n",
|
||
" }\n",
|
||
"\n",
|
||
" // HACK: For SOME reason, a selection gets made when we change what is hidden, unselect it\n",
|
||
" let sel = document.getSelection();\n",
|
||
" sel.removeAllRanges();\n",
|
||
"\n",
|
||
" // Animate to the top of the screen when expanding, so we can see the whole thing immediately\n",
|
||
" $('html,body').animate(\n",
|
||
" {scrollTop: $("#" + $(this).parent().attr('id')).offset().top}, 'fast');\n",
|
||
" }\n",
|
||
" else\n",
|
||
" {\n",
|
||
" // CONTRACT\n",
|
||
" // --------------------------------------------------------\n",
|
||
" $("#" + $(this).data("detail-div")).hide();\n",
|
||
"\n",
|
||
" // HACK: For SOME reason, a selection gets made when we change what is hidden, unselect it\n",
|
||
" let sel = document.getSelection();\n",
|
||
" sel.removeAllRanges();\n",
|
||
"\n",
|
||
" $(this).parent().parent().data('expanded', 'false');\n",
|
||
" $(this).parent().parent().css('height', '161px');\n",
|
||
"\n",
|
||
" if ($(this).parent().attr('id') == "summary-target")\n",
|
||
" {\n",
|
||
" $("#summary-target-bg").removeClass("bg-tab-summary-target-full");\n",
|
||
" $("#summary-target-bg").addClass("bg-tab-summary-target");\n",
|
||
" }\n",
|
||
" }\n",
|
||
" // var offTop = $("#" + $(this).parent().attr('id')).offset().top;\n",
|
||
" // $('html,body').scrollTop(offTop);\n",
|
||
" // let thisIndex = $(this).parent().parent().data('order-index');\n",
|
||
" //alert(thisIndex);\n",
|
||
" // for (let i = parseInt(thisIndex) + 1; i < 10; i++) {\n",
|
||
" // let currentTop = $("#summary-pos-f" + i).attr('style')\n",
|
||
" // $("#summary-pos-f" + i).attr('style',\n",
|
||
" // }\n",
|
||
"// if(g_snapped == $(this).parent().attr('id'))\n",
|
||
"// {\n",
|
||
"// $("#" + $(this).data("rollover-span")).removeClass("bg-tab-summary-rollover-locked");\n",
|
||
"// $("#" + $(this).data("rollover-span")).addClass("bg-tab-summary-rollover");\n",
|
||
"// g_snapped = "";\n",
|
||
"// }\n",
|
||
"// else if (g_snapped == "")\n",
|
||
"// {\n",
|
||
"// $("#" + $(this).data("rollover-span")).removeClass("bg-tab-summary-rollover");\n",
|
||
"// $("#" + $(this).data("rollover-span")).addClass("bg-tab-summary-rollover-locked");\n",
|
||
"// g_snapped = $(this).parent().attr('id');\n",
|
||
"// // $("#" + $(this).data("detail-div")).show();\n",
|
||
"// //$(g_lastHovered).show();\n",
|
||
"// // alert(this.parent().id);\n",
|
||
"// }\n",
|
||
" }\n",
|
||
");\n",
|
||
"\n",
|
||
"\n",
|
||
"// SPECIFIC BUTTONS\n",
|
||
"// ---------------------------------------------------------------------------------------------------------------------------\n",
|
||
"// SUMMARY: ASSOCIATIONS\n",
|
||
"// $("#button-summary-associations-source, #button-summary-associations-compare").hover(\n",
|
||
"// // ENTER function\n",
|
||
"// function()\n",
|
||
"// {\n",
|
||
"// if(g_snapped=="")\n",
|
||
"// {\n",
|
||
"// hideAllDetails();\n",
|
||
"// $("#df-assoc").show();\n",
|
||
"// //$("#df-assoc").show();\n",
|
||
"// }\n",
|
||
"// g_lastHovered = "#df-assoc";\n",
|
||
"// },\n",
|
||
"// // EXIT function\n",
|
||
"// function()\n",
|
||
"// {\n",
|
||
"// if(g_snapped=="")\n",
|
||
"// {\n",
|
||
"// hideAllDetails();\n",
|
||
"// }\n",
|
||
"// });\n",
|
||
"// );\n",
|
||
"\n",
|
||
"// ASSOCIATIONS CLICK\n",
|
||
"$("#button-summary-associations-source, #button-summary-associations-compare").click(function(event) {\n",
|
||
" let actual_div = "#" + $(this).data("detail-div");\n",
|
||
" // Quick hack: just remove the selected state to both buttons and restore if needed\n",
|
||
" $("#button-summary-associations-source, #button-summary-associations-compare").removeClass("button-assoc-selected");\n",
|
||
" $("#button-summary-associations-source, #button-summary-associations-compare").addClass("button-assoc");\n",
|
||
" if(g_snapped == actual_div)\n",
|
||
" {\n",
|
||
" // DESELECT/HIDE ASSOC\n",
|
||
" // --------------------------------------------------------\n",
|
||
" g_snapped = "";\n",
|
||
" $(actual_div).hide();\n",
|
||
" $(".page-all-summaries").css({top: "160px"});\n",
|
||
" // $(this).removeClass("button-assoc-selected");\n",
|
||
" // $(this).addClass("button-assoc");\n",
|
||
" }\n",
|
||
" else if(g_snapped == "")\n",
|
||
" {\n",
|
||
" // SELECT/SHOW ASSOC\n",
|
||
" // --------------------------------------------------------\n",
|
||
" g_snapped = actual_div;\n",
|
||
" $(actual_div).show();\n",
|
||
" $(".page-all-summaries").css({top: "993px"});\n",
|
||
" $(this).addClass("button-assoc-selected");\n",
|
||
" }\n",
|
||
" else\n",
|
||
" {\n",
|
||
" // SWAP to OTHER ASSOC: DESELECT old, select new\n",
|
||
" // --------------------------------------------------------\n",
|
||
" $(g_snapped).hide();\n",
|
||
" g_snapped = actual_div;\n",
|
||
" $(this).addClass("button-assoc-selected");\n",
|
||
" $(actual_div).show();\n",
|
||
" }\n",
|
||
"});\n",
|
||
"\n",
|
||
"\n",
|
||
"// DETAIL GRAPH BUTTONS\n",
|
||
"$(".button-bin").click(function() {\n",
|
||
" which_id = $(this).attr('data-target');\n",
|
||
" $("#"+which_id).attr('class', $(this).attr('data-new_class') + " pos-detail-num-graph");\n",
|
||
"});\n",
|
||
"\n",
|
||
"\n",
|
||
"}); // $(document).ready(... </script>\n",
|
||
" <style> span.icon-expand { content: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABwAAAAcCAYAAAByDd+UAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAALRJREFUeNpi/P//PwM9ARMDncGohVQHLATkDYA4gEQzD0AxdgBKpTjw/P/kg/m4zMVlWQKSRgE8jkLHAkgOTcCmBlccKkDpRCD+QEJwfkDSo0DNRAMqLfbjkRcYzYeDJh8ixxk6cMAizkgtCw9gsYwBbwan0EJHLD4+gEV8NNEMrlSKr0hjpLYPH0CLp/n4iikcRdp8JDMGvnpiJNBqc0DKc8SCDUB8AWdcjDYTRy0kFQAEGAAqdjq/C2RykQAAAABJRU5ErkJggg==);}\n",
|
||
"span.icon-categorical { content: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABwAAAAcCAYAAAByDd+UAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAOFJREFUeNpi/P//PwM9ARMDncGohVQHLHjkHKAYHTwA4gVQdgIQK2BRcwCKMQEolWLBCf/xgwYoxgcSsJmNy4cwVxcC8QUkcQMg7gdieyQxXGoUSA1SBqhBB6igZjSVwkE8WkqVJ1MNwVTqAMTv8aTA/VCMC7yHmoFhNiOewlsBms8YcORFBlwpEZpPHwwKH7LgKWUEoC59iBY/CVh8g02NA7bsQijRLETT5IDFQmLUjOZDlHIRH59YNQQthCXpfhzyB5Hiq5+AGURZCMtHhOrDB6TWh4yjrbZRCwe9hQABBgAyc1dqBJEdOQAAAABJRU5ErkJggg==);}\n",
|
||
"span.icon-collapse { content: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABwAAAAcCAYAAAByDd+UAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAJxJREFUeNpi/P//PwM9ARMDncGohVQHLATkDYA4gEQzD0AxdgBKpTjw/P/kg/m4zMVlWQKSRgE8jkLHAkgOTcCmBlccKkDpRCD+QEJwfkDSo0DPRCMwmg8HTT6E5x4i1TFSy8ID9Pah42iiGZIWfqCnhQ+gxdN8fMUUjiJtPpIZA189MRJotTlAMSlgAxBfwFkyjDYTRy0kFQAEGAD+JDS/pyABgwAAAABJRU5ErkJggg==);}\n",
|
||
"\n",
|
||
"span.bg-tab-summary { position: absolute; z-index:-1000; content: 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);}\n",
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);}\n",
|
||
"/* used in assoc */\n",
|
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|
||
"\n",
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|
||
"\n",
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"div.ic-missing-green { position: absolute; top: 2px; z-index: -1; content: url(data:image/png;base64,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);}\n",
|
||
"div.ic-missing-yellow { position: absolute; top: 2px; z-index: -1; content: url(data:image/png;base64,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);}\n",
|
||
"div.ic-missing-orange { position: absolute; top: 2px; z-index: -1; content: url(data:image/png;base64,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);}\n",
|
||
"div.ic-missing-red { position: absolute; top: 2px; z-index: -1; content: url(data:image/png;base64,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);} </style>\n",
|
||
" <style> @font-face\n",
|
||
"{\n",
|
||
" font-family: RobotoBoldCond; font-style: normal; font-weight: normal;\n",
|
||
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format('truetype');\n",
|
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"}\n",
|
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"@font-face\n",
|
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"{\n",
|
||
" font-family: RobotoMed; font-style: normal; font-weight: normal;\n",
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DzkAsSAbERKxEgA5ObAlEbEPAzk5sCoSsQwGOTkwMRM0NjcuATU0NjMyFhUUBgceARUUBCMiJDcUFjI2NTQmIgYTFBYyNjU0JiIGaHxwXm3wzM3wbl9ye/782Nn++/N93HuB1H8hbbptbrpsAY11ujIwp2u62tq6a6cwNbh0wOHiy2uAfG9shYQCIWR2dmRfe3UAAAIAXf/6BBIFxAAVACEAYACyDAAAK7ENCOmyBAIAK7EgB+m0ExkMBA0rsRMG6QGwIi+wANaxFhDpsBYQsRwBK7ARMrEIEemxIwErsRYAERKxDA05ObAcEbIQBBM5OTkAsRkTERKwETmwIBGwADkwMRM0PgEzMgARFRAABSM1Mz4BNwYjIgI3FBYzMjY3NTQmIgZddNaN3AEC/pz+nx0j1+YOeqPA5PB+aUmAI4TSfQPIkOqC/rj+7UT+dv5iA8kDydKBAQ3iiahUSl+hxK0AAAACAIL/9QGdBFEACgAVAC0AsgkAACuxAwvpsBQvsQ4L6QGwFi+wAdawCzKxBhXpsBEysQYV6bEXASsAMDE2NDYzMhYVFAYjIgI0NjMyFhUUBiMigkpDREpKREFMSkNESkpEQT90TU06OUsDm3RNTTo5SwAAAAIALv64AYgEUQAJABQAOgCwEy+xDQvpAbAVL7AD1rEGDemwBhCzJQYQDiuxCxXpsAsvsRAV6bEWASuxBgMRErIJDRM5OTkAMDEXPgE3NTMHDgEHAjQ2MzIWFRQGIyIuOisB2wEBaVNESkNESkpEQfpbh0a9r2rVRQTYdE1NOjlLAAAAAAEAPwCkA4QETgAGABEAsgIBACsBsAcvsQgBKwAwMRM1ARUNARU/A0X9sgJOAhnBAXTz5ODzAAAAAgCRAWQD7wPWAAMABwAaALAAL7EBCOmwBC+xBQPpAbAIL7EJASsAMDETNSEVATUhFZEDXvyiA14BZMnJAajKygAAAAABAIAApQPgBE4ABgARALIEAQArAbAHL7EIASsAMDE3NS0BNQEVgAJq/ZYDYKXv6OPv/ozBAAAAAAIAPP/0A5gFxAAYACMAdgCyIgAAK7EcC+myAwIAK7EVA+mzACIDCCuwBjMBsCQvsADWsRgR6bAYELEMASuxCw/psy0MGQ4rsR8U6bALELESASuxBhHpsSUBK7ELDBEStAMVHCEiJBc5sRIfERKxDwk5ObAGEbAIOQCxABwRErELEjk5MDETPgEzMhYVFA8BBgcjND4BNzY1NCYjIgYVEzQ2MzIWFRQGIiY8Au3DyeGYe0IC40LDGihdWlZpHko/QEpIhEcERbHOzLejnnlLkIWevSg9R15jYVP8MDtJSzk3SkoAAAIAW/47BtkFkAA2AEIAtACyCwAAK7EdBOmyEAAAK7E6BOmwMi+xKwTpsEAvsRcE6bAjL7EEBOkBsEMvsADWtCcNABUEK7AnELEgASu0CA0ADQQrsUQBK7A2Gro/u/odABUrCg6wPRCwPsCxGxj5sBrAALMaGz0+Li4uLgGzGhs9Pi4uLi6wQBoBsScAERKxASg5ObAgEbcLBBIjKy8yOCQXObAIErEJITk5ALErMhESsC85sAsRsC45sTodERKwDTkwMRMaASQzMgQSAwYCIyInDgEjIiY3NhI2MzIWFwMGMzI2NxIAISIEAgcGEgQzMjY3Fw4BIyIkJyYlBhYzMjY3EyYjIgZmDN4Bgfb5AWeyDAzevrU9M4dKkpcSEH/DblSBVzQThWaDBhH+wf7AxP7RsgkMiwEfz1S3QCY9z2n+/pRbXgKBDUpRNmAeLTIvb4wB1wESAbXy2/5l/uz6/t+aTEzwyaMBBo8qQv3NxtuuAXEBiMT+je3x/qO2KCKJKDHXzNP1iI1fUwHtE9EAAAACABIAAAVCBbAABwAKACwAsgAAACuwAzOyAQIAK7QGCAABDSuxBgPpAbALL7EMASsAsQEIERKwCjkwMTMBMwEhAyEDEyEDEgIm4wIn/vh3/cx2vQGm0wWw+lABU/6tAh8CXAAAAwCUAAAEowWwAA4AFgAfAGMAsgAAACuxDwPpsgICACuxHwPptBcWAAINK7EXBukBsCAvsADWsQ8M6bAXMrAPELETASuxCwzpsBsg1hGxBQzpsSEBK7EFExESsAg5ALEWDxESsAs5sBcRsAg5sB8SsAU5MDEzESEyBBUUBgceARUUBCMlITI2NTQnITUzMjY1NCYrAZQB8/cBAmxodoH++fX+6gEZd4bo/tL4doV7gvYFsMbEZKAsILF8zdzKdmnjBbprYmxgAAABAGb/7ATrBcQAHQBWALIaAAArsRMD6bITGgors0ATFwkrsgUCACuxDAPpsgwFCiuzQAwJCSsBsB4vsADWsRAM6bAQELEWASuwCTKxFwzpsAgysR8BK7EWEBESsQUaOTkAMDETNTQSJDMyABcjLgEjIgYHFRQWMzI2NzMGACMiJAJmkgERs/EBJhj8EpOOpbECqaOVlhT8Fv7U+a7+95ACiojOATqq/vrvnYvx6YHs+Iac6f77pQEwAAAAAAIAlAAABNIFsAALABUAMACyCwAAK7EMA+myAgIAK7EVA+kBsBYvsADWsQwM6bAMELEQASuxBwzpsRcBKwAwMTMRITIEEh0BFAIEIyczMjY3NTQmKwGUAa7BASukpf7Pxaalx9UCzsSxBbCs/sTMSc/+xqrK+elR7foAAAABAJQAAARMBbAACwBHALIAAAArsQkD6bIBAgArsQQD6bQFCAABDSuxBQjpAbAML7AA1rEJDOmwBDKyCQAKK7NACQMJK7AKMrNACQcJK7ENASsAMDEzESEVIREhFSERIRWUA7H9TAJW/aoCuwWwzP5uyP5AygAAAAABAJQAAAQxBbAACQBAALIAAAArsgECACuxBAPptAgFAAENK7EIA+kBsAovsADWsQkM6bAEMrIJAAors0AJAwkrs0AJBwkrsQsBKwAwMTMRIRUhESEVIRGUA539YAJK/bYFsMz+T8r9lwAAAAABAGr/7ATwBcQAHgBrALIbAAArsRED6bIEAgArsQoD6bIKBAors0AKCAkrtBUWGwQNK7EVB+kBsB8vsADWsQ4M6bAOELETASuwCDKxGAzpsAcyshMYCiuzQBMVCSuxIAErsRMOERKyCgQbOTk5ALEVERESsBg5MDETNRAAITIEFyMCISIGBxUUEjMyNxEhNSERBgQjIiQCagE8ARvzAR4d+Cr++aqxA8exwlL+1AIoT/7osrf+5pkClXIBSgFz8OIBB/XtcOz++1gBHcD90mdqpgE1AAEAlAAABRgFsAALAD8AsgAAACuwBzOyAQIAK7AFM7QDCgABDSuxAwPpAbAML7AA1rELDOmwAjKwCxCxCAErsAQysQcM6bENASsAMDEzETMRIREzESMRIRGU/QKL/Pz9dQWw/aICXvpQAof9eQAAAAABAKMAAAGfBbAAAwAhALIAAAArsgECACsBsAQvsADWsQMM6bEDDOmxBQErADAxMxEzEaP8BbD6UAAAAAABAC3/7APkBbAADwA/ALINAAArsQQD6bIEDQors0AEAAkrsggCACsBsBAvsADWsQEM6bABELEHASuxCgzpsREBK7EHARESsA05ADAxEzMUFjMyNjURMxEUBCMiJi38c21mefz++9bk+AGfdHWHdwP8/APR9uYAAAABAJQAAAUYBbAADAAwALIAAAArsAgzsgECACuwBTMBsA0vsADWsQwM6bACMrEOASsAsQEAERKxAwo5OTAxMxEzETcBIQkBIQEHEZT9jAGqATL94wI8/tT+SqUFsP1VrQH+/Xv81QJ1r/46AAABAJQAAAQmBbAABQAsALIAAAArsQMD6bIBAgArAbAGL7AA1rEDDOmyAwAKK7NAAwUJK7EHASsAMDEzETMRIRWU/QKVBbD7GsoAAAAAAQCUAAAGagWwAA4AVwCyAAAAK7EGCjMzsgECACuwBDMBsA8vsADWsQ4M6bEMD+mwDhCxBwErsQYM6bAGELEJD+mwCS+xEAErsQcOERKzAgQKCyQXOQCxAQARErIDCQw5OTkwMTMRIQkBIREjERMBIwETEZQBSAGkAaMBR/wZ/lK1/lMZBbD7pARc+lAB4AKC+54EYf1//iAAAAAAAQCUAAAFFwWwAAkARgCyAAAAK7AGM7IBAgArsAQzAbAKL7AA1rEJDOmwCRCxAwErsQYM6bELASuxCQARErACObADEbAHOQCxAQARErEDCDk5MDEzETMBETMRIwERlP0Ci/v9/XcFsPvzBA36UAQJ+/cAAAACAGb/7AUeBcQAEAAeADwAsg0AACuxFAnpsgUCACuxGwnpAbAfL7AA1rERDOmwERCxFwErsQkM6bEgASuxFxERErIFBA05OTkAMDETNTQSJCAEEhcVFAIEIyIkAjcUEjMyEj0BNAIjIgIHZpcBEwFkAROWAZT+7bOx/uuX/LumqLW3qKS5AgKqUtUBRq2r/r/VUdb+va2tAUDZ8P76AQD2TPIBAv7/6wACAJQAAATUBbAACgATAEIAsgAAACuyAQIAK7ETA+m0CQsAAQ0rsQkD6QGwFC+wANaxCgzpsAsysAoQsQ8BK7EFDOmxFQErALETCxESsAU5MDEzESEyBBUUBCMhGQEhMjY1NCYnIZQCLfQBH/7n/f7TATCHjpB+/skFsP7R1u794wLof3h2jQIAAgBg/wQFGgXEABUAIwBPALISAAArsRkJ6bIFAgArsSAJ6QGwJC+wANaxFgzpsBYQsRwBK7EKDOmwDjKxJQErsRwWERKyEBIFOTk5sAoRsQ0POTkAsRkSERKwDTkwMRM1NBIkMzIEEhcVFAIHFwclBiMiJAI3FBIzMhI9ATQmIyICB2CXAROxtAETlgGDdvqk/so9RrD+65f8uaeptbioo7kCAqpS1QFGrav+v9VRz/7RWcOU9Q2tAUDZ7P72AQD2TPb+/v/qAAACAJQAAATeBbAADgAXAGEAsgAAACuwCjOyAQIAK7EXA+m0DQ8AAQ0rsQ0D6QGwGC+wANaxDgzpsA8ysA4QsRMBK7EFDOmxGQErsRMOERKxDAg5ObAFEbALOQCxDQARErAJObAPEbAIObAXErAFOTAxMxEhMgQVFAYHARUhASEZASEyNjU0JichlAIA/AESjX4BR/7x/tz+5gEEgJCFhP71BbDi1pLFNf2hDQIx/c8C/IFwdYACAAAAAQBK/+wEigXEACcAbQCyJAAAK7EECOmyBCQKK7NABAAJK7IQAgArsRgD6bIYEAors0AYFAkrAbAoL7AN1rEbDOmwACDWEbEBDOmwGxCxBwErsBUysSEM6bAUMrEpASuxBxsRErQEChAeJCQXOQCxGAQRErENITk5MDETMxQWMzI2NTQmJCcmNTQkMzIeARUjNCYjIgYVFBYEHgEVFAQjIiQmSv2kmYSFh/6gaMcBH+WY7oj8j4V8iZQBVM5g/unvnv73kwG4fIhrWGBoakF9ybDkcM9+coFqX1BrZYGncLbXdc4AAQAtAAAEsAWwAAcAOgCyBgAAK7IBAgArsQAD6bADMgGwCC+wBtaxBQzpsgUGCiuzQAUDCSuyBgUKK7NABgAJK7EJASsAMDETNSEVIREjES0Eg/46+wTkzMz7HATkAAAAAQB9/+wEvQWwABAANwCyDgAAK7EGA+myAQIAK7AJMwGwES+wANaxAwzpsAMQsQgBK7ELDOmxEgErsQgDERKwDjkAMDETETMRFBYzIBkBMxEUACMiAH38lJABJPz+1/f6/toB5APM/DKSmgE0A8b8M+j+8QELAAAAAQASAAAFHQWwAAYAPQCyBgAAK7IAAgArsAMzAbAHL7AA1rEBFemwARCxAwErsQQV6bEIASuxAwERErEFBjk5ALEABhESsAI5MDETIQkBIQEjEgEVAW4BcgEW/fT1BbD7jQRz+lAAAAABADAAAAblBbAADACRALIMAAArsQkLMzOyAAIAK7IDBAYzMzMBsA0vsADWsQEM6bABELEGASuxBwzpsQ4BK7A2Gro+B/A9ABUrCrADLg6wAsCxChn5BbALwLrB7fBtABUrCrAJLrELCgiwCsAOsQUG+QWwBMADALICBQouLi4BtgIDBAUJCgsuLi4uLi4usEAasQYBERKxCAw5OQAwMRMzEwEzARMzASMJASMw++IBFtQBE+D7/rDy/uv+5fMFsPu6BEb7uARI+lAEJ/vZAAAAAQApAAAE6QWwAAsAJgCyAAAAK7AIM7ICAgArsAUzAbAML7ENASsAsQIAERKxBAo5OTAxMwkBIQkBIQkBIQkBKQHD/kcBJAEyATIBJP5IAcL+2f7H/sYC3gLS/fICDv0u/SICFv3qAAABAAcAAATWBbAACAAwALIHAAArsgACACuwAzMBsAkvsAfWsQYM6bEKASuxBgcRErACOQCxAAcRErACOTAxEyEJASEBESMRBwEZAU8BTwEY/hj+BbD9TgKy/Gj96AIYAAABAFAAAASMBbAACQAuALIAAAArsQcD6bIEAgArsQMD6QGwCi+xCwErALEHABESsAE5sQQDERKwBjkwMTM1ASE1IRUBIRVQAvH9FAQf/Q4DCqQEQMyg+7rKAAAAAAEAhP68AhwGjgAHADUAsAcvsQUG6bAEL7ECBukBsAgvsADWtAcVAAoEK7ACMrEFEem0AxUACgQrsAYysQkBKwAwMRMRIRUjETMVhAGYpaX+vAfSvvmpvQABABT/gwNkBbAAAwARALIAAgArAbAEL7EFASsAMDETMwEjFPACYPAFsPnTAAEADP68AaYGjgAHAD4AsAcvsQAG6bADL7EEBukBsAgvsAfWsAMytAYVAAoEK7AGELEBEemwAS+wBhC0AxUACgQrsAMvsQkBKwAwMRczESM1IREhDKenAZr+ZocGV774LgAAAAABADUC2QM1BbAABgARALIBAgArAbAHL7EIASsAMDETATMBIwsBNQErqwEqzbOyAtkC1/0pAc3+MwAAAAABAAP/QQOYAAAAAwAaALIAAAArsQMH6bIAAAArAbAEL7EFASsAMDEzIRUhAwOV/Gu/AAAAAQAxBNECCQYAAAMAIACwAy+0AQsADgQrAbAEL7AA1rQCFQAJBCuxBQErADAxEyETIzEBFcPKBgD+0QAAAgBa/+wD+wROAB4AKQCCALIYAAArshwAACuxIgfpshABACuxCAbpsggQCiuzQAgMCSu0AyccEA0rsQME6QGwKi+wANaxHxHpsB8QsSUBK7AEMrEUEemxKwErsR8AERKwDDmwJRGyCxAcOTk5sBQSsRgaOTkAsSIYERKxFho5ObAnEbEUADk5sQgDERKwEzkwMRM0JDsBNTQmIyIGFSM0PgEzMhYXERQXFSMmJwYjIiY3FBYzMjY3NSMiBloBAe+VXmBTavN2y32+4gMp+BAMdKijzvNdTkh/IIOHiAEvrblHVGVTQFmbWL+t/hiSVxEfRnm6okZTRjvMXgAAAgB8/+wEMgYAAA8AGwBfALIAAAArsgwAACuxEgjpsgUBACuxGQjpsAEvAbAcL7AA1rEQEemwAjKxDw7psBAQsRUBK7EJEemxHQErsRAPERKwDjmwFRGxBQw5OQCxEgARErAOObEFGRESsAM5MDEzETMRNjMyEhEVFAIjIicHExYzMjY3NTQmIyIHfPNpssbi4cW+agwXQZ9yfAJ8dp5ABgD90nz+2v74Dvz+1ol1AT+NqqwfsLCKAAEAT//sA/UETgAcAFYAshoAACuxEgfpshIaCiuzQBIWCSuyBAEAK7ELB+myCwQKK7NACwcJKwGwHS+wANaxDxHpsA8QsRUBK7AIMrEWD+mwBzKxHgErsRUPERKxBBo5OQAwMRM1NAAzMhYXIy4BIyIGBxUUFjMyNjczDgIjIgBPAQjkwfMG5QR3XHaAAX94W3gE5QR2ynXj/vYCFRn3ASnht114q64nsK1qTmWvZgEmAAAAAAIAT//sBAMGAAAOABkAaQCyCQAAK7IMAAArsRII6bIDAQArsRcI6bAGLwGwGi+wANaxDxHpsA8QsRQBK7AFMrEIEemwCBCxCQ7psAkvsRsBK7EUDxESsQMMOTmwCRGwCjkAsRIJERKwCjmwFxGwADmwAxKwBTkwMRM0EjMyFxEzESMnBiMiAjcUFjMyNxEmIyIGT+jDrGrz3Axttr7r8391lUVDlXaAAiX6AS94Air6AHCEATLypbmFAc6CuwAAAAIAU//sBAsETgAVAB0ATwCyEwAAK7ENB+myBQEAK7EbB+m0FgoTBQ0rsRYF6QGwHi+wF9axCBDpshcICiuzQBcACSuxHwErsQgXERKxDxA5OQCxCg0RErEPEDk5MDETNTQSNjMyEhEVIR4BMzI3Fw4BIyIAEyE1LgEjIgZTfeKL3fH9PQudd6dpg0HZh+f+4fkBzwhyZWR7AgEeogD/jv7m/v5ihpyHfWFrASMBcxJ6fYwAAAEALQAAAtYGFQAUAFgAshMAACuyAQEAK7AOM7EABemwEDKwCy+xBgjpAbAVL7AT1rACMrESEemwDTKyEhMKK7NAEhAJK7ITEgors0ATAAkrsRYBKwCxCwERErAJObAGEbAIOTAxEzUzNTQ2MzIXByYjIh0BMxUjESMRLaXItEBIBig1rtzc8wOGtGO0xBK+CLNgtPx6A4YAAgBS/lYEDAROABkAJACEALIXAAArsR0I6bIGAQArsgMBACuxIgjpsAsvsREH6QGwJS+wANaxGhHpsBoQsRQBK7AfMrEIEemwCBCxBg7psAYvsSYBK7EaABESsQ4POTmwFBGzAxELFyQXObAGErAFOQCxEQsRErAOObAXEbAPObAdErAVObAiEbAAObAGErAFOTAxEzQSMzIXNzMRFAQjIiYnNxYzMjY9AQYjIgI3FBYzMjcRJiMiBlLtxLlqC9v+9+F34ztzcKR5jGmvvvHyhXaTR0WTeIUCJfwBLYFt++fV9mNQkoWDf0l1AS72o7t+Adx7vgAAAAABAHkAAAP4BgAAEABFALIAAAArsAgzsgUBACuxDQjpsAEvAbARL7AA1rEQEemwAjKwEBCxCQErsQgR6bESASuxCRARErAFOQCxBQ0RErADOTAxMxEzETYzIBMRIxE0JiMiBxF583e2AVoF82FekkgGAP3Eiv51/T0CunBdgvz7AAIAfQAAAZAF1QAJAA0APwCyCgAAK7ILAQArsAgvsQML6QGwDi+wANaxBRTpsQUU6bMKBQAIK7ENEemxDwErsQ0KERKzAwcIAiQXOQAwMRM0NjIWFRQGIiYTETMRfUeESEiERw/zBVM4Sko4N0lJ+uQEOvvGAAAAAAL/tf5LAYUF1QAMABYASwCyBQEAK7AKL7ECCOmwFS+xEAvpAbAXL7AE1rEHEemwEjKwBxCxDRTpsA0vsRgBK7EHBBESsQ8VOTkAsQIKERKwDDmwBRGwADkwMQcWMzI3ETMRFAYjIicTNDYyFhUUBiImSyYweQPzpZ9DPr1HhEhIhEfkCYQEo/tmpq8RBvc4Sko4N0lJAAAAAQB9AAAENgYAAAwAMACyAAAAK7AIM7IFAQArsAEvAbANL7AA1rEMEemwAjKxDgErALEFABESsQMKOTkwMTMRMxE3ASEJASEBBxF980wBKwEk/m4Bvf7n/r9sBgD8il8BUf49/YkB0G/+nwAAAQCMAAABfwYAAAMAHwCyAAAAK7ABLwGwBC+wANaxAxHpsQMR6bEFASsAMDEzETMRjPMGAPoAAAABAHwAAAZ5BE4AHQBwALIAAAArsQ0WMzOyAQEAK7IFAQArsAkzsRoI6bASMgGwHi+wANaxHRHpsAIysB0QsRcBK7EWEemwFhCxDgErsQ0R6bEfASuxHQARErADObAXEbAFObAWErAHObAOEbEJEjk5ALEBGhESsQMHOTkwMTMRMxc2MzIXNjMyFhcRIxE0JiMiBgcTIxEmIyIHEXzlB3LG2VB21rOvAvNaaFNpFQHzBb6SPQQ6cYWmpsbB/TkCwGdgWUj9GgLIv3f88AABAHkAAAP4BE4AEABNALIAAAArsAgzsgEBACuyBQEAK7ENCOkBsBEvsADWsRAR6bACMrAQELEJASuxCBHpsRIBK7EQABESsAM5sAkRsAU5ALEBDRESsAM5MDEzETMXNjMgExEjETQmIyIHEXnlB3jDAVIG81llk0gEOn2R/n39NQK9Z2OF/P4AAgBP/+wEPQROAA8AGgBAALINAAArsRMH6bIFAQArsRgH6QGwGy+wANaxEBHpsBAQsRUBK7EJEemxHAErsRUQERKxBQ05ObAJEbAHOQAwMRM1NBI2MzIAHwEUDgEjIgA3FBYyNjU0JiMiBk9+5JTbARELAXvlluX+7fOK9omNeXeMAhsMnwD/if7m6Tmg/IoBMfWnvcC5pMC9AAAAAgB8/mAEMAROAA8AGgBfALIMAAArsRIH6bIBAQArsgUBACuxGAjpsAAvAbAbL7AA1rEPEemwEDKxAg/psA8QsRUBK7EJEemxHAErsQ8CERKwAzmwFRGxDAU5OQCxEgwRErAOObEBGBESsAM5MDETETMXNjMyEhEVFAIjIicZARYzMjY1NCYjIgd84ApruMbh5MCya0KWdIOBeJVB/mAF2m6C/tn++g/7/tV1/f8CzH67vqK+ewAAAAIAT/5gBAIETgAOABkAaQCyDAAAK7ESB+myBgEAK7IDAQArsRcH6bAJLwGwGi+wANaxDxHpsA8QsQkBK7AUMrEIEemwCBCxBg3psAYvsRsBK7EJDxESsQMMOTmwBhGwBTkAsRIMERKwCjmwFxGwADmwBhKwBTkwMRM0EjMyFzczESMRBiMiAjcUFjMyNxEmIyIGT+jGtWoO2PNqqsLq84N0kEZGjnSFAib+ASp/a/omAfxwAS/2pr17Aex2ugAAAAEAfAAAArQETgANADQAsgAAACuyAQEAK7AHM7IFAQArsQoK6QGwDi+wANaxDRHpsAIysQ8BKwCxAQoRErADOTAxMxEzFzYzMhcHJiMiBxF86AZYnDQiATAzpzoEOnmNDuQIgP0cAAAAAQBL/+wDygROACYAbQCyIwAAK7EEBemyBCMKK7NABAAJK7IQAQArsRcF6bIXEAors0AXEwkrAbAnL7AN1rEaEOmwACDWEbEBEOmwGhCxBwErsBQysSAQ6bATMrEoASuxBxoRErQEChAdIyQXOQCxFwQRErENIDk5MDETMx4BMzI2NTQuAScmNTQ2MzIWFSM0JiMiBhUUFgQeARUUBiMiLgFL7AV4Y2Bka/hTtuy2wu/zaFZQZV4BHqNP8sSF0HQBVVZdSTtBRDQoWKeMvMCZRl1KPjg+P1d6V5K1YKgAAAABAAj/7AJyBUEAFABjALIRAAArsQwI6bIBAQArsAUzsQAF6bAHMrIBAAors0ABBAkrAbAVL7AT1rACMrEJEemwBDKyCRMKK7NACQcJK7AOMrITCQors0ATAAkrsRYBKwCxDBERErAPObAAEbAOOTAxEzUzETMRMxUjERQWMzI3FQYjIBkBCLLzv78xPyorU03+6AOGtAEH/vm0/aQ+Nwq8FwE1AmUAAAABAHf/7AP3BDoAEABNALILAAArsg4AACuxBQjpsgEBACuwCDMBsBEvsADWsQMR6bADELEHASuwCzKxChHpsRIBK7EHAxESsA45sAoRsAw5ALEFCxESsAw5MDETETMRFDMyNxEzESMnBiMiJnfzq7E+8+UGa8WwtQF9Ar39Rs5/Awn7xmp+zgAAAQAWAAAD2gQ6AAYAPQCyBgAAK7IAAQArsAMzAbAHL7AA1rEBDOmwARCxAwErsQQM6bEIASuxAwERErEFBjk5ALEABhESsAI5MDETMxsBMwEjFvzo5fv+idMEOvz6Awb7xgAAAAEAIQAABcwEOgAMAJEAsgwAACuxCQszM7IAAQArsgMEBjMzMwGwDS+wANaxARDpsAEQsQYBK7EHEOmxDgErsDYauj1L7ZYAFSsKsAMuDrACwLEKBfkFsAvAusK47YsAFSsKsAkusQsKCLAKwA6xBRj5BbAEwAMAsgIFCi4uLgG2AgMEBQkKCy4uLi4uLi6wQBqxBgERErEIDDk5ADAxEzMbATMbATMBIwsBIyHtr9634azt/tnI6OTIBDr9HQLj/RUC6/vGAuf9GQAAAAEAHwAAA+gEOgALACYAsgAAACuwCDOyAgEAK7AFMwGwDC+xDQErALECABESsQQKOTkwMTMJASEbASEJASELAR8BVv62AQzKzgEO/rUBVv702NcCJQIV/pwBZP3r/dsBcv6OAAABAAz+SwPWBDoADwBNALIAAQArsAMzsAcvsQsD6QGwEC+wANaxARPpsAEQsQMBK7EEE+mxEQErsQEAERKyBwkKOTk5sAMRsA85ALELBxESsAk5sAARsAI5MDETIRsBIQECIyInNRcyNj8BDAEG5dwBA/5SY+01QC5cXRsjBDr9IgLe+yL+7xK8A0NPXQAAAAABAFIAAAPABDoACQAuALIAAAArsQcH6bIEAQArsQMH6QGwCi+xCwErALEHABESsAE5sQQDERKwBjkwMTM1ASE1IRUBIRVSAiX95QNP/dUCQJ8C18Sa/SLCAAAAAAEAOP6YApEGPQAXADAAsAAvsQEF6QGwGC+wFdawAzKxEA/psAoysRkBK7EQFRESsA05ALEBABESsA05MDETNTI9AT4BNxcGBxUUBxYdARYXByQDNTQ4wQO1sDCtBq2tBq0w/p8HAhGy4tS03jKMOPrY4Vtc49X6OI1jAWDV4QAAAQCu/vIBVQWwAAMAIgCyAQIAKwGwBC+wANa0Aw0AFQQrtAMNABUEK7EFASsAMDETETMRrqf+8ga++UIAAQAb/pgCdQY9ABgAMACwEi+xEQXpAbAZL7AC1rAHMrEVD+mwDjKxGgErsRUCERKwBTkAsRESERKwBTkwMRc2EzU0NyY9AQInNx4BHQEUMxUiHQEUBgcbsAS2tgSwMLaywsKztds5AP/Q51ZW6s8A/zmMM+W5yOGy4cW75TMAAAABAHUBgwTcAy8AFwBiALAPL7EIA+myCA8KK7NACAsJK7AUL7EDA+myFAMKK7NAFAAJKwGwGC+wANa0Fw0AFQQrsBcQsQsBK7QMDQAVBCuxGQErsQsXERKxAw85OQCxCA8RErASObEDFBESsAY5MDETNDYzMh4CMzI2NTMUBiMiLgIjIgYVdbaUSoWRQydDVLy+jkp9mkMmQ00BqavbO4QicFSw3ziJIWhUAAAAAgCG/pQBmQRNAAsADwBBALIDAQArsQkL6QGwEC+wANawDDKxBhTpsQYU6bAPMrMOBgAIK7ENDemwDS+xDg3psREBK7EODRESsQkDOTkAMDETNDYzMhYVFAYjIiYbATMThkhCQUhIQUJIDBjRGAPLN0tLNzhLS/sBBAL7/gAAAAABAGT/CwQKBSYAIABvALAdL7QUCwAKBCuwDi+0BQsACgQrAbAhL7AA1rEREemwERCxHQErsAQysRwN6bAGMrAcELEXASuwCzKxGA/psAoysSIBK7EcHRESsQ4UOTkAsRQdERKxGx45ObAOEbIKFxg5OTmwBRKxBAc5OTAxEzU0Ejc1MxUeARcjLgEjIgMHFBYzMjY3Mw4BBxUjNSYCZMy3yJ65BOQHdlvmEAF/eVl4BuQExZLIt8wCEhzVASAi4eAc2Jxgdf7ISLCtaFCIzRzq6iIBHwAAAAABAF4AAAR8BcMAHwCTALIZAAArsRoD6bAWMrIGAgArsQwD6bIMBgors0AMCAkrtAABGQYNK7AQM7EACOmwEjIBsCAvsB/WsAIysRMM6bAQMrADINYRsQ8M6bIDDwors0ADAAkrsB8QsRQM6bIUHwors0AUEgkrsBMQsQkBK7EIEemxIQErsQ8fERKxBRY5ObEJFBESsAw5sAgRsAY5ADAxEzUzJzQ2IBYVIzQmIyIGFRchFSEXFAchByE1Mz4BNSdemwj6AZbo9WleWWcJATf+0AdAArgB++dSJysHAlbH8srq2rhfaYJo8sewh1XKyglvW7kAAgBd/+UFTwTxABsAKAB/ALIYAAArsRUbMzOxIAbpsCYvsQoG6QGwKS+wA9a0HA0AFQQrsBwQsSMBK7QRDQAVBCuxKgErsRwDERKzAQUHGyQXObAjEbMIDBYaJBc5sBESsw0PExUkFzkAsSAYERKzFAAWGiQXObAmEbMBBQ8TJBc5sAoSswYIDA4kFzkwMT8BJjU0Nyc3FzYzMhc3FwcWFRQHFwcnBiMiJwcTFB4BMj4BNC4BIg4BXYdkbZCNjpvAwpuRjpRrYouOhJ/Lyp6BT26+3L5tbb3evm12iZzFyKWTkJFzdZSRl5/KwZyNkYZ/foQCenjOdXbO7sx1dcwAAAEACwAABDQFsAAWAHQAsg4AACuyAAIAK7ADM7QQEQ4ADSuwCTOxEATpsAsytBQVDgANK7AFM7EUBOmwBzIBsBcvsA7WsBIysQ0M6bAIMrINDgors0ANBwkrsAoysg4NCiuzQA4UCSuwEDKxGAErsQ0OERKwAjkAsQAVERKwAjkwMRMhCQEhATMVIRUhFSERIxEhNSE1ITUzCwERAQUBBgEN/qvq/tEBL/7R/P7MATT+zPgFsP2fAmH9NpiKl/7TAS2XipgAAAAAAgCI/vIBbQWwAAMABwAiALIFAgArAbAIL7AA1rAEMrEDD+mwBjKxAw/psQkBKwAwMRMRMxEDETMRiOXl5f7yAxv85QPIAvb9CgAAAAIAWv4mBIwFxAAvAD0AlACyFgIAK7EdB+myHRYKK7NAHRkJK7AtL7EEB+kBsD4vsA7WsAAysTAR6bABMrATINYRsSAR6bAwELE3ASuxJhDpsCYQsCog1hGxBxHpsAcvsBozsSoR6bEZEemxPwErsTATERKwEDmxByAREkAJBAsWHSMtNTo8JBc5sSo3ERKwKDkAsR0EERK1AAETKjU8JBc5MDEXNxQWMzI2NTQmJy4CNTQ3LgE1NCQzMgQVIzQmIyIGFRQWBB4BFRQHFhUUBCMiJBMUFh8CNjU0JicmJwZa8pyIeY2Gu7y+XalBRAET5vABDPOReHuLeAGDwlqrh/7y6vb+4PZjlbMuc4i7UUxsMgFueF9PTVs3M26abbhaMohkqszhzGqAX1JUV2hxmWy4WWS5rcbZAy9RVi81EC91UWE4FRwoAAACAF0E3wMjBcwACAARADkAsAcvsA8zsQMK6bALMrEDCukBsBIvsADWsQUM6bAFELEJASuxDgzpsRMBKwCxAwcRErEJDjk5MDETNDYyFhQGIiYlNDYyFhQGIiZdQ3ZERHZDAclDdkREdkMFVjJERGRERDEyRERkREQAAAAAAwBX/+wF4gXEAA0AGwA2ALgAsgoAACu0EgQADwQrsgQCACu0GQQADwQrtDUuCgQNK7Q1BAAPBCuyLjUKK7NALjIJK7QgJwoEDSu0IAQADwQrsicgCiuzQCcjCSsBsDcvsADWtA8NAA0EK7APELEcASu0Kw0ADQQrsCsQsTEBK7AkMrQyDQANBCuwIzKwMhCxFQErtAcNAA0EK7E4ASuxMSsREkAJAxESGQonIDQ1JBc5sDIRsAQ5ALEnLhEStQYHDg8VACQXOTAxEzQSJCAEEhACBCMiJAISEBIEICQSNTQCJCMiBBM1NDYzMhYVIzQmIyIGHQEUFjMyNjUzFAYgJle7AUsBgAFKu7v+uMLB/re8epsBEQFAAROYlv7uo5/+70W/nqOtnFxYXGdoW1lanK/+wL0C2coBWsfH/qb+bP6mycgBWgF1/qz+4KeqASCnpgEdq6T+AHGu1aWVYFOIdnV2hlFimKLVAAAAAAIAjQKzAxEFxAAaACQAgQCyDgIAK7EHBOmwGC+xHQTpsCIvtAMEAA8EKwGwJS+wANa0Gw0AFQQrsAoysBsQtAsNABUEK7ALL7AbELEgASuwBDK0Eg0AFQQrsSYBK7EgGxESsQ4YOTmwEhGxFRY5OQCxHRgRErEUFjk5sCIRsRIAOTmxBwMRErIKCxE5OTkwMRM0NjsBNTQjIgYVJzQ2MzIWFREUFyMnBiMiJjcUMzI2NzUjDgGNqK1mdEFJra+IiZoasRFNfHaDr3UoVBtqTFYDl255M38zMA5ogZGE/sRhUURSe21YJBmJATwAAgBXAIoDhQOpAAYADQAAEzUBMwMTIxM1ATMDEyNXASCn9/enRwEgp/f3pwIQEwGG/nD+cQGGEwGG/nD+cQAAAAEAfwF2A8IDJQAFADAAsAAvsQEF6bIAAQors0AABAkrAbAGL7AE1rEDDemyBAMKK7NABAAJK7EHASsAMDETNSERIxF/A0PIAnqr/lEBBAAAAQBHAgkCVALNAAMAIgCwAC+xAQfpsQEH6QGwBC+xAAErtAMVAAgEK7EFASsAMDETNSEVRwINAgnExAAABABX/+wF4gXEAA0AGwAxADoAygCyCgAAK7QSBAAPBCuyBAIAK7QZBAAPBCu0MDIKBA0rtDAEAA8EK7IwMgors0AwHAkrsCkytB46CgQNK7QeBAAPBCsBsDsvsADWtA8NAA0EK7APELEcASu0MQ0ADQQrsDIysDEQsTYBK7AqMrQhDQANBCuwKDKwIRCxFQErtAcNAA0EK7E8ASuxMRwRErEDETk5sDYRshIZCjk5ObAhErMEIyUmJBc5ALEwEhESsgcPJTk5ObAyEbIVACM5OTmwOhKyBg4hOTk5MDETNBIkIAQSEAIEIyIkAhIQEgQgJBI1NAIkIyIEExEhMhYVFAceARQWFxUjJjU0JisBGQEzMjY1NCYnI1e7AUsBgAFKu7v+uMLB/re8epsBEQFAAROYlv7uo5/+74kBGZmseEE0BwqbDUJNno9FXUddjQLZygFax8f+pv5s/qbJyAFaAXX+rP7gp6oBIKemAR2rpPyZA1KHfXU/HW+jRBcQIqBMQ/6vAdc+NkY7AQAAAQCbBQwDSgWqAAMAFwCwAC+xAQTpsQEE6QGwBC+xBQErADAxEzUhFZsCrwUMnp4AAgB/A68CiwXEAAkAEwBUALIDAgArsRME6bINAQArsQgE6bIAAAArsgYAACsBsBQvsAHWtAsNAA0EK7ALELEQASu0Bg0ADQQrsRUBK7EQCxESsQgDOTkAsRMNERKxAQU5OTAxEjQ2MzIWFAYjIgIUFjMyNjU0JiJ/nWtqmphsbRBJNDVFRWoEStyentybAT1oSEc1NEwAAAACAF8AAQPzBPwACwAPAFsAsgwAACuxDQfpsAAvsAczsQEI6bAFMrIAAQors0AACgkrsgEACiuzQAEDCSsBsBAvsArWsAIysQkN6bAEMrIJCgors0AJBwkrsgoJCiuzQAoACSuxEQErADAxEzUhETMRIRUhESMRATUhFV8BZdgBV/6p2P65A1ECvMcBef6Hx/58AYT9RcTEAAEAPAKbArIFuwAXAG8AsgMCACuxFATpshQDCiuzQBQACSuwDS+xCgTpAbAYL7AA1rQXDQAVBCuwFxCxEQErtAYNABUEK7IGEQors0AGDAkrshEGCiuzQBENCSuxGQErsREXERKxAwo5OQCxCg0RErAOObAUEbEGETk5MDETNDYzMhYVFA8CIRUhNQE2NTQmIyIGFTyph4+camKMAXP9nAEdcTY0OkIErnSZgHNrZldxlH0BBWdDKjVCNgAAAQA3ApACqQW7ACQAjwCyGAIAK7ERBOmyERgKK7NAERUJK7AiL7EEBOmyBCIKK7NABAAJK7AKL7QLBAAPBCsBsCUvsADWsBUytAENABUEK7AUMrABELEHASuwDjK0Hw0AFQQrsBsysgcfCiuzQAcKCSuxJgErsQcBERKxGCI5ObAfEbAdOQCxCgQRErAfObALEbAdObARErAbOTAxEzMUFjMyNjU0JyM1MzI1NCYjIgYVIzQ2MzIWFRQHFhUUBiMiJje6RTw/PYZcUYQ2PjBBuqWCj6OHlbGPh6sDgCY1NyplAYFhIzUnI2N8eWl3MymOan5/AAEAcATRAkgGAAADACAAsAAvtAELAA4EKwGwBC+wANa0AhUACQQrsQUBKwAwMRsBIQFwwwEV/usE0QEv/tEAAAABAJL+YAQfBDoAEgBSALIMAAArsg8AACuxBgfpsgEBACuwCTOwAC8BsBMvsADWsRIR6bACMrASELEIASuxCxHpsRQBK7EIEhESsA85sAsRsA05ALEGDBESsQ0ROTkwMRMRMxEeATMyNxEzESMnBiMiJxGS8gJZaqg7898HXJN5Tf5gBdr9hI2CeQMS+8ZWazf+PgAAAQBFAAADVgWwAAoANwCyBgAAK7IDAgArAbALL7AA1rQEFQAHBCuwBBCxBg3psAYvsAQQtAAVAAcEK7AAL7EMASsAMDETNAAzIREjESMiJEUBCuYBIdJQ5v73A9zVAP/6UAII/gAAAAABAI4CRQGpA1IACgAiALAIL7EDC+mxAwvpAbALL7AA1rEFFemxBRXpsQwBKwAwMRM0NjIWFRQGIyImjkqGS05AQUwCyjpOTjo7SkoAAQBt/kEByQADAA4APACwCC+0CQQADwQrsAAvsQEE6QGwDy+wDNaxBQ3psRABK7EFDBESsQMCOTkAsQAJERKwBTmwARGwAzkwMRc3MwcWFRQGIycyNjU0Jm0gsQuWrJsHQkdHiIs2G5JpdokvKi0jAAEAgAKbAgIFrgAGAEMAsAAvsQEE6bIBAAors0ABAgkrAbAHL7AF1rQEDQAVBCuyBQQKK7NABQEJK7EIASuxBAURErACOQCxAQARErAGOTAxEzUlMxEjEYABbxO5BKWSd/ztAjoAAAAAAgB3ArIDLAXEAAwAGgBAALIEAgArsRcE6bAKL7EQBOkBsBsvsADWtA0NABUEK7ANELETASu0Bw0AFQQrsRwBK7ETDRESsgMECjk5OQAwMRM1NDYgFh0BFAYjIiY3FBYzMjY3NTQmIyIGFXe/ATbAvJ2evq9dUE5bAV1PTl0EGUigw8KmSJ/DxJ5ibmxhUGFubWYAAAIAXQCKA5kDqQAGAA0AADcTAzMBFQEzEwMzARUBXff3pwEg/uDO9/enASD+4IoBjwGQ/noT/noBjwGQ/noT/noAAAAABABZAAAFgwWrAAYACgAVABkAsACyEwAAK7AVL7AQM7EWBOmwDjKyFhUKK7NAFgwJK7AAL7EBBOmwCDKyAQAKK7NAAQIJKwGwGi+wBda0BA0AFQQrsgUECiuzQAUBCSuwBBCxEwErsBcytBINABUEK7ANMrITEgors0ATCwkrsRsBK7EEBRESsgIHCjk5ObATEbIIDBY5OTmwEhKwCTkAsRUTERKwCjmwFhGxBws5ObAAErIEBRg5OTmwARGxBgk5OTAxEzUlMxEjERMBFwElATMRMxUjFSM1ITczNQdZAW8TuSYCx339OQE1AW29X1+7/pqsug4EopJ3/O0COvvrBHJI+46nAfn+JZejo5fyFgADAFAAAAXMBa4ABgAKACIAxwCyGAAAK7EVBOmwHy+xDgTpsh8OCiuzQB8LCSuwAC+xAQTpsgEACiuzQAECCSsBsCMvsAXWsAcytAQNABUEK7IFBAors0AFAQkrsAQQsQsBK7QiDQAVBCuwIhCxHAErtBENABUEK7IRHAors0ARFwkrshwRCiuzQBwYCSuxJAErsQQFERKxAgo5ObEiCxESsAg5sBwRsg4VCTk5OQCxFRgRErEKGTk5sB8RsgcRHDk5ObAOErEFBDk5sQEAERKyBggJOTk5MDETNSUzESMREwEXCQE0NjMyFhUUDwIhFSE1ATY1NCYjIgYVUAFvE7kEAsd9/TkBvKmHj5xqYowBc/2cAR1xNjQ6QgSlknf87QI6++gEckj7jgGedJmAc2tmV3GUfQEFZ0MqNUI2AAAAAAQAZwAABfwFuwAkACgAMwA3AQkAsjEAACuyGAIAK7ERBOmyERgKK7NAERUJK7QzNDEYDSuwLDOxMwTpsC4ysjQzCiuzQDQqCSu0IgQxGA0rsSIE6bIEIgors0AEAAkrtAsKMRgNK7QLBAAPBCsBsDgvsADWsBUytAENABUEK7AUMrABELEHASuwDjK0Hw0AFQQrsBsysgcfCiuzQAcKCSuwHxCxMQErsDUytDANABUEK7ArMrIxMAors0AxKQkrsTkBK7EHARESshgiJTk5ObAfEbEdKDk5sDESsiYqNDk5ObAwEbAnOQCxMzERErAoObA0EbElKTk5sCISsDY5sQoEERKwHzmwCxGwHTmwERKxGyc5ObAYEbAmOTAxEzMUFjMyNjU0JyM1MzI1NCYjIgYVIzQ2MzIWFRQHFhUUBiMiJgkBFwElATMRMxUjFSM1ITczNQdnukU8Pz2GXFGENj4wQbqlgo+jh5Wxj4erAW4Cx339OQEhAW29X1+7/pqsug4DgCY1NyplAYFhIzUnI2N8eWl3MymOan5//a4Eckj7jqcB+f4ll6Ojl/IWAAAAAAIAQv5/A6UETgAZACMAgwCyAAAAK7ENEzMzsh0BACuxIgvpsBcvsRAD6QGwJC+wANaxDRHpsA0QsQUBK7EHD+mwBxCzLQcfDiuxGhTpsBovsR8U6bAHELETASuxFBHpsSUBK7ENABESsAI5sBoRsAM5sAUSsQQLOTmwBxG2ChAXHB0hIiQXOQCxIgARErAGOTAxMzQ/ATY/ATMOAQ8BBhUUFjMyNjUzDgEjIiYBNDYyFhUUBiImQptcTgoC4wI1SWdaYllYavMC78LO4gE1SIRHR4RIpaNdSHM1fJFPamFqXl1kU7HQyQSEN0tLNzhLSwAAAAADABIAAAVCBzYABwALAA4ALACyAAAAK7ADM7IBAgArtAYMAAENK7EGA+kBsA8vsRABKwCxAQwRErAOOTAxMwEzASEDIQMTIRMjAyEDEgIm4wIn/vh3/cx2OwEVw8qMAabTBbD6UAFT/q0HNv7R/BgCXAAAAAMAEgAABUIHNgAHAAoADgAsALIAAAArsAMzsgECACu0BggAAQ0rsQYD6QGwDy+xEAErALEBCBESsAo5MDEzATMBIQMhAxMhCwETIQESAibjAif++Hf9zHa9AabTd8MBFf7rBbD6UAFT/q0CHwJcAYwBL/7RAAAAAAMAEgAABUIHNwAHABAAEwAsALIAAAArsAMzsgECACu0BhEAAQ0rsQYD6QGwFC+xFQErALEBERESsBM5MDEzATMBIQMhAxM1ATMBFSMnBwMhAxICJuMCJ/74d/3Mdj4BD48BEcOWlUIBptMFsPpQAVP+rQYWDQEU/uoLnJz8CQJcAAAAAAMAEgAABUIHLAAHAB0AIAB6ALIAAAArsAMzsgECACu0Bh4AAQ0rsQYD6bAVL7EOBOmzGg4VCCuxCwTpAbAhL7AI1rQdDQANBCuwHjKwHRCxEQErtBINAA0EK7EiASuxHQgRErAGObAREbQBCwIVHyQXObASErAFOQCxAR4RErAgObAVEbEIHTk5MDEzATMBIQMhAxM0NjMyFjMyNjUXFAYjIi4CIyIGFRMhAxICJuMCJ/74d/3MdiZ/XzmhNCY2lX9gJzlpKxomNQIBptMFsPpQAVP+rQYabpZaOS8MbpIRPAw5LvwNAlwAAAAABAASAAAFQgcCAAcAEAATABwAcQCyAAAAK7ADM7IBAgArtAYRAAENK7EGA+mwDy+wGjOxCwrpsBYyAbAdL7AI1rENDOmwDRCxFAErsRkM6bEeASuxDQgRErIBBhE5OTmwFBGwEzmwGRKyAgUSOTk5ALEBERESsBM5sQsPERKxFBk5OTAxMwEzASEDIQMTNDYyFhQGIiYTIQMTNDYyFhQGIiYSAibjAif++Hf9zHYyQ3ZERHZDiwGm02tDdkREdkMFsPpQAVP+rQaMMkREZERE+8UCXAIQMkREZEREAAQAEgAABUIHlAAHABEAFAAfAIAAsgAAACuwAzOyAQIAK7QGEgABDSuxBgPpsBAvtBgEAA8EK7AeL7QLBAAPBCsBsCAvsAnWtBUNAA0EK7AVELEbASu0Dg0ADQQrsSEBK7EVCRESsQESOTmwGxGzAhAUCyQXObAOErATOQCxARIRErAUObEeGBESswgNDgkkFzkwMTMBMwEhAyEDEjQ2MzIWFAYjIgMhCwEUFjMyNjU0JiIGEgIm4wIn/vh3/cx2t39fXYB9YGF3AabTa0IuL0E/Yj8FsPpQAVP+rQZvqnt7qnj8KAJcAkkvQUAwLkNDAAL/9gAAB1cFsAAPABIAfACyDAAAK7AAM7EJB+myAQIAK7EECOm0DhAMAQ0rsQ4J6bQFCAwBDSuxBQjpAbATL7AS1rEEEemwBBCwCCDWEbEREOmwES+wDTOxCBDpsAUysQkM6bIJEQors0AJBwkrs0AJCgkrsRQBK7EEERESsAw5ALEEBRESsBI5MDEjASEVIRMhFSETIRUhAyEDASEDCgNDA+D9ehECJP3kFAKX/H4P/gq4ASwBeRsFsMX+aMX+NsQBVP6sAisCiAAAAAIAZv48BOsFxAAdACwAigCyGgAAK7QfBAAPBCuyBQIAK7EMA+myDAUKK7NADAkJK7AmL7QnBAAPBCsBsC0vsADWsRAM6bAQELEqASuxIw3psCMQsRYBK7AJMrEXDOmwCDKxLgErsSoQERK3DAUTGh4fJickFzmwIxGxISA5OQCxGicRErIeISM5OTmxDB8RErITFhc5OTkwMRM1NBIkMzIAFyMuASMiBgcVFBYzMjY3MwYAIyIkAgE3MwcWFRQGIycyNjU0JmaSARGz8QEmGPwSk46lsQKpo5WWFPwW/tT5rv73kAHNILELlqybB0JHRwKKiM4BOqr++u+di/Hpgez4hpzp/vulATD9sos2G5JpdokvKi0jAAACAJQAAARMBz0ACwAPAE8AsgAAACuxCQPpsgECACuxBAPptAUIAAENK7EFCOkBsBAvsADWsQkM6bAEMrIJAAors0AJAwkrsAoys0AJBwkrsREBK7EJABESsAw5ADAxMxEhFSERIRUhESEVASETI5QDsf1MAlb9qgK7/M0BFcPKBbDM/m7I/kDKBz3+0QAAAAACAJQAAARMBz0ACwAPAEcAsgAAACuxCQPpsgECACuxBAPptAUIAAENK7EFCOkBsBAvsADWsQkM6bAEMrIJAAors0AJAwkrsAoys0AJBwkrsREBKwAwMTMRIRUhESEVIREhFQETIQGUA7H9TAJW/aoCu/2rwwEV/usFsMz+bsj+QMoGDgEv/tEAAgCUAAAETAc+AAsAFABRALIAAAArsQkD6bIBAgArsQQD6bQFCAABDSuxBQjpAbAVL7AA1rEJDOmwBDKyCQAKK7NACQMJK7AKMrNACQcJK7EWASuxCQARErEMDTk5ADAxMxEhFSERIRUhESEVATUBMwEVIycHlAOx/UwCVv2qArv80AEPjwERw5aVBbDM/m7I/kDKBh0NART+6gucnAAAAAMAlAAABEwHCQALABQAHQCHALIAAAArsQkD6bIBAgArsQQD6bQFCAABDSuxBQjpsBMvsBszsQ8K6bAXMgGwHi+wANaxCQzpsAQysgkACiuzQAkDCSuwCjKzQAkHCSuwABCwDCDWEbERDOmwCRCxFQErsRoM6bEfASuxCQwRErEOEzk5sBERsQ8SOTkAsQ8TERKxFRo5OTAxMxEhFSERIRUhESEVATQ2MhYUBiImJTQ2MhYUBiImlAOx/UwCVv2qArv8xEN2RER2QwHJQ3ZERHZDBbDM/m7I/kDKBpMyRERkREQxMkREZEREAAAAAv/IAAABoAc9AAMABwAqALIEAAArsgUCACsBsAgvsATWsQcM6bACMrEJASuxBwQRErEDATk5ADAxAyETIwMRMxE4ARXDyjP8Bz3+0fnyBbD6UAAAAgCjAAACfQc9AAMABwAqALIAAAArsgECACsBsAgvsADWsAQysQMM6bEJASuxAwARErEFBzk5ADAxMxEzEQMTIQGj/PrDARX+6wWw+lAGDgEv/tEAAv/LAAACegc+AAgADAApALIJAAArsgoCACsBsA0vsAnWsQwM6bEOASuxDAkRErIDAgc5OTkAMDEDNQEzARUjJwcTETMRNQEPjwERw5aVF/wGHQ0BFP7qC5yc+eMFsPpQAAAAAAP/vwAAAoUHCQAIAAwAFQBjALIJAAArsgoCACuwBy+wEzOxAwrpsA8yAbAWL7AJ1rEMDOmzBQwJCCuxAAzpsAAvsQUM6bMNDAkIK7ESDOmxFwErsQkAERKxAwY5ObESDBESsQ8UOTkAsQMHERKxDRI5OTAxAzQ2MhYUBiImExEzEQM0NjIWFAYiJkFDdkREdkPk/BdDdkREdkMGkzJERGRERPmfBbD6UAaSMkREZEREAAAAAAL/9wAABPAFsAAPAB0AXQCyDQAAK7EQA+myBAIAK7EZA+m0AQANBA0rsBwzsQEF6bAaMgGwHi+wDtawAjKxEAzpsBkyshAOCiuzQBAcCSuyDhAKK7NADgAJK7AQELEUASuxCQzpsR8BKwAwMQM1MxEhMgQSHQEUAgQjIRETMzI2PQE0JisBETMVIwm7Aa7BASukpf7Pxf5d/aPL1c7EseXlAoyqAnqs/sTMSc/+xqoCjP4+/fBG7fr+UqoAAgCUAAAFFwcsAAkAHwCNALIAAAArsAYzsgECACuwBDOwFy+xEATpsxwQFwgrsQ0E6QGwIC+wANaxCQzpswoJAAgrtB8NAA0EK7AJELEDASuxBgzpsxQGAwgrtBMNAA0EK7ATL7QUDQANBCuxIQErsQkKERKwAjmxEx8RErENFzk5sAMRsAc5ALEBABESsQMIOTmwFxGxCh85OTAxMxEzAREzESMBEQM0NjMyFjMyNjUXFAYjIi4CIyIGFZT9Aov7/f13KX9fOaE0JjaVf2AnOWkrGiY1BbD78wQN+lAECfv3Bhpullo5LwxukhE8DDkuAAAAAAMAZv/sBR4HNgAQAB4AIgA+ALINAAArsRQJ6bIFAgArsRsJ6QGwIy+wANaxEQzpsBEQsRcBK7EJDOmxJAErsRcRERK0BQQNHyEkFzkAMDETNTQSJCAEEhcVFAIEIyIkAjcUEjMyEj0BNAIjIgIHEyETI2aXARMBZAETlgGU/u2zsf7rl/y7pqi1t6ikuQIIARXDygKqUtUBRq2r/r/VUdb+va2tAUDZ8P76AQD2TPIBAv7/6wQw/tEAAAAAAwBm/+wFHgc2ABAAHgAiAD4Asg0AACuxFAnpsgUCACuxGwnpAbAjL7AA1rERDOmwERCxFwErsQkM6bEkASuxFxERErQFBA0fISQXOQAwMRM1NBIkIAQSFxUUAgQjIiQCNxQSMzISPQE0AiMiAgcbASEBZpcBEwFkAROWAZT+7bOx/uuX/LumqLW3qKS5AubDARX+6wKqUtUBRq2r/r/VUdb+va2tAUDZ8P76AQD2TPIBAv7/6wMBAS/+0QADAGb/7AUeBzcAEAAeACcAPgCyDQAAK7EUCemyBQIAK7EbCekBsCgvsADWsREM6bARELEXASuxCQzpsSkBK7EXEREStAUEDR8jJBc5ADAxEzU0EiQgBBIXFRQCBCMiJAI3FBIzMhI9ATQCIyICBxM1ATMBFSMnB2aXARMBZAETlgGU/u2zsf7rl/y7pqi1t6ikuQILAQ+PARHDlpUCqlLVAUatq/6/1VHW/r2trQFA2fD++gEA9kzyAQL+/+sDEA0BFP7qC5ycAAMAZv/sBR4HLAAQACYANAB/ALINAAArsSoJ6bIFAgArsTEJ6bAeL7EXBOmzIxceCCuxFATpAbA1L7AA1rEnDOmzEScACCu0Jg0ADQQrsCcQsS0BK7EJDOmzGwktCCu0Gg0ADQQrsBovtBsNAA0EK7E2ASuxGiYRErYEBRQNHioxJBc5ALEeBRESsREmOTkwMRM1NBIkIAQSFxUUAgQjIiQCEzQ2MzIWMzI2NRcUBiMiLgIjIgYVAxQSMzISPQE0AiMiAgdmlwETAWQBE5YBlP7ts7H+65fvf185oTQmNpV/YCc5aSsaJjWIu6aotbeopLkCAqpS1QFGrav+v9VR1v69ra0BQARBbpZaOS8MbpIRPAw5Lvyg8P76AQD2TPIBAv7/6wAEAGb/7AUeBwIAEAAZACcAMACCALINAAArsR0J6bIFAgArsSQJ6bAYL7AuM7EUCumwKjIBsDEvsADWsRoM6bMRGgAIK7EWDOmwGhCxIAErsQkM6bMtCSAIK7EoDOmwKC+xLQzpsTIBK7EWGhESshMEGDk5ObAoEbINHSQ5OTmwIBKyBSsuOTk5ALEUGBESsSgtOTkwMRM1NBIkIAQSFxUUAgQjIiQCEzQ2MhYUBiImExQSMzISPQE0AiMiAgcBNDYyFhQGIiZmlwETAWQBE5YBlP7ts7H+65f7Q3ZERHZDAbumqLW3qKS5AgHIQ3ZERHZDAqpS1QFGrav+v9VR1v69ra0BQASzMkREZERE/Fjw/voBAPZM8gEC/v/rA4UyRERkREQAAQBNANYD7ASGAAsAABMJATcJARcJAQcJAU0BPP7ElAE7ATyU/sQBPJT+xP7FAWwBQgFClv6+AUKW/r7+vpYBQf6/AAADAGn/oQUiBe4AFwAgACkAZQCyEQAAK7EjCemyBQIAK7EdCekBsCovsADWsRgM6bAYELEmASuxDQzpsSsBK7EYABESsBQ5sCYRtQcREwUbISQXObANErAIOQCxIxERErETFjk5sB0RsRopOTmwBRKxBwo5OTAxEzU0EiQzMhc3MwcWExUUAgQjIicHIzcmExQXASYjIgIHExYzMhI9ATQnaZYBFLLFj1enk50BlP7ttKSEW6mRw/1HAfZXh6S5AqpOaam1LAK5Q9UBRK9lj/PB/sNL1v69rUuW7sMBYM+AAzpV/v/r/ew2AQD2TKZyAAACAH3/7AS9BzYAEAAUAEIAsg4AACuxBgPpsgECACuwCTMBsBUvsADWsQMM6bADELEIASuxCwzpsRYBK7EDABESsBE5sAgRsw4SExQkFzkAMDETETMRFBYzIBkBMxEUACMiABMhEyN9/JSQAST8/tf3+v7axQEVw8oB5APM/DKSmgE0A8b8M+j+8QELBj/+0QACAH3/7AS9BzYAEAAUAEIAsg4AACuxBgPpsgECACuwCTMBsBUvsADWsQMM6bADELEIASuxCwzpsRYBK7EIAxESsw4REhQkFzmwCxGwEzkAMDETETMRFBYzIBkBMxEUACMiAAETIQF9/JSQAST8/tf3+v7aAaPDARX+6wHkA8z8MpKaATQDxvwz6P7xAQsFEAEv/tEAAgB9/+wEvQc3ABAAGQBNALIOAAArsQYD6bIBAgArsAkzAbAaL7AA1rEDDOmwAxCxCAErsQsM6bEbASuxAwARErEREjk5sAgRtA4TFBcZJBc5sAsSsRUWOTkAMDETETMRFBYzIBkBMxEUACMiABM1ATMBFSMnB338lJABJPz+1/f6/trIAQ+PARHDlpUB5APM/DKSmgE0A8b8M+j+8QELBR8NART+6gucnAAAAAMAff/sBL0HAgAQABkAIgB7ALIOAAArsQYD6bIBAgArsAkzsBgvsCAzsRQK6bAcMgGwIy+wANaxAwzpsxEDAAgrsRYM6bADELEIASuxCwzpsx8LCAgrsRoM6bAaL7EfDOmxJAErsRYDERKxExg5ObAaEbEOBjk5sAgSsR0gOTkAsRQYERKxGh85OTAxExEzERQWMyAZATMRFAAjIgATNDYyFhQGIiYlNDYyFhQGIiZ9/JSQAST8/tf3+v7avEN2RER2QwHJQ3ZERHZDAeQDzPwykpoBNAPG/DPo/vEBCwWVMkREZEREMTJERGRERAAAAAIABwAABNYHNgAIAAwANwCyBwAAK7IAAgArsAMzAbANL7AH1rAJMrEGDOmxDgErsQYHERKyAgoMOTk5ALEABxESsAI5MDETIQkBIQERIxEbASEBBwEZAU8BTwEY/hj+B8MBFf7rBbD9TgKy/Gj96AIYA+8BL/7RAAIAlAAABH4FsAAMABQASwCyAAAAK7IBAgArtAsNAAENK7ELB+m0AxQAAQ0rsQMH6QGwFS+wANaxDBHpsQINMjKwDBCxEQErsQcR6bEWASsAsRQNERKwBzkwMTMRMxEzMgQVFAQrARkBMzI2NCYnI5Tz8fQBEv7u8/L2fZGMev4FsP7o7sjH7/7UAe+C3oQCAAEAiP/sBJsGFQAsAIkAsgAAACuyFAAAK7EbB+mwKS+xBAfpAbAtL7AA1rEsEemwLBCxJgErsQcQ6bMMByYIK7EjEemwIy+xDBHpsx4HJggrsRER6bEuASuxIywRErMEGBcpJBc5sCYRsCE5sAwSsRQbOTmwHhGwCjmxEQcRErAPOQCxGwARErAXObApEbIHERg5OTkwMTMRNDYzMhYVFA4CFRQeAhUUBiMiJic3HgEzMjY1NC4CNTQ2NTQmIyIHEYjlzrvXG0UWQbJR2cZQqyYxLX82YVpGrlF+XFC4BARR1u67qT5icUEnLFSUiUuruScZwxwlVkMxW4iIUFjJTVFh9/ukAAAAAAMAWv/sA/sGAAAeACIALQCSALIYAAArshwAACuxJgfpshABACuxCAbpsggQCiuzQAgMCSu0AyscEA0rsQME6bAfLwGwLi+wANaxIxHpsCMQsSkBK7AEMrEUEemxLwErsSMAERKxDB85ObApEbULEBwgISIkFzmwFBKxGBo5OQCxJhgRErEWGjk5sCsRsRQAOTmxCAMRErATObEfEBESsCE5MDETNCQ7ATU0JiMiBhUjND4BMzIWFxEUFxUjJicGIyImEyETIwMUFjMyNjc1IyIGWgEB75VeYFNq83bLfb7iAyn4EAx0qKPOhAEVw8qfXU5IfyCDh4gBL625R1RlU0BZm1i/rf4YklcRH0Z5ugVa/tH8d0ZTRjvMXgAAAwBa/+wD+wYAAB4AKQAtAJIAshgAACuyHAAAK7EiB+myEAEAK7EIBumyCBAKK7NACAwJK7QDJxwQDSuxAwTpsCsvAbAuL7AA1rEfEemwHxCxJQErsAQysRQR6bEvASuxHwARErAMObAlEbULEBwqKy0kFzmwFBKyGBosOTk5ALEiGBESsRYaOTmwJxGxFAA5ObEIAxESsBM5sSsQERKwKjkwMRM0JDsBNTQmIyIGFSM0PgEzMhYXERQXFSMmJwYjIiY3FBYzMjY3NSMiBhsBIQFaAQHvlV5gU2rzdst9vuIDKfgQDHSoo87zXU5IfyCDh4hvwwEV/usBL625R1RlU0BZm1i/rf4YklcRH0Z5uqJGU0Y7zF4DMwEv/tEAAAAAAwBa/+wD+wYBAB4AJwAyAJgAshgAACuyHAAAK7ErB+myEAEAK7EIBumyCBAKK7NACAwJK7QDMBwQDSuxAwTpsCEvAbAzL7AA1rEoEemwKBCxLgErsAQysRQR6bE0ASuxKAARErIMHyA5OTmwLhG2CxAcISIlJyQXObAUErMYGiMkJBc5ALErGBESsRYaOTmwMBGxFAA5ObEIAxESsBM5sSEQERKwHzkwMRM0JDsBNTQmIyIGFSM0PgEzMhYXERQXFSMmJwYjIiYTNQEzARUjJwcDFBYzMjY3NSMiBloBAe+VXmBTavN2y32+4gMp+BAMdKijzocBD48BEcOWlVVdTkh/IIOHiAEvrblHVGVTQFmbWL+t/hiSVxEfRnm6BDoNART+6gucnPxoRlNGO8xeAAMAWv/sA/sF9gAeADQAPwDYALIYAAArshwAACuxOAfpshABACuxCAbpsggQCiuzQAgMCSu0Az0cEA0rsQME6bAsL7ElBOmzMSUsCCuxIgTpAbBAL7AA1rE1EemwNRCwNCDWEbQfDQANBCuwHy+0NA0ADQQrsAsysh80CiuzQB8MCSuwNRCxOwErsAQysRQR6bMpFDsIK7QoDQANBCuwKC+0KQ0ADQQrsUEBK7E7NBEStRAcIiUsOCQXObAoEbEYGjk5ALE4GBESsRYaOTmwPRGxFAA5ObEIAxESsBM5sSwQERKxHzQ5OTAxEzQkOwE1NCYjIgYVIzQ+ATMyFhcRFBcVIyYnBiMiJhM0NjMyFjMyNjUXFAYjIi4CIyIGFQMUFjMyNjc1IyIGWgEB75VeYFNq83bLfb7iAyn4EAx0qKPOb39fOaE0JjaVf2AnOWkrGiY1EV1OSH8gg4eIAS+tuUdUZVNAWZtYv63+GJJXER9GeboEPm6WWjkvDG6SETwMOS78bEZTRjvMXgAAAAQAWv/sA/sFzAAeACcAMgA7AM4AshgAACuyHAAAK7ErB+myEAEAK7EIBumyCBAKK7NACAwJK7QDMBwQDSuxAwTpsCYvsDkzsSIK6bA1MgGwPC+wANaxKBHpsx8oAAgrsSQM6bAoELEuASuwBDKxFBHpsBQQsDgg1hGxMwzpsDMvsTgM6bE9ASuxHwARErAMObAoEbEhJjk5sCQSsxwiCyUkFzmwMxGyCBArOTk5sTguERKzGBo1OiQXOQCxKxgRErEWGjk5sDARsRQAOTmxCAMRErATObEiJhESsTM4OTkwMRM0JDsBNTQmIyIGFSM0PgEzMhYXERQXFSMmJwYjIiYTNDYyFhQGIiYTFBYzMjY3NSMiBgE0NjIWFAYiJloBAe+VXmBTavN2y32+4gMp+BAMdKijzntDdkREdkN4XU5IfyCDh4gBUUN2RER2QwEvrblHVGVTQFmbWL+t/hiSVxEfRnm6BLAyRERkRET8JEZTRjvMXgO3MkREZEREAAAAAAQAWv/sA/sGXgAeACkAMwA+ANUAshgAACuyHAAAK7EiB+myEAEAK7EIBumyCBAKK7NACAwJK7QDJxwQDSuxAwTpsDIvtDcEAA8EK7A9L7QtBAAPBCsBsD8vsADWsR8R6bAfELErASu0NA0ADQQrsDQQsSUBK7AEMrEUEemzMBQlCCu0Og0ADQQrsDovtDANAA0EK7FAASuxHwARErAMObE0KxESsAs5sDoRtQgcIhAyLSQXObEwJRESsRgaOTkAsSIYERKxFho5ObAnEbEUADk5sQgDERKwEzmxPTcRErMqLzArJBc5MDETNCQ7ATU0JiMiBhUjND4BMzIWFxEUFxUjJicGIyImNxQWMzI2NzUjIgYSNDYzMhYUBiMiJxQWMzI2NTQmIgZaAQHvlV5gU2rzdst9vuIDKfgQDHSoo87zXU5IfyCDh4gNf19dgH1gYQ9CLi9BP2I/AS+tuUdUZVNAWZtYv63+GJJXER9GebqiRlNGO8xeA5uqe3uqeM0vQUAwLkNDAAAAAwBI/+wGhARQACkANAA8AK0AsicAACuwIjOxLQbpsBsysg8BACuwEzOxCAfpsDoytDUYJw8NK7AxM7E1BemwAzIBsD0vsADWsSoR6bAqELExASuwBDKxGBDpsDUysBgQsTYBK7EWEOmxPgErsSoAERKwDDmwMRGyCw8nOTk5sBgSsREkOTmwNhGxGyI5ObAWErEeHzk5ALEtJxESsR8kOTmwGBGzAB4qMCQXObEINRESsQsMOTmwDxGwETkwMRM0NjsBNTQmIyIGFSc0NjMyFzYXMhIdASEeATMyPwEXDgEjIicOASMiJjcUFjMyNjc1Iw4BASE1NCYjIgZI7um/X1hbc/L9xd9vg8jU7v1JCZiGiWs9SUbRcf2MQdaGsMjyXVg6iC3EaHgClgHEbWVjfwE4nqxHW2dZQhOSuYWHAv7964mLnjoipjhAoU1UsJhBTzsr0QJfAQgecXqKAAAAAAIAT/48A/UETgAcACsAigCyGgAAK7QeBAAPBCuyBAEAK7ELB+myCwQKK7NACwcJK7AlL7QmBAAPBCsBsCwvsADWsQ8R6bAPELEpASuxIg3psCIQsRUBK7AIMrEWD+mwBzKxLQErsSkPERK3BAsSGh0eJSYkFzmwIhGxIB85OQCxGiYRErIdICI5OTmxCx4RErISFRY5OTkwMRM1NAAzMhYXIy4BIyIGBxUUFjMyNjczDgIjIgABNzMHFhUUBiMnMjY1NCZPAQjkwfMG5QR3XHaAAX94W3gE5QR2ynXj/vYBWyCxC5asmwdCR0cCFRn3ASnht114q64nsK1qTmWvZgEm/mGLNhuSaXaJLyotIwAAAwBT/+wECwYAABUAGQAhAFoAshMAACuxDQfpsgUBACuxHwfptBoKEwUNK7EaBemwFi8BsCIvsBvWsQgQ6bIbCAors0AbAAkrsSMBK7EIGxESsQ8QOTkAsQoNERKxDxA5ObEWBRESsBg5MDETNTQSNjMyEhEVIR4BMzI3Fw4BIyIAEyETIwMhNS4BIyIGU33ii93x/T0LnXenaYNB2Yfn/uF/ARXDypQBzwhyZWR7AgEeogD/jv7m/v5ihpyHfWFrASME8f7R/bESen2MAAAAAAMAU//sBAsGAAAVAB0AIQBcALITAAArsQ0H6bIFAQArsRsH6bQWChMFDSuxFgXpsB8vAbAiL7AX1rEIEOmyFwgKK7NAFwAJK7EjASuxCBcRErIPECA5OTkAsQoNERKxDxA5ObEfBRESsB45MDETNTQSNjMyEhEVIR4BMzI3Fw4BIyIAEyE1LgEjIgYbASEBU33ii93x/T0LnXenaYNB2Yfn/uH5Ac8IcmVke1PDARX+6wIBHqIA/47+5v7+Yoach31hawEjAXMSen2MAdIBL/7RAAAAAwBT/+wECwYBABUAHgAmAF0AshMAACuxDQfpsgUBACuxJAfptB8KEwUNK7EfBemwGC8BsCcvsCDWsQgQ6bIgCAors0AgAAkrsSgBK7EIIBESsw8QGhskFzkAsQoNERKxDxA5ObEYBRESsBY5MDETNTQSNjMyEhEVIR4BMzI3Fw4BIyIAEzUBMwEVIycHAyE1LgEjIgZTfeKL3fH9PQudd6dpg0HZh+f+4YIBD48BEcOWlUoBzwhyZWR7AgEeogD/jv7m/v5ihpyHfWFrASMD0Q0BFP7qC5yc/aISen2MAAAEAFP/7AQLBcwAFQAeACYALwCpALITAAArsQ0H6bIFAQArsSQH6bQfChMFDSuxHwXpsB0vsC0zsRkK6bApMgGwMC+wFtaxGwzpsBsQsSABK7EIEOmyIAgKK7NAIAAJK7MsCCAIK7EnDOmwJy+xLAzpsTEBK7EbFhESsgsKHzk5ObAnEbMNEwUkJBc5sCASsiIpLjk5ObAsEbIPKi05OTmwCBKwEDkAsQoNERKxDxA5ObEZHRESsScsOTkwMRM1NBI2MzISERUhHgEzMjcXDgEjIgATNDYyFhQGIiYTITUuASMiBgE0NjIWFAYiJlN94ovd8f09C513p2mDQdmH5/7hdkN2RER2Q4MBzwhyZWR7ATVDdkREdkMCAR6iAP+O/ub+/mKGnId9YWsBIwRHMkREZERE/V4Sen2MAlYyRERkREQAAAAC/7QAAAGMBfkAAwAHACcAsgQAACuyBQEAKwGwCC+wBNaxBxHpsQkBK7EHBBESsQMBOTkAMDEDIRMjAxEzEUwBFcPKM/MF+f7R+zYEOvvGAAIAjwAAAmkF+QADAAcAKgCyAAAAK7IBAQArAbAIL7AA1rAEMrEDEemxCQErsQMAERKxBQc5OQAwMTMRMxEDEyEBj/PxwwEV/usEOvvGBMoBL/7RAAL/twAAAmYF+gAIAAwAKQCyCQAAK7IKAQArAbANL7AJ1rEMEemxDgErsQwJERKyAwIHOTk5ADAxAzUBMwEVIycHExEzEUkBD48BEcOWlRfzBNkNART+6gucnPsnBDr7xgAAAAAD/6sAAAJxBcUACAAMABUAZQCyCQAAK7IDAgArsA8zsQcK6bATMrIKAQArAbAWL7AJ1rEMEemzBQwJCCuxAAzpsAAvsQUM6bMNDAkIK7ESDOmxFwErsQkAERKxAwY5ObESDBESsQ8UOTkAsQMHERKxDRI5OTAxAzQ2MhYUBiImExEzEQM0NjIWFAYiJlVDdkREdkPk8w5DdkREdkMFTzJERGRERPrjBDr7xgVOMkREZEREAAACAGf/7ARABiwAHQArAFwAshoAACuxIQfpsCkvsQQG6QGwLC+wANaxHhHpsB4QsSQBK7EWEemxLQErsR4AERKxDQ45ObAkEbYECgYQExoLJBc5sBYSsRESOTkAsSkhERKwADmwBBGwBjkwMRM0PgEzMhcmJwcnNyYnNxYXNxcHEhEVFAIGIyIuATcUFjMyNj0BJy4BIyIGZ3HOhJJxMX7MTqx+okvusbROmv5+5YyK4n7zjW5viQEge05+iwHUled9W6l6h21yUirDMod4bWf+9/5vUqb++ZJ+4oh+qMitdBIwOKgAAAAAAgB5AAAD+AX2ABAAJgCKALIAAAArsAgzsgEBACuyBQEAK7ENCOmwHi+xFwTpsyMXHggrsRQE6QGwJy+wANaxEBHpsQImMjKwEBC0EQ0ADQQrsBEvsBAQsQkBK7EIEemzGggJCCu0Gw0ADQQrsSgBK7EQERESsAM5sAkRtAUUFx4jJBc5ALEBDRESsAM5sR4FERKxESY5OTAxMxEzFzYzIBMRIxE0JiMiBxEDNDYzMhYzMjY1FxQGIyIuAiMiBhV55Qd4wwFSBvNZZZNInX9fOaE0JjaVf2AnOWkrGiY1BDp9kf59/TUCvWdjhfz+BORullo5LwxukhE8DDkuAAAAAAMAT//sBD0GAAAPABMAHgBVALINAAArsRcH6bIFAQArsRwH6bAQLwGwHy+wANaxFBHpsBQQsRkBK7EJEemxIAErsRQAERKwEDmwGRG0BRENExIkFzmwCRKwBzkAsRAFERKwEjkwMRM1NBI2MzIAHwEUDgEjIgATIRMjAxQWMjY1NCYjIgZPfuSU2wERCwF75Zbl/u2YARXDyrOK9omNeXeMAhsMnwD/if7m6Tmg/IoBMQTj/tH9Qae9wLmkwL0AAAMAT//sBD0GAAAPABoAHgBRALINAAArsRMH6bIFAQArsRgH6bAcLwGwHy+wANaxEBHpsBAQsRUBK7EJEemxIAErsRUQERK0BQ0bHB4kFzmwCRGxBx05OQCxHAURErAbOTAxEzU0EjYzMgAfARQOASMiADcUFjI2NTQmIyIGGwEhAU9+5JTbARELAXvlluX+7fOK9omNeXeMg8MBFf7rAhsMnwD/if7m6Tmg/IoBMfWnvcC5pMC9AgMBL/7RAAAAAAMAT//sBD0GAQAPABgAIwBcALINAAArsRwH6bIFAQArsSEH6bASLwGwJC+wANaxGRHpsBkQsR4BK7EJEemxJQErsRkAERKxEBE5ObAeEbUFEhMWGA0kFzmwCRKyBxQVOTk5ALESBRESsBA5MDETNTQSNjMyAB8BFA4BIyIAEzUBMwEVIycHAxQWMjY1NCYjIgZPfuSU2wERCwF75Zbl/u2bAQ+PARHDlpVpivaJjXl3jAIbDJ8A/4n+5uk5oPyKATEDww0BFP7qC5yc/TKnvcC5pMC9AAAAAAMAT//sBD0F9gAPACUAMACIALINAAArsSkH6bIFAQArsS4H6bAdL7EWBOmzIhYdCCuxEwTpAbAxL7AA1rEmEemwJhCwJSDWEbQQDQANBCuwEC+0JQ0ADQQrsCYQsSsBK7EJEemwGSDWEbQaDQANBCuxMgErsRklERK2DRMFHSgpLiQXObEJGhESsAc5ALEdBRESsRAlOTkwMRM1NBI2MzIAHwEUDgEjIgATNDYzMhYzMjY1FxQGIyIuAiMiBhUDFBYyNjU0JiMiBk9+5JTbARELAXvlluX+7YN/XzmhNCY2lX9gJzlpKxomNSWK9omNeXeMAhsMnwD/if7m6Tmg/IoBMQPHbpZaOS8MbpIRPAw5Lv02p73AuaTAvQAABABP/+wEPQXMAA8AGAAjACwAmACyDQAAK7EcB+myBQEAK7EhB+mwFy+wKjOxEwrpsCYyAbAtL7AA1rEZEemzEBkACCuxFQzpsBkQsR4BK7EJEemzKQkeCCuxJAzpsCQvsSkM6bEuASuxGRARErESFzk5sBURshMWGzk5ObAkErINBSE5OTmwHhGyHCYrOTk5sCkSsScqOTmwCRGwBzkAsRMXERKxJCk5OTAxEzU0EjYzMgAfARQOASMiABM0NjIWFAYiJhMUFjI2NTQmIyIGATQ2MhYUBiImT37klNsBEQsBe+WW5f7tj0N2RER2Q2SK9omNeXeMAWVDdkREdkMCGwyfAP+J/ubpOaD8igExBDkyRERkRET87qe9wLmkwL0ChzJERGRERAADAEMAkwQ3BMwAAwAPABkALgCwDS+xBwvpsAAvsQEJ6bAYL7ETC+kBsBovsATWsBAysQoV6bAVMrEbASsAMDETNSEVATQ2MzIWFRQGIyImEDQ2MzIWFAYjIkMD9P18SkNESkpEQ0pKQ0RKSkRDAkbU1P7QOkxMOjlKSgMxckxMcksAAAADAE//dwQ9BLsAFQAdACUAagCyDwAAK7EgB+myBAEAK7EbB+kBsCYvsADWsRYR6bAWELEjASuxCxHpsScBK7EWABESsRMUOTmwIxG1BgQSDxkeJBc5sAsSsAc5ALEgDxESsREUOTmwGxGzCwAYJSQXObAEErEGCTk5MDETNBI2MzIXNzMHFhEUDgEjIicHIzcmExQXASYjIgYTFjMyNjU0J09+5JRqWEeRZsR75ZZdWkiRZs7zQAErLzl3jKcrM3uJOgInnwD/iSKP0Jn+wKD8ih6Tz5YBNpxiAmEWvf3xEcC5lF0AAAAAAgB3/+wD9wYAABAAFABjALILAAArsg4AACuxBQjpsgEBACuwCDOwES8BsBUvsADWsQMR6bADELEHASuwCzKxChHpsRYBK7EDABESsBE5sAcRsw4SExQkFzmwChKwDDkAsQULERKwDDmxEQERErATOTAxExEzERQzMjcRMxEjJwYjIiYTIRMjd/OrsT7z5QZrxbC1aQEVw8oBfQK9/UbOfwMJ+8Zqfs4FRv7RAAIAd//sA/cGAAAQABQAXwCyCwAAK7IOAAArsQUI6bIBAQArsAgzsBIvAbAVL7AA1rEDEemwAxCxBwErsAsysQoR6bEWASuxBwMRErMOERIUJBc5sAoRsQwTOTkAsQULERKwDDmxEgERErAROTAxExEzERQzMjcRMxEjJwYjIiYBEyEBd/OrsT7z5QZrxbC1AUfDARX+6wF9Ar39Rs5/Awn7xmp+zgQXAS/+0QACAHf/7AP3BgEAEAAZAGoAsgsAACuyDgAAK7EFCOmyAQEAK7AIM7ATLwGwGi+wANaxAxHpsAMQsQcBK7ALMrEKEemxGwErsQMAERKxERI5ObAHEbQOExQXGSQXObAKErIMFRY5OTkAsQULERKwDDmxEwERErAROTAxExEzERQzMjcRMxEjJwYjIiYTNQEzARUjJwd386uxPvPlBmvFsLVsAQ+PARHDlpUBfQK9/UbOfwMJ+8Zqfs4EJg0BFP7qC5ycAAAAAwB3/+wD9wXMABAAGQAiAJ4AsgsAACuyDgAAK7EFCOmyAQEAK7AIM7AYL7AgM7EUCumwHDIBsCMvsADWsQMR6bARINYRsRYM6bADELEHASuwCzKxChHpsAoQsB8g1hGxGgzpsBovsR8M6bEkASuxAxERErETGDk5sBYRsRQXOTmwGhKxDgU5ObAHEbEcITk5sB8SsgwdIDk5OQCxBQsRErAMObEUGBESsRofOTkwMRMRMxEUMzI3ETMRIycGIyImEzQ2MhYUBiImJTQ2MhYUBiImd/OrsT7z5QZrxbC1YEN2RER2QwHJQ3ZERHZDAX0Cvf1Gzn8DCfvGan7OBJwyRERkREQxMkREZEREAAIADP5LA9YGAAAPABMAYQCyAAEAK7ADM7AHL7ELA+mwES8BsBQvsADWsQET6bABELEDASuxBBPpsRUBK7EBABESsgcJCjk5ObADEbMPEBETJBc5sAQSsBI5ALELBxESsAk5sAARsAI5sBESsBA5MDETIRsBIQECIyInNRcyNj8BAxMhAQwBBuXcAQP+UmPtNUAuXF0bIwLDARX+6wQ6/SIC3vsi/u8SvANDT10EzAEv/tEAAAIAgv5gBDcGAAAPABoAVQCyDAAAK7ESB+myBQEAK7EYCOmwAC+wAS8BsBsvsADWsQ8R6bECEDIysA8QsRUBK7EJEemxHAErsRUPERKxBQw5OQCxEgwRErAOObEFGBESsAM5MDETETMRNjMyEhEVFAIjIicZARYzMjY1NCYjIgeC82qwxePjwrJrQpZ0g4N2lUH+YAeg/dd3/tr++hD3/tF1/f8CzH67vqa6ewADAAz+SwPWBcwADwAYACEAoACyAAEAK7ADM7AHL7ELA+mwFy+wHzOxEwrpsBsyAbAiL7AQ1rEVDOmzARUQCCuxABPpsAAvsQET6bAVELEDASuxBBPpsBkg1hGxHgzpsSMBK7EQABESsQkKOTmwARGyBxIXOTk5sBUSsg8TFjk5ObAZEbACObADErEbIDk5sB4RsRwfOTkAsQsHERKwCTmwABGwAjmxExcRErEZHjk5MDETIRsBIQECIyInNRcyNj8BAzQ2MhYUBiImJTQ2MhYUBiImDAEG5dwBA/5SY+01QC5cXRsj6UN2RER2QwHJQ3ZERHZDBDr9IgLe+yL+7xK8A0NPXQVRMkREZEREMTJERGRERAACAGT/7ActBcQAFwAjAIQAshIAACuxDwPpshQAACuxGwfpsgcCACuxCgPpsgUCACuxIAfptAsOFAUNK7ELCOkBsCQvsADWsRgR6bAYELEdASuxDwzpsAoysg8dCiuzQA8JCSuwEDKzQA8NCSuxJQErsR0YERKxFAU5ObAPEbASOQCxDxsRErAdObEgChESsB45MDETETQSJDMyFyEVIREhFSERIRUhBiMiJAI3FBYzMjcRJiMiBgdkkQELqHunA1z9TAJW/aoCu/ydp3mn/veU8bKhY2hyW6GvAQI2ATqsARKWFMz+bsj+QMoUkwENtMHRDQQ4Ds+8AAMAW//sBvIETwAeACoAMgCAALIcAAArsBgzsSIH6bARMrIEAQArsAkzsSgH6bAwMrQrDhwEDSuxKwXpAbAzL7AA1rEfEemwHxCxLAErsQwQ6bE0ASuxLB8RErcEBhEYHA4lKyQXObAMEbEUFTk5ALEiHBESsRUaOTmwDhGwFDmwKxKxHyU5ObEEKBESsAY5MDETNTQAMzIXPgEXMhIdASEeATMyNjcXDgEjIicGIyIANxQWMzI2NTQmIyIGBSE1NCYjIgZbAQ/g+YZBt23W7v1WC5F1WY9HT0fNePeMhvbj/vLyhnl3hod4dYgDAAG1cWNVeAIbDPgBL7FUXgH+/eyIi54qMp4/Qa6uAS35qrq5wKa+ukgZb3qJAAAAAwAHAAAE1gcCAAgAEQAaAHoAsgcAACuyAAIAK7ADM7AQL7AYM7EMCumwFDIBsBsvsAfWsQYM6bMOBgcIK7EJDOmwCS+xDgzpsxIGBwgrsRcM6bEcASuxBwkRErIBDA85OTmxEg4RErACObEXBhESsgMUGTk5OQCxAAcRErACObEMEBESsRIXOTkwMRMhCQEhAREjEQM0NjIWFAYiJiU0NjIWFAYiJgcBGQFPAU8BGP4Y/uBDdkREdkMByUN2RER2QwWw/U4Csvxo/egCGAR0MkREZEREMTJERGRERAAAAAABAJQE4ANDBgEACAAhALAAL7AFM7QCCwAWBCsBsAkvsQoBKwCxAgARErAHOTAxEzUBMwEVIycHlAEPjwERw5aVBOANART+6gucnAAAAQB6BNsDVwX1ABUAPwCwDS+xBgTpsxIGDQgrsQME6QGwFi+wANa0FQ0ADQQrsBUQsQkBK7QKDQANBCuxFwErsQkVERKxAw05OQAwMRM0NjMyFjMyNjUXFAYjIi4CIyIGFXp/XzmhNCY2lX9gJzlpKxomNQTjbpZaOS8MbpIRPAw5LgAAAQBHAgkCVALNAAMAABM1IRVHAg0CCcTEAAAAAAEARwIJAlQCzQADAAATNSEVRwINAgnExAAAAAABAEcCCQJUAs0AAwAAEzUhFUcCDQIJxMQAAAAAAQCeAm0EmAMxAAMAFwCwAC+xAQfpsQEH6QGwBC+xBQErADAxEzUhFZ4D+gJtxMQAAQCCAm0F0AMxAAMAFwCwAC+xAQfpsQEH6QGwBC+xBQErADAxEzUhFYIFTgJtxMQAAQBjBCABlgYaAAgAJQCwAC+0BAsACQQrAbAJL7AA1rEIDemxCgErsQgAERKwBDkAMDETNT4BNxcGBxVjAWdPfFsDBCCKYNE/TYWQmAAAAAABADMEAAFlBgAACAAlALAIL7QDCwAIBCsBsAkvsALWsQUN6bEKASuxBQIRErAIOQAwMRM2NzUzFRQGBzNaA9VpTQRNg5KeimfRPgAAAQAy/tYBZADKAAgAJQCwCC+0AwsACQQrAbAJL7AC1rEFDemxCgErsQUCERKwCDkAMDEXNjc1MxUOAQcyVQPaAWZQ3H+Uk4Vd0EIAAAIAbAQgAu8GGgAIABEAQgCwAC+wCTO0BAsACQQrsA0yAbASL7AA1rEIDemwCBCxCQErsREN6bETASuxCAARErAEObAJEbAFObARErANOQAwMRM1PgE3FwYHFTM1PgE3FwYHFWwBZ098WwN7AWdPfFsDBCCKYNE/TYWQmIpg0T9NhZCYAAIAQAQAAsAGAAAIABEAQgCwCC+wETO0AwsACAQrsAwyAbASL7AC1rEFDemwBRCxCwErsQ4N6bETASuxBQIRErAIObALEbAJObAOErAROQAwMRM2NzUzFRQGBzc2NzUzFRQGB0BaA9VpTdJaA9VpTQRNg5KeimfRPk2Dkp6KZ9E+AAAAAAIAMv7CAqoA/wAJABIAQgCwCS+wEjO0AwsACAQrsA0yAbATL7AC1rEFDemwBRCxDAErsQ8N6bEUASuxBQIRErAJObAMEbAKObAPErASOQAwMRc2NzUzFQYHBgc3Njc1MxUUBgcyVQPaATcxSsNYBNpmUfCJncm6bHJkQU6Olsu2Y91HAAEAiAIGAkQD2wANAC4AsAsvtAQLAAkEK7QECwAJBCsBsA4vsADWtAgVAAoEK7QIFQAKBCuxDwErADAxEzU0NjMyFh0BFAYjIiaIeWRneHdnY3kC1i1feXliJV53cwAAAAMAiv/1BSgBAAAKABUAIABFALIJAAArsRQfMzOxAwvpsQ4ZMjKyCQAAK7EDC+kBsCEvsAHWsQYV6bAGELEMASuxERXpsBEQsRcBK7EcFemxIgErADAxNjQ2MzIWFRQGIyIkNDYzMhYVFAYjIiQ0NjMyFhUUBiMiikpDREpKREEBfkpDREpKREEBbUpDREpKREE/dE1NOjlLSnRNTTo5S0p0TU06OUsAAAEAbACKAjMDqQAGACEAAbAHL7AA1rQFFQAJBCuwAzKxCAErsQUAERKwBDkAMDETNQEzAxMjbAEgp/f3pwIQEwGG/nD+cQAAAAEAVACKAhsDqQAGACEAAbAHL7AA1rACMrQFFQAJBCuxCAErsQUAERKwATkAMDE3EwMzARUBVPf3pwEg/uCKAY8BkP56E/56AAEAXv/tBDAFwwAjAJMAsiAAACuxGwjpsgkCACuxDgPptAABIAkNK7AVM7EABOmwFzK0BQQgCQ0rsBMzsQUE6bARMgGwJC+wI9axAgYyMrEYDOmxERQyMrIYIwors0AYFwkrsBIysiMYCiuzQCMACSuwBDKxJQErsRgjERKxByI5OQCxGyARErAeObAAEbAdObEOBRESsAw5sAkRsAs5MDETNTM1IzUzEgAzMhcHJiMiBgchFSEVIRUhHgEzMjcXBiMgAANerKytDQEs/WqFHGZll6IJAWP+nAFk/pwGo5huXxx4gP8A/toIAg+NgI0A/wEbH80irKSNgI2urCHMHQEgAQIAAgBtA5QEVwWwAAcAFACRALIJAgArsQEMMzO0CAsACAQrsgUOETIyMrIJAgArtAgLAAgEK7IJAgArtAAEAA8EK7ADMgGwFS+wBta0BQ0ADQQrsgUGCiuzQAUDCSuyBgUKK7NABgAJK7AFELEIASu0FA0ADQQrsBQQsQ8BK7QODQANBCuxFgErsQ8UERKxCgw5OQCxAAgRErILEBM5OTkwMRM1IRUjESMRAREzGwEzESMRAyMDEW0BjIp1AUmJgYWFb3w+fAVRX1/+RQG7/kMCHP6DAX395AF1/osBdP6MAAABAAAAAAQ4BDgAAwA1ALIAAAArtAELAAcEK7IAAAArtAELAAcEKwGwBC+wANa0AxUABwQrtAMVAAcEK7EFASsAMDExESERBDgEOPvIAAAAAAIAGAAABBcGFQAXABsAegCyFgAAK7AYM7IBAQArsREZMzOxAAXpsBMysA0vsQcJ6QGwHC+wFtawAjKxFRHpsBAyshUWCiuzQBUTCSuyFhUKK7NAFgAJK7AVELEYASuxGxHpsR0BK7EYFRESsQ0HOTmwGxGxCwo5OQCxDQERErALObAHEbAKOTAxEzUzNT4CMzIWFwcmIyIGHQEzFSMRIxEBETMRGKUBasKIUJNPJYpyb2TV1fMCZ/MDhrRKf7ZcIhrJMGFhRLT8egOG/HoEOvvGAAAAAQAtAAAELAYVABYAbgCyFQAAK7AJM7IBAQArsBAzsQAF6bASMrANL7EGCOkBsBcvsBXWsAIysRQR6bAPMrIUFQors0AUEgkrshUUCiuzQBUACSuwFBCxCgErsQkR6bEYASuxChQRErAGOQCxDQERErALObAGEbAIOTAxEzUzNT4BMzIFESMRJiMiHQEzFSMRIxEtpQHXxHoBRPNmSsTc3PMDhrRht8Mw+hsFPw64W7T8egOGAAAAAAIALQAABpMGFQAoACwApQCyJwAAK7EiKTMzsgEBACuyDh4qMzMzsQAF6bEgJDIysAsvsBozsQYI6bAUMgGwLS+wJ9awAjKxJhHpsA0ysicmCiuzQCcACSuwJhCxIwErsA8ysSIR6bAdMrIiIwors0AiIAkrsCIQsSkBK7EsEemxLgErsSMmERKxBgg5ObEpIhESsRoUOTmwLBGxGBc5OQCxCwERErEJGDk5sAYRsQgXOTkwMRM1MzU0NjMyFwcmIyIdASE1PgIzMhYXByYjIgYdATMVIxEjESERIxEBETMRLaXItEBIBig1rgF0AWrCiFCTTyaIc29k1dXz/ozzBM7zA4a0Y7TEEr4Is2BKf7ZcIhrJMGFhRLT8egOG/HoDhvx6BDr7xgAAAQAtAAAGkwYVACcAmQCyJgAAK7EWITMzsgEBACuxDh0zM7EABemxHyMyMrALL7AaM7EGCOmwEzIBsCgvsCbWsAIysSUR6bANMrImJQors0AmAAkrsCUQsSIBK7APMrEhEemwHDKyISIKK7NAIR8JK7AhELEXASuxFhHpsSkBK7EiJRESsQYIOTmxFyERErATOQCxCwERErEJGDk5sAYRsQgVOTkwMRM1MzU0NjMyFwcmIyIdASE1PgEzMgURIxEmIyIdATMVIxEjESERIxEtpci0QEgGKDWuAXQB18R6AUTzZkrE3Nzz/ozzA4a0Y7TEEr4Is2Bht8Mw+hsFPw64W7T8egOG/HoDhgAAAAEAAAACIxKOYEf7Xw889QAfCAAAAAAAxPARLgAAAADaq65+/6v+JgdXB5QAAAAIAAIAAAAAAAAAAQAACHP9rQAAB7T/q/+pB1cAAQAAAAAAAAAAAAAAAAAAAOoC7ABEAAAAAAH+AAAAAAAAAf4AAAIlAI8CmABlBOIAYASMAGQF4ABjBR0AVgFaAFICygCAAtIAKAOJABsEdQBEAcIAHAKgAEcCPACHAyoAAgSMAGkEjACoBIwAUQSMAE8EjAA0BIwAgQSMAHUEjABFBIwAaASMAF0CHwCCAecALgQRAD8EegCRBCoAgAPkADwHKABbBVMAEgUMAJQFOQBmBToAlASGAJQEZQCUBXIAagWvAJQCQgCjBHEALQULAJQEVACUBwEAlAWuAJQFhgBmBR0AlAWGAGAE/gCUBNQASgTbAC0FNwB9BS0AEgcKADAFEAApBOAABwTRAFACMQCEA1gAFAIxAAwDawA1A5wAAwKUADEEVABaBIEAfAQwAE8EhABPBEsAUwLWAC0EiQBSBHEAeQILAH0CAf+1BC0AfQILAIwG9gB8BHMAeQSOAE8EgQB8BIsATwLQAHwEIQBLAqkACARyAHcD9QAWBfIAIQQGAB8D5QAMBAYAUgKvADgCAgCuAq8AGwVRAHUB/gAAAh4AhgR9AGQEtQBeBZ0AXQRAAAsB/ACIBPgAWgOFAF0GRABXA5EAjQPiAFcEbQB/AqAARwZEAFcD2wCbAwoAfwRKAF8C9gA8AvYANwKbAHAEuwCSA+0ARQJCAI4CEABtAvYAgAOnAHcD4gBdBdAAWQYrAFAGVwBnA+QAQgVTABIFUwASBVMAEgVTABIFUwASBVMAEgeF//YFOQBmBIYAlASGAJQEhgCUBIYAlAJC/8gCQgCjAkL/ywJC/78FWP/3Ba4AlAWGAGYFhgBmBYYAZgWGAGYFhgBmBEQATQWEAGkFNwB9BTcAfQU3AH0FNwB9BOAABwTKAJQE5wCIBFQAWgRUAFoEVABaBFQAWgRUAFoEVABaBsEASAQwAE8ESwBTBEsAUwRLAFMESwBTAhr/tAIaAI8CGv+3Ahr/qwSnAGcEcwB5BI4ATwSOAE8EjgBPBI4ATwSOAE8EkQBDBIgATwRyAHcEcgB3BHIAdwRyAHcD5QAMBJcAggPlAAwHtABkBzoAWwTgAAcD5gCUA9gAegPKAAAHlAAAA8oAAAeUAAAChgAAAeUAAAFDAAABQwAAAPIAAAGEAAAAawAAAqAARwKgAEcCoABHBSkAngYwAIIBwABjAbwAMwHOADIDFABsAxsAQAMIADICywCIBaYAigGEAAACcgBsAmkAVAHlAAAEjABeBQkAbQQ4AAAEqAAYBLwALQcjAC0ALQAAAAAALAAsACwALAAsAGwApAGOAhwCwgNaA4ADrgPiBCIEZASMBKoE1ATsBToFZAXEBkgGkgcQB3QHmAgeCIYIwAkCCR4JQAlcCc4K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format('truetype');\n",
|
||
"}\n",
|
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"@font-face\n",
|
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"{\n",
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" font-family: RobotoReg; font-style: normal; font-weight: normal;\n",
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format('truetype');\n",
|
||
"}\n",
|
||
"\n",
|
||
"body\n",
|
||
"{\n",
|
||
"/* Re-adding horizontal scrollbar\n",
|
||
" overflow-x: hidden;\n",
|
||
" background-color: #f7f7f7;\n",
|
||
"*/\n",
|
||
" background-color: #f3f3f0;\n",
|
||
" color: #58544f;\n",
|
||
" margin-top: 0px;\n",
|
||
"}\n",
|
||
"\n",
|
||
".isHidden { display: none; }\n",
|
||
"\n",
|
||
".page-root\n",
|
||
"{\n",
|
||
"\t/*width: 1880px;*/\n",
|
||
" /* Made this bigger to better match actual width and avoid flickering due to the horizontal Scrollbar showing up */\n",
|
||
"\twidth: 1903px;\n",
|
||
"\toverflow: visible;\n",
|
||
"\t margin: 0 auto;\n",
|
||
" position: relative;\n",
|
||
"}\n",
|
||
".page-root-vertical\n",
|
||
"{\n",
|
||
"\twidth: 1056px;\n",
|
||
"\toverflow: visible;\n",
|
||
"\t margin: 0 auto;\n",
|
||
" position: relative;\n",
|
||
"}\n",
|
||
".page-column-main { width: 930px; position: absolute;}\n",
|
||
".page-column-detail { position: absolute; left: 1005.0px; }\n",
|
||
".page-all-summaries { position: absolute; top:160px; left: -12px; width: 960px; }\n",
|
||
"\n",
|
||
".pos-feature-summary\n",
|
||
"{\n",
|
||
"\twidth: 1056px;\n",
|
||
"\theight:162px;\n",
|
||
" position: relative;\n",
|
||
"}\n",
|
||
"\n",
|
||
".container-feature-summary\n",
|
||
"{\n",
|
||
"\twidth: 1056px;\n",
|
||
"\theight:175px;\n",
|
||
" position: absolute;\n",
|
||
"}\n",
|
||
".container-feature-summary-target\n",
|
||
"{\n",
|
||
"\twidth: 1056px;\n",
|
||
"\theight:175px;\n",
|
||
" position: relative;\n",
|
||
"}\n",
|
||
".container-feature-detail\n",
|
||
"{\n",
|
||
" height:900px;position:sticky;top:0;\n",
|
||
" transform: scale(1.0);transform-origin: 0 0;\n",
|
||
"}\n",
|
||
".container-feature-detail-vertical\n",
|
||
"{\n",
|
||
" width: 900px;height:900px;position:absolute; top: 151px; left:93px\n",
|
||
"}\n",
|
||
".container-feature-detail__offset\n",
|
||
"{\n",
|
||
" height:900px;position:absolute;top:0px;left:-17px\n",
|
||
"}\n",
|
||
"\n",
|
||
".color-source { color: #0088ed; }\n",
|
||
".button-border-source { border:1px solid #0088ed; }\n",
|
||
".color-source-target { color: #004bd1; }\n",
|
||
".color-compare { color: #f77721; }\n",
|
||
".button-border-compare { border:1px solid #f77721; }\n",
|
||
".color-compare-target { color: #e54600; }\n",
|
||
".color-normal { color: #58544f; }\n",
|
||
".color-target-summary { color: #CFC8BC; }\n",
|
||
".color-light { color: #837d76; }\n",
|
||
".color-red { color: #ff0000; }\n",
|
||
".dim { opacity: 0.5; }\n",
|
||
".color-title-disabled { color: #e2e2e2; }\n",
|
||
"\n",
|
||
"a { color: #58544f; }\n",
|
||
".text-dataframe-title { font-family: RobotoBoldCond; font-size: 24px; }\n",
|
||
".text-dataframe-title-small { font-family: RobotoBoldCond; font-size: 20px; }\n",
|
||
".text-large-bold { font-family: RobotoBoldCond; font-size: 15.4px; }\n",
|
||
".text-med-bold { font-family: RobotoBoldCond; font-size: 12px; }\n",
|
||
".text-med { font-family: RobotoMed; font-size: 12px; }\n",
|
||
".text-small-med { font-family: RobotoMed; font-size: 10px; }\n",
|
||
".text-small-bold { font-family: RobotoBoldCond; font-size: 10px; }\n",
|
||
".text-label { font-family: RobotoReg; font-size: 11px;}\n",
|
||
".text-value { font-family: RobotoMed; font-size: 11px; }\n",
|
||
".text-distinct { font-family: RobotoMed; font-size: 12px; font-weight: bold;}\n",
|
||
".text-version { font-family: RobotoReg; font-size: 14px; font-weight: bold; }\n",
|
||
".text-credits { font-family: RobotoReg; font-size: 9px;}\n",
|
||
"\n",
|
||
".pos-logo-group { position: absolute; top:0px; left:0px; width: 380px; height: 200px; text-align: center;}\n",
|
||
".pos-logo { position: relative;\n",
|
||
" margin-left: auto;\n",
|
||
" margin-right: auto;\n",
|
||
" top: 32px; }\n",
|
||
".pos-credits { position: relative; top:26px; text-align: center; }\n",
|
||
"\n",
|
||
".row-colored { background-color: #00000008; }\n",
|
||
".row-missing { background-color: #00000008; text-indent: 4px; height: 16px; width: 250px; }\n",
|
||
".assoc-row { height: 13px; line-height: 11px; text-indent: 4px; }\n",
|
||
".assoc-row-target { height: 13px; line-height: 11px; text-indent: 4px; background-color: #221F1F; color: #c1b9af; }\n",
|
||
".row-numeric-summary { height: 13px; line-height: 11px; width: 140px; }\n",
|
||
".row-separator-bottom { border-bottom: 1px solid #00000018; }\n",
|
||
".row-separator-top { border-top: 1px solid #00000018; }\n",
|
||
".breakdown-row { height: 13px; line-height: 11px; text-indent: 4px; }\n",
|
||
".breakdown-row-header { height: 26px; text-indent: 4px; }\n",
|
||
".breakdown-row-header-2-lines { height: 30px; text-indent: 4px; }\n",
|
||
".breakdown-hr { position:absolute; top: 13px; left: 10px; width: 592px; }\n",
|
||
".breakdown-hr-2-lines { position:absolute; top: 20px; left: 10px; width: 592px; }\n",
|
||
"\n",
|
||
"/* TAB ICON/NAME */\n",
|
||
".text-title-tab { font-family: RobotoBoldCond; font-size: 15.4px; position: absolute; left: 74px; top: 24px; width:250px; }\n",
|
||
".pos-tab-image { position: absolute; left: 45px; top: 21px; }\n",
|
||
".pos-detail-tab-icon-text__offset { position: absolute; left: -4px; top: -4px; }\n",
|
||
".pos-text-title-tab__no-icon { position: absolute; left: 37px; top: 17px; }\n",
|
||
"\n",
|
||
"/*\n",
|
||
" DATAFRAME SUMMARY\n",
|
||
"------------------------------------*/\n",
|
||
".pos-dataframe-summary-title-source { position: absolute; left: 0px; top: 12px; width: 250px; text-align: right; }\n",
|
||
".pos-dataframe-summary-title-compare { position: absolute; left: 350px; top: 12px; width: 250px; text-align: left; }\n",
|
||
".pos-dataframe-summary-title-compare-none { position: absolute; left: 350px; top: 16px; width: 250px; text-align: left; }\n",
|
||
".pos-dataframe-summary { position: absolute; top: 9px; left: 380px; }\n",
|
||
".pos-dataframe-summary-rows { position: absolute; top: 47px; left: 19px; }\n",
|
||
".dataframe-summary-row { height: 13px; width: 563px; line-height: 12px; }\n",
|
||
".pos-df-summary-source { position: absolute; left: 0px; width: 231px; text-align: right;}\n",
|
||
".pos-df-summary-center { position: absolute; left: 231px; width: 100px; text-align: center;}\n",
|
||
".pos-df-summary-compare { position: absolute; left: 331px; width: 200px; text-align: left;}\n",
|
||
".size-df-summary-button { width: 156px; height: 35px; }\n",
|
||
".pos-df-summary-button-assoc-source { position: absolute; top: 54px; left: 10px; }\n",
|
||
".pos-df-summary-button-assoc-compare { position: absolute; top: 54px; left: 397px; }\n",
|
||
"\n",
|
||
"/*\n",
|
||
" FEATURE SUMMARY\n",
|
||
"------------------------------------*/\n",
|
||
".summary-number\n",
|
||
"{\n",
|
||
" position: absolute; top: 17px; left: 0px; width: 34px;\n",
|
||
" font-family: RobotoBoldCond; font-size: 26px;\n",
|
||
" color: #d9d9d9; text-align: right;\n",
|
||
"}\n",
|
||
".summary-number-vertical\n",
|
||
"{\n",
|
||
" position: absolute; top: 25px; left: 6px; width: 34px;\n",
|
||
" font-family: RobotoBoldCond; font-size: 26px;\n",
|
||
" color: #d9d9d9; text-align: right;\n",
|
||
" text-orientation: mixed;\n",
|
||
" writing-mode: vertical-rl;\n",
|
||
"}\n",
|
||
"\n",
|
||
"/* BASE STATS */\n",
|
||
".pos-base-stats { position: absolute; top: 65px; left: 74px; }\n",
|
||
".pos-base-stats-in-detail { position: absolute; top: 49px; left: 68px; }\n",
|
||
".base-stats-row { height: 13px; width: 200px; }\n",
|
||
".pos-base-stats__label { position: absolute; left: 0px; text-align: left;}\n",
|
||
".pos-base-stats__source { position: absolute; left: 55px; width: 55px; text-align: right;}\n",
|
||
".pos-base-stats__source-perc { position: absolute; left: 113px; width: 35px; text-align: right;}\n",
|
||
".pos-base-stats__compare { position: absolute; left: 153px; width: 55px; text-align: right;}\n",
|
||
".pos-base-stats__compare-perc { position: absolute; left: 211px; width: 35px; text-align: right;}\n",
|
||
"\n",
|
||
"/* These are all NUMERICAL SUMMARY actually! */\n",
|
||
".pos-summary-numeric-group1 { position: absolute; top: 67px; left: 372px; }\n",
|
||
".pos-summary-numeric-group2 { position: absolute; top: 67px; left: 560px; }\n",
|
||
".pos-summary-numeric-source { position: absolute; left: 40px; width: 50px; text-align: right;}\n",
|
||
".pos-summary-numeric-compare { position: absolute; left: 90px; width: 50px; text-align: right;}\n",
|
||
".pos-summary-numeric-source-wide { position: absolute; left: 40px; width: 64px; text-align: right;}\n",
|
||
".pos-summary-numeric-compare-wide { position: absolute; left: 104px; width: 64px; text-align: right;}\n",
|
||
".pos-detail-num__top { position: absolute; top: 63px; line-height: 13px; }\n",
|
||
".pos-detail-num-col1__labels { left: 320px; text-align: left; }\n",
|
||
".pos-detail-num-col1__source { right: 636px; text-align: right;}\n",
|
||
".pos-detail-num-col1__compare { right: 581px; text-align: right; }\n",
|
||
".pos-detail-num-col2__labels { left: 520px; text-align: left; }\n",
|
||
".pos-detail-num-col2__source { right: 441px; text-align: right;}\n",
|
||
".pos-detail-num-col2__compare { right: 386px; text-align: right; }\n",
|
||
"\n",
|
||
".pos-summary-text { position: absolute; left: 372px; top: 67px; }\n",
|
||
".summary-text { overflow: hidden; text-overflow: ellipsis; position: absolute; height: 14px; white-space: nowrap; }\n",
|
||
"\n",
|
||
".pos-minigraph-cat { position: absolute; right: 40px; top: 62px; }\n",
|
||
".pos-minigraph-numeric { position: absolute; right: 40px; top: 62px; }\n",
|
||
"\n",
|
||
".selector {}\n",
|
||
".selector__body { z-index:10; position: absolute; left: 0px; top:40px; width: 1040px; height: 134px; }\n",
|
||
".selector__bottom { z-index:10; position: absolute; left: 305px; top:174px; width: 735px; height: 22px; }\n",
|
||
".selector__top { z-index:10; position: absolute; left: 0px; top:16px; width: 305px; height: 24px; }\n",
|
||
"\n",
|
||
"/*\n",
|
||
"DETAILS\n",
|
||
"------------------------------------*/\n",
|
||
".pos-detail-cat-graph { position: absolute; left: 45px; top: 120px; }\n",
|
||
".pos-detail-cat-breakdown { position: absolute; left: 44px; overflow: hidden; }\n",
|
||
".pos-detail-num-graph { position: absolute; left: 50px; top: 78px; }\n",
|
||
".pos-detail-num-buttons { position: absolute; left: 400px; top: 46px; width: 212px; }\n",
|
||
"\n",
|
||
".pos-detail-assoc-graph { position: absolute; left: 28px; top: 84px; }\n",
|
||
".pos-detail-assoc-desc-text { position: absolute; left: 37px; top: 41px; width: 800px; line-height: 11px;}\n",
|
||
"\n",
|
||
".pos-detail-text { position: absolute; left: 45px; top: 75px; }\n",
|
||
"\n",
|
||
"/* DETAIL LISTS */\n",
|
||
".container-detail-assoc { position: absolute; left: 40px; top: 27px; width: 215px;}\n",
|
||
".pos-detail-num-most { position: absolute; left: 20px; top: 606px; }\n",
|
||
".pos-detail-num-min { position: absolute; left: 313px; top: 606px; }\n",
|
||
".pos-detail-num-max { position: absolute; left: 607px; top: 606px; }\n",
|
||
".pos-detail-num-label { position: absolute; left: 0px; width: 56px; }\n",
|
||
".pos-detail-num-source-pair { position: absolute; width: 84px; left: 53px;}\n",
|
||
".pos-detail-num-compare-pair { position: absolute; width: 84px; left: 135px;}\n",
|
||
".pos-detail-num-pair-pos__num { position: absolute; left: 0px; width: 42px; text-align: right;}\n",
|
||
".pos-detail-num-pair-pos__perc { position: absolute; left: 49px; width: 30px; text-align: right; }\n",
|
||
"\n",
|
||
"/* Number, percentage pairs in CATEGORICAL breakdown */\n",
|
||
".pair__col { position: absolute; width: 84px; }\n",
|
||
".pair__header { position: absolute; width: 79px; text-align: center;}\n",
|
||
".pair-pos__num { position: absolute; left: 0px; width: 42px; text-align: right;}\n",
|
||
".pair-pos__perc { position: absolute; left: 49px; width: 30px; text-align: right; }\n",
|
||
"\n",
|
||
"/* DETAIL-ASSOC */\n",
|
||
".pos-detail-cat-assoc-1 { position: absolute; left: 618px; top: 28px; width: 275px;}\n",
|
||
".pos-detail-cat-assoc-CN { position: absolute; left: 618px; top: 565px; width: 275px;}\n",
|
||
".pos-assoc-row__label { position: absolute; left: 0px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; width: 156px;}\n",
|
||
".pos-assoc-row__source { position: absolute; left: 150px; text-align: right; width: 30px; }\n",
|
||
".pos-assoc-row__compare { position: absolute; left: 120px; text-align: right; width: 30px; }\n",
|
||
"\n",
|
||
"/* NUM-DETAIL COLS */\n",
|
||
".pos-num-detail-row__label { position: absolute; left: 0px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; width: 62px;}\n",
|
||
"\n",
|
||
"hr { background-color: #58544f; height: 1px; border-width: 0px; }\n",
|
||
"\n",
|
||
"button\n",
|
||
"{\n",
|
||
"\tbox-shadow:inset 0px 1px 0px 0px #ffffff;\n",
|
||
"\tbackground:linear-gradient(to bottom, #f9f9f9 5%, #e9e9e9 100%);\n",
|
||
"\tbackground-color:#f9f9f9;\n",
|
||
"\tborder-radius:6px;\n",
|
||
"\tborder:1px solid #dcdcdc;\n",
|
||
"\tdisplay:inline-block;\n",
|
||
"\tcursor:pointer;\n",
|
||
"\tcolor:#666666;\n",
|
||
"\tfont-family:Arial;\n",
|
||
"\tfont-size:10px;\n",
|
||
"\tpadding:3px 13px;\n",
|
||
"\ttext-decoration:none;\n",
|
||
"\ttext-shadow:0px 1px 0px #ffffff;\n",
|
||
"}\n",
|
||
".button-assoc {\n",
|
||
" outline: none;\n",
|
||
"}\n",
|
||
".button-assoc:hover {\n",
|
||
"\tborder:2px solid #221f1f;\n",
|
||
" outline: none;\n",
|
||
"}\n",
|
||
".button-assoc:focus {\n",
|
||
" outline: none;\n",
|
||
"}\n",
|
||
".button-assoc-selected {\n",
|
||
"\tborder:2px solid #ff0000;\n",
|
||
"}\n",
|
||
".button-assoc-selected:hover {\n",
|
||
"\tborder:2px solid #ff0000;\n",
|
||
"}\n",
|
||
".button-assoc-selected:focus {\n",
|
||
"\tborder:2px solid #ff0000;\n",
|
||
" outline: none;\n",
|
||
"}\n",
|
||
" </style>\n",
|
||
"\n",
|
||
" <style>\n",
|
||
"\n",
|
||
" span.minigraph-f0::before { content: 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);}\n",
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);}\n",
|
||
" span.detail_graph-f1-5::before { content: 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);}\n",
|
||
" span.detail_graph-f1-15::before { content: 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);}\n",
|
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);}\n",
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);}\n",
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||
" span.detail_graph-f2-5::before { content: 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);}\n",
|
||
" span.detail_graph-f2-15::before { content: 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);}\n",
|
||
" span.detail_graph-f2-30::before { content: url(data:image/png;base64,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);}\n",
|
||
" span.association-graph-source::before { content: 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);}\n",
|
||
" span.association-graph-compare::before { content: url(data:image/png;base64,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);}\n",
|
||
" span.graph-legend { content: url(data:image/png;base64,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);}\n",
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" </style>\n",
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"<script>\n",
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" g_height = 946;\n",
|
||
" g_scale = 1.0;\n",
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||
"</script>\n",
|
||
"</head>\n",
|
||
"\n",
|
||
"<body>\n",
|
||
"<div class="page-root-vertical">\n",
|
||
" <!-- TOP HEADER -->\n",
|
||
" <!-- ALL SUMMARY TABS -->\n",
|
||
" <div class="page-column-main" id="col1" style="transform: scale(1.0);transform-origin: 0 0;">\n",
|
||
" <!-- DF Summary -->\n",
|
||
"\n",
|
||
" <!-- ASSOCIATIONS (VERTICAL ONLY) -->\n",
|
||
" <div class="isHidden container-feature-detail" id="df-assoc-source"Yellow\n",
|
||
" style="display: contents; "\n",
|
||
">\n",
|
||
"<div class="container-feature-detail__offset"\n",
|
||
" style="position: absolute; top: 137px"\n",
|
||
">\n",
|
||
" <span class="bg-tab-detail-wide"></span>\n",
|
||
" <span class="text-title-tab pos-text-title-tab__no-icon">Associations</span>\n",
|
||
" <div class="text-med pos-detail-assoc-desc-text" style="font-size: 11px;">\n",
|
||
" <span class="color-source">[Only including dataset "DataFrame"]</span><br>\n",
|
||
" &#9632; <b>Squares</b> are categorical associations (uncertainty coefficient & correlation ratio) from 0 to 1. The uncertainty coefficient is <b>assymmetrical</b>,\n",
|
||
" (i.e. ROW LABEL values indicate how much they PROVIDE INFORMATION to each LABEL at the TOP).\n",
|
||
" <br><br>&#8226; <b>Circles</b> are the symmetrical numerical correlations (Pearson's) from -1 to 1. The <b>trivial diagonal</b> is intentionally left blank for clarity.\n",
|
||
" </div>\n",
|
||
" <span class="association-graph-source pos-detail-assoc-graph"></span>\n",
|
||
"</div>\n",
|
||
"</div>\n",
|
||
"\n",
|
||
" <div class="isHidden container-feature-detail" id="df-assoc-compare"Yellow\n",
|
||
" style="display: contents; "\n",
|
||
">\n",
|
||
"<div class="container-feature-detail__offset"\n",
|
||
" style="position: absolute; top: 137px"\n",
|
||
">\n",
|
||
" <span class="bg-tab-detail-wide"></span>\n",
|
||
" <span class="text-title-tab pos-text-title-tab__no-icon">Associations</span>\n",
|
||
" <div class="text-med pos-detail-assoc-desc-text" style="font-size: 11px;">\n",
|
||
" <span class="color-compare">[Only including dataset "None"]</span><br>\n",
|
||
" &#9632; <b>Squares</b> are categorical associations (uncertainty coefficient & correlation ratio) from 0 to 1. The uncertainty coefficient is <b>assymmetrical</b>,\n",
|
||
" (i.e. ROW LABEL values indicate how much they PROVIDE INFORMATION to each LABEL at the TOP).\n",
|
||
" <br><br>&#8226; <b>Circles</b> are the symmetrical numerical correlations (Pearson's) from -1 to 1. The <b>trivial diagonal</b> is intentionally left blank for clarity.\n",
|
||
" </div>\n",
|
||
" <span class="association-graph-compare pos-detail-assoc-graph"></span>\n",
|
||
"</div>\n",
|
||
"</div>\n",
|
||
"\n",
|
||
"\n",
|
||
" <!-- ALL SUMMARIES -->\n",
|
||
" <div class="container-feature-summary" id="summary-df" data-detail-div="detail-df">\n",
|
||
" <div class="pos-dataframe-summary text-label">\n",
|
||
" <span class="top-header"></span>\n",
|
||
" <div class="pos-dataframe-summary-title-source text-dataframe-title color-source">DataFrame</div>\n",
|
||
" <div class="pos-dataframe-summary-title-compare-none text-dataframe-title-small color-title-disabled">NO COMPARISON TARGET</div>\n",
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||
" <div class="pos-dataframe-summary-rows">\n",
|
||
" <div class="dataframe-summary-row row-colored">\n",
|
||
" <div class="pos-df-summary-source color-source">1846</div>\n",
|
||
" <div class="pos-df-summary-center">ROWS</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare"></div>\n",
|
||
" </div>\n",
|
||
" <div class="dataframe-summary-row">\n",
|
||
" <div class="pos-df-summary-source color-source">0</div>\n",
|
||
" <div class="pos-df-summary-center">DUPLICATES</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare"></div>\n",
|
||
" </div>\n",
|
||
" <div class="dataframe-summary-row row-colored">\n",
|
||
" <div class="pos-df-summary-source color-source">147.5 kb</div>\n",
|
||
" <div class="pos-df-summary-center">RAM</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare"></div>\n",
|
||
" </div>\n",
|
||
" <div class="dataframe-summary-row row">\n",
|
||
" <div class="pos-df-summary-source color-source">\n",
|
||
" 3\n",
|
||
" </div>\n",
|
||
" <div class="pos-df-summary-center">FEATURES</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare">\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="dataframe-summary-row row-colored">\n",
|
||
" <div class="pos-df-summary-source color-source">1</div>\n",
|
||
" <div class="pos-df-summary-center">CATEGORICAL</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare"></div>\n",
|
||
" </div>\n",
|
||
" <div class="dataframe-summary-row ">\n",
|
||
" <div class="pos-df-summary-source color-source">2</div>\n",
|
||
" <div class="pos-df-summary-center">NUMERICAL</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare"></div>\n",
|
||
" </div>\n",
|
||
" <div class="dataframe-summary-row row-colored">\n",
|
||
" <div class="pos-df-summary-source color-source">0</div>\n",
|
||
" <div class="pos-df-summary-center">TEXT</div>\n",
|
||
" <div class="pos-df-summary-compare color-compare"></div>\n",
|
||
" </div>\n",
|
||
" <button class="button-assoc color-source button-border-source size-df-summary-button pos-df-summary-button-assoc-source" id="button-summary-associations-source"\n",
|
||
" data-detail-div="df-assoc-source">ASSOCIATIONS</button >\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"</div>\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
" <div class="pos-logo-group">\n",
|
||
" <div class="pos-logo im-logo"></div>\n",
|
||
" <div class="pos-credits text-credits">\n",
|
||
" <span class="text-version">2.3.1<br>\n",
|
||
" <a href="https://github.com/fbdesignpro/sweetviz">Get updates, docs & report issues here</a></span><br>\n",
|
||
" Created & maintained by <a href="https://www.fbdesignpro.com">Francois Bertrand</a> <br>\n",
|
||
" Graphic design by <a href="https://www.fbdesignpro.com" data-reach="Jeff is working on his contact info :)">Jean-Francois Hains</a>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="page-all-summaries">\n",
|
||
" <span class="graph-legend" style="left: 391px;position: absolute;top: 5px;"></span>\n",
|
||
" <!-- TARGET Summary -->\n",
|
||
" <!-- FEATURE Summaries -->\n",
|
||
" <div class="pos-feature-summary" style="top: 0.0px">\n",
|
||
" <div class="container-feature-summary" id="summary-f0"\n",
|
||
" style="top: 0px">\n",
|
||
" <div class="selector selector__body" data-detail-div="detail-f0" data-rollover-span="rollover-f0"></div>\n",
|
||
" <div class="selector selector__bottom" data-detail-div="detail-f0" data-rollover-span="rollover-f0"></div>\n",
|
||
" <div class="selector selector__top" data-detail-div="detail-f0" data-rollover-span="rollover-f0"></div>\n",
|
||
" <span class="bg-tab-summary" style="z-index: -20000"></span>\n",
|
||
" <span class="bg-tab-summary-rollover" id="rollover-f0" style="z-index: -19999"></span>\n",
|
||
" <div class="summary-number"\n",
|
||
" >\n",
|
||
" 1\n",
|
||
" </div>\n",
|
||
" <div class="pos-tab-image ic-cat"></div>\n",
|
||
" <span class="text-title-tab color-normal ">dataset</span>\n",
|
||
" <div class="pos-base-stats">\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">VALUES:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" 1,846\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
" (100%)\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">MISSING:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" ---\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc" >\n",
|
||
"\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">DISTINCT:</div>\n",
|
||
" <div class="text-distinct color-source pos-base-stats__source">\n",
|
||
" 13\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
" (<1%)\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <span class="minigraph-f0 pos-minigraph-cat"></span>\n",
|
||
"</div>\n",
|
||
" <!-- This DETAIL WINDOW (VERTICAL ONLY) -->\n",
|
||
" <div class="isHidden container-feature-detail-vertical"\n",
|
||
" style="top: 157px"\n",
|
||
" id="detail-f0">\n",
|
||
"<div class="container-feature-detail__offset">\n",
|
||
"\n",
|
||
" <span class="detail_graph-f0-\n",
|
||
" pos-detail-cat-graph" id="detail_graph-f0"\n",
|
||
" style="top: 75px;"></span>\n",
|
||
"\n",
|
||
" <div class="pos-detail-cat-breakdown " id="detail_breakdown-f0"\n",
|
||
" style="top: 614.0px;"> <!-- height: 296.0px;"> WHY was this needed? Causes issue in vertical layout. -->\n",
|
||
" <!-- HEADER ROW -->\n",
|
||
" <div class="breakdown-row-header text-value" style="width:553px">\n",
|
||
" <div class="text-med-bold" style="position: absolute; left:10px">TOP CATEGORIES</div>\n",
|
||
" <div class="breakdown-hr"><hr></div>\n",
|
||
" <div class="pair__header color-source" style="left: 90px"></div>\n",
|
||
" <!-- Targets -->\n",
|
||
" <div class="pair__header color-compare" style="position: absolute; left: px">\n",
|
||
" <!--None-->\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <!-- ROW CONTENT -->\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">dino</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">away</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">h_lines</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">v_lines</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">x_shape</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">star</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">high_lines</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">dots</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">circle</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">bullseye</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">slant_up</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">slant_down</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value " style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">wide_lines</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">142</div>\n",
|
||
" <div class="pair-pos__perc">8%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value" style="width:553px">\n",
|
||
" </div>\n",
|
||
" <div class="breakdown-row text-value row-colored" style="width:553px">\n",
|
||
" <!-- Name -->\n",
|
||
" <div class="text-label color-normal " style="position: absolute; left:10px;\n",
|
||
" width: 90px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;">ALL</div>\n",
|
||
"\n",
|
||
" <!-- Freq -->\n",
|
||
" <div class="pair__col color-source" style="left: 90px">\n",
|
||
" <div class="pair-pos__num dim">1,846</div>\n",
|
||
" <div class="pair-pos__perc">100%</div>\n",
|
||
" </div>\n",
|
||
" <!-- Targets -->\n",
|
||
" </div>\n",
|
||
" <div id="detail_cat_end-0"></div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <!-- ASSOCIATIONS -->\n",
|
||
" <div class="pos-detail-cat-assoc-1" id="cat-assoc-CC-f0">\n",
|
||
" <!-- no background for target in vertical mode -->\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc " id="cat-assoc-window-f0">\n",
|
||
" <!-- CAT-CAT -->\n",
|
||
" <div class="text-small-bold color-light" style="text-align:right; line-height: 10px">\n",
|
||
" CATEGORICAL ASSOCIATIONS<br>\n",
|
||
" (UNCERTAINTY COEFFICIENT, 0 to 1)\n",
|
||
" </div>\n",
|
||
" <div class="text-large-bold" style="line-height: 104%;">dataset<br>\n",
|
||
" PROVIDES INFORMATION ON...</div>\n",
|
||
" <hr>\n",
|
||
" <br>\n",
|
||
" <div class="text-large-bold" style="line-height: 104%;">THESE FEATURES<br>GIVE INFORMATION<br>\n",
|
||
" ON dataset:</div>\n",
|
||
" <hr>\n",
|
||
" <br>\n",
|
||
" <!-- CAT-NUM -->\n",
|
||
" <div class="text-small-bold color-light" style="text-align:right; line-height: 10px">\n",
|
||
" NUMERICAL ASSOCIATIONS<br>\n",
|
||
" (CORRELATION RATIO, 0 to 1)\n",
|
||
" </div>\n",
|
||
" <div class="text-large-bold" style="line-height: 104%;">dataset<br>\n",
|
||
" CORRELATION RATIO WITH...</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row " >\n",
|
||
" <div class="pos-assoc-row__label text-label">x</div>\n",
|
||
" <div class="pos-assoc-row__source text-label color-source">0.00</div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored" >\n",
|
||
" <div class="pos-assoc-row__label text-label">y</div>\n",
|
||
" <div class="pos-assoc-row__source text-label color-source">0.00</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"</div>\n",
|
||
"</div>\n",
|
||
" </div>\n",
|
||
" <div class="pos-feature-summary" style="top: 0.0px">\n",
|
||
" <div class="container-feature-summary" id="summary-f1"\n",
|
||
" style="top: 0px">\n",
|
||
" <div class="selector selector__body" data-detail-div="detail-f1" data-rollover-span="rollover-f1"></div>\n",
|
||
" <div class="selector selector__bottom" data-detail-div="detail-f1" data-rollover-span="rollover-f1"></div>\n",
|
||
" <div class="selector selector__top" data-detail-div="detail-f1" data-rollover-span="rollover-f1"></div>\n",
|
||
" <span class="bg-tab-summary" style="z-index: -19998"></span>\n",
|
||
" <span class="bg-tab-summary-rollover" id="rollover-f1" style="z-index: -19997"></span>\n",
|
||
" <div class="summary-number"\n",
|
||
" >\n",
|
||
" 2\n",
|
||
" </div>\n",
|
||
" <div class="pos-tab-image ic-numeric"></div>\n",
|
||
" <span class="text-title-tab color-normal">x</span>\n",
|
||
"\n",
|
||
" <div class="pos-base-stats">\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">VALUES:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" 1,846\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
" (100%)\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">MISSING:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" ---\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc" >\n",
|
||
"\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">DISTINCT:</div>\n",
|
||
" <div class="text-distinct color-source pos-base-stats__source">\n",
|
||
" 1,804\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
" (98%)\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">ZEROES:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" ---\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
"\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <div class="pos-summary-numeric-group1">\n",
|
||
" <div class="row-numeric-summary row-separator-bottom ">\n",
|
||
" <div class="text-label" style="position:absolute">MAX</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">98.3</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">95%</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">81.1</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">Q3</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">67.3</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">AVG</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">54.3</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">MEDIAN</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">52.6</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">Q1</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">41.1</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">5%</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">27.9</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary row-separator-top ">\n",
|
||
" <div class="text-label" style="position:absolute">MIN</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">15.6</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="pos-summary-numeric-group2">\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">RANGE</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">82.7</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">IQR</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">26.2</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">STD</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">16.7</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">VAR</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">279</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">KURT.</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">-0.696</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">SKEW</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">0.135</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">SUM</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">100k</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <span class="minigraph-f1 pos-minigraph-numeric"></span>\n",
|
||
"</div>\n",
|
||
" <!-- This DETAIL WINDOW (VERTICAL ONLY) -->\n",
|
||
" <div class="isHidden container-feature-detail-vertical"\n",
|
||
" style="top: 157px"\n",
|
||
" id="detail-f1" >\n",
|
||
"<div class="container-feature-detail__offset">\n",
|
||
"\n",
|
||
" <!-- BUTTONS -->\n",
|
||
" <div class="pos-detail-num-buttons">\n",
|
||
" <button class="button-bin" data-target="detail_graph-f1"\n",
|
||
" data-new_class="detail_graph-f1-0">Auto </button>\n",
|
||
" <button class="button-bin" data-target="detail_graph-f1"\n",
|
||
" data-new_class="detail_graph-f1-5">5 </button>\n",
|
||
" <button class="button-bin" data-target="detail_graph-f1"\n",
|
||
" data-new_class="detail_graph-f1-15">15 </button>\n",
|
||
" <button class="button-bin" data-target="detail_graph-f1"\n",
|
||
" data-new_class="detail_graph-f1-30">30 </button>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <!-- GRAPH -->\n",
|
||
" <span class="detail_graph-f1-0\n",
|
||
" pos-detail-num-graph" id="detail_graph-f1"></span>\n",
|
||
"\n",
|
||
" <!-- ASSOCIATIONS -->\n",
|
||
" <div class="pos-detail-cat-assoc-1" id="cat-assoc-CN-f1">\n",
|
||
" <span class="bg-extra-column" <!-- expand if target in vertical layout -->\n",
|
||
" ></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold">NUMERICAL ASSOCIATIONS</div>\n",
|
||
" <div class="text-small-bold color-light" style="line-height: 10px">\n",
|
||
" (PEARSON, -1 to 1)\n",
|
||
" </div>\n",
|
||
"<!-- <div class="text-med-bold">x</div>\n",
|
||
" <div class="text-large-bold">CORRELATION RATIO WITH...</div>\n",
|
||
"-->\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row " >\n",
|
||
" <div class="pos-assoc-row__label text-label">y</div>\n",
|
||
" <div class="pos-assoc-row__source text-label color-red">-0.07</div>\n",
|
||
" </div>\n",
|
||
" <br>\n",
|
||
" <div class="text-large-bold">CATEGORICAL ASSOCIATIONS</div>\n",
|
||
" <div class="text-small-bold color-light" style="line-height: 10px">\n",
|
||
" (CORRELATION RATIO, 0 to 1)\n",
|
||
" </div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row " >\n",
|
||
" <div class="pos-assoc-row__label text-label">dataset</div>\n",
|
||
" <div class="pos-assoc-row__source text-label color-source">0.00</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <!-- FREQUENT -->\n",
|
||
" <div class="pos-detail-num-most">\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold">MOST FREQUENT VALUES</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">50.0</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">4</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">56.6667</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">4</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">29.7436</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">4</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">44.1026</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">59.2308</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">67.9487</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">55.3846</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">51.5385</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">46.1538</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">42.8205</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">38.7179</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">22.3077</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">53.0769</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">61.2821</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">61.7949</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <!-- MINIMUM -->\n",
|
||
" <div class="pos-detail-num-min">\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold"> SMALLEST VALUES</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">15.5607495229</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">17.8934987136</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">18.1094722949</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">19.2882047369</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">20.0245005746</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">20.2097781637</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">20.4089478892</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">20.6891490538</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">20.9319996761</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">20.9594648125</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">21.0379688969</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">21.7780404779</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">21.7960992263</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">21.8635812756</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">22.0037091415</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <!-- MAXIMUM -->\n",
|
||
" <div class="pos-detail-num-max">\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold">LARGEST VALUES</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.2881232748</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.2051</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">96.0805193672</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">95.5934163965</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">95.4434878077</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">95.3846</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">95.2605278366</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">95.2492339568</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">95.0652748396</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">94.9974880471</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">93.3333</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">92.5487933153</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">92.2484016622</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">92.2478988278</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">92.0175590822</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
"</div>\n",
|
||
"</div>\n",
|
||
" </div>\n",
|
||
" <div class="pos-feature-summary" style="top: 0.0px">\n",
|
||
" <div class="container-feature-summary" id="summary-f2"\n",
|
||
" style="top: 0px">\n",
|
||
" <div class="selector selector__body" data-detail-div="detail-f2" data-rollover-span="rollover-f2"></div>\n",
|
||
" <div class="selector selector__bottom" data-detail-div="detail-f2" data-rollover-span="rollover-f2"></div>\n",
|
||
" <div class="selector selector__top" data-detail-div="detail-f2" data-rollover-span="rollover-f2"></div>\n",
|
||
" <span class="bg-tab-summary" style="z-index: -19996"></span>\n",
|
||
" <span class="bg-tab-summary-rollover" id="rollover-f2" style="z-index: -19995"></span>\n",
|
||
" <div class="summary-number"\n",
|
||
" >\n",
|
||
" 3\n",
|
||
" </div>\n",
|
||
" <div class="pos-tab-image ic-numeric"></div>\n",
|
||
" <span class="text-title-tab color-normal">y</span>\n",
|
||
"\n",
|
||
" <div class="pos-base-stats">\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">VALUES:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" 1,846\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
" (100%)\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">MISSING:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" ---\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc" >\n",
|
||
"\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">DISTINCT:</div>\n",
|
||
" <div class="text-distinct color-source pos-base-stats__source">\n",
|
||
" 1,807\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
" (98%)\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" </div>\n",
|
||
" <div class="base-stats-row">\n",
|
||
" <div class="text-label color-normal pos-base-stats__label ">ZEROES:</div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source">\n",
|
||
" ---\n",
|
||
" </div>\n",
|
||
" <div class="text-value color-source pos-base-stats__source-perc">\n",
|
||
"\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <div class="pos-summary-numeric-group1">\n",
|
||
" <div class="row-numeric-summary row-separator-bottom ">\n",
|
||
" <div class="text-label" style="position:absolute">MAX</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">99.7</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">95%</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">90.1</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">Q3</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">71.8</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">AVG</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">47.8</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">MEDIAN</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">47.6</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">Q1</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">22.6</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary ">\n",
|
||
" <div class="text-label" style="position:absolute">5%</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">10.6</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary row-separator-top ">\n",
|
||
" <div class="text-label" style="position:absolute">MIN</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">0.0</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="pos-summary-numeric-group2">\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">RANGE</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">99.7</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">IQR</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">49.2</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">STD</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">26.8</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">VAR</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">721</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">KURT.</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">-1.28</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">SKEW</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">0.160</div>\n",
|
||
" </div>\n",
|
||
" <div class="row-numeric-summary">\n",
|
||
" <div class="text-label" style="position:absolute">SUM</div>\n",
|
||
" <div class="pos-summary-numeric-source text-value color-source">88,304</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <span class="minigraph-f2 pos-minigraph-numeric"></span>\n",
|
||
"</div>\n",
|
||
" <!-- This DETAIL WINDOW (VERTICAL ONLY) -->\n",
|
||
" <div class="isHidden container-feature-detail-vertical"\n",
|
||
" style="top: 157px"\n",
|
||
" id="detail-f2" >\n",
|
||
"<div class="container-feature-detail__offset">\n",
|
||
"\n",
|
||
" <!-- BUTTONS -->\n",
|
||
" <div class="pos-detail-num-buttons">\n",
|
||
" <button class="button-bin" data-target="detail_graph-f2"\n",
|
||
" data-new_class="detail_graph-f2-0">Auto </button>\n",
|
||
" <button class="button-bin" data-target="detail_graph-f2"\n",
|
||
" data-new_class="detail_graph-f2-5">5 </button>\n",
|
||
" <button class="button-bin" data-target="detail_graph-f2"\n",
|
||
" data-new_class="detail_graph-f2-15">15 </button>\n",
|
||
" <button class="button-bin" data-target="detail_graph-f2"\n",
|
||
" data-new_class="detail_graph-f2-30">30 </button>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <!-- GRAPH -->\n",
|
||
" <span class="detail_graph-f2-0\n",
|
||
" pos-detail-num-graph" id="detail_graph-f2"></span>\n",
|
||
"\n",
|
||
" <!-- ASSOCIATIONS -->\n",
|
||
" <div class="pos-detail-cat-assoc-1" id="cat-assoc-CN-f2">\n",
|
||
" <span class="bg-extra-column" <!-- expand if target in vertical layout -->\n",
|
||
" ></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold">NUMERICAL ASSOCIATIONS</div>\n",
|
||
" <div class="text-small-bold color-light" style="line-height: 10px">\n",
|
||
" (PEARSON, -1 to 1)\n",
|
||
" </div>\n",
|
||
"<!-- <div class="text-med-bold">y</div>\n",
|
||
" <div class="text-large-bold">CORRELATION RATIO WITH...</div>\n",
|
||
"-->\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row " >\n",
|
||
" <div class="pos-assoc-row__label text-label">x</div>\n",
|
||
" <div class="pos-assoc-row__source text-label color-red">-0.07</div>\n",
|
||
" </div>\n",
|
||
" <br>\n",
|
||
" <div class="text-large-bold">CATEGORICAL ASSOCIATIONS</div>\n",
|
||
" <div class="text-small-bold color-light" style="line-height: 10px">\n",
|
||
" (CORRELATION RATIO, 0 to 1)\n",
|
||
" </div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row " >\n",
|
||
" <div class="pos-assoc-row__label text-label">dataset</div>\n",
|
||
" <div class="pos-assoc-row__source text-label color-source">0.00</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <!-- FREQUENT -->\n",
|
||
" <div class="pos-detail-num-most">\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold">MOST FREQUENT VALUES</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">10.641</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">6</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.3%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">51.0256</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">51.4103</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">55.2564</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">46.0256</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">25.2564</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">18.3333</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">14.8718</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">3</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.2%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">79.8718</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">77.5641</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">71.4103</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">66.4103</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">52.9487</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">62.1795</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">38.3333</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">2</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc">0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <!-- MINIMUM -->\n",
|
||
" <div class="pos-detail-num-min">\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold"> SMALLEST VALUES</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">0.0151193251552</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">0.217006270014</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">0.30387242055</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">0.5091067352</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">0.601490941965</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">1.13388036584</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">1.21055166293</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">1.48813233299</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">1.50441817488</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">1.74146171252</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">1.80811559665</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">2.33519661206</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">2.73476016988</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">2.9487</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">3.7168538855</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <!-- MAXIMUM -->\n",
|
||
" <div class="pos-detail-num-max">\n",
|
||
" <span class="bg-extra-column"></span>\n",
|
||
" <div class="container-detail-assoc">\n",
|
||
" <div class="text-large-bold">LARGEST VALUES</div>\n",
|
||
" <hr>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.6946801425</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.6441791736</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.6134716833</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.5795911254</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.4872</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.2837639519</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.2568672885</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">99.1026</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.9310270371</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.6283694405</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.6038611855</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.1843018589</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">98.1651568396</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row row-colored">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">97.8376147235</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" <div class="assoc-row ">\n",
|
||
" <div class="pos-num-detail-row__label text-label pos-detail-num-label">97.6099835723</div>\n",
|
||
" <div class="pos-detail-num-source-pair color-source text-value">\n",
|
||
" <div class="pos-detail-num-pair-pos__num dim">1</div>\n",
|
||
" <div class="pos-detail-num-pair-pos__perc"><0.1%</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
"</div>\n",
|
||
"</div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
" </div>\n",
|
||
"\n",
|
||
" <!-- ALL DETAIL WINDOWS (WIDESCREEN ONLY) -->\n",
|
||
"</div>\n",
|
||
"</body>\n",
|
||
"</html>\" frameborder=\"0\" allowfullscreen></iframe>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2026-02-22 11:37:04,556 - INFO - Executing shutdown due to inactivity...\n",
|
||
"2026-02-22 11:37:08,648 - INFO - Executing shutdown...\n",
|
||
"2026-02-22 11:37:08,650 - INFO - Not running with the Werkzeug Server, exiting by searching gc for BaseWSGIServer\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"report = sv.analyze(df)\n",
|
||
"#report.show_html(\"sweetviz_report.html\")\n",
|
||
"report.show_notebook()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "678e3713",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"Explore:\n",
|
||
"\n",
|
||
"- Distributions\n",
|
||
"- Correlations\n",
|
||
"- Missing values\n",
|
||
"- Variable relationships\n",
|
||
"\n",
|
||
"What patterns do you notice?\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ee012206",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"## 6️⃣ Interactive Exploration (D-Tale)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "90110819",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2026-02-22 09:59:06,283 - ERROR - Exception on /dtale/charts/_dash-update-component [POST]\n",
|
||
"Traceback (most recent call last):\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 1473, in wsgi_app\n",
|
||
" response = self.full_dispatch_request()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 882, in full_dispatch_request\n",
|
||
" rv = self.handle_user_exception(e)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 880, in full_dispatch_request\n",
|
||
" rv = self.dispatch_request()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 865, in dispatch_request\n",
|
||
" return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) # type: ignore[no-any-return]\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\dash.py\", line 1376, in dispatch\n",
|
||
" ctx.run(\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 507, in add_context\n",
|
||
" raise err\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 496, in add_context\n",
|
||
" output_value = _invoke_callback(func, *func_args, **func_kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 43, in _invoke_callback\n",
|
||
" return func(*args, **kwargs) # %% callback invoked %%\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\saved_charts.py\", line 215, in load_saved_chart\n",
|
||
" return dict(display=\"block\"), charts, config, build_saved_header(config)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\saved_charts.py\", line 106, in build_saved_header\n",
|
||
" if chart_type == \"scatter\" and config[\"trendline\"]:\n",
|
||
" ~~~~~~^^^^^^^^^^^^^\n",
|
||
"KeyError: 'trendline'\n",
|
||
"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\charts.py:4170: GuessedAtParserWarning:\n",
|
||
"\n",
|
||
"No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"html.parser\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
|
||
"\n",
|
||
"The code that caused this warning is on line 4170 of the file d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\charts.py. To get rid of this warning, pass the additional argument 'features=\"html.parser\"' to the BeautifulSoup constructor.\n",
|
||
"\n",
|
||
"\n",
|
||
"2026-02-22 10:02:45,101 - ERROR - Exception on /dtale/charts/_dash-update-component [POST]\n",
|
||
"Traceback (most recent call last):\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 1473, in wsgi_app\n",
|
||
" response = self.full_dispatch_request()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 882, in full_dispatch_request\n",
|
||
" rv = self.handle_user_exception(e)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 880, in full_dispatch_request\n",
|
||
" rv = self.dispatch_request()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 865, in dispatch_request\n",
|
||
" return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) # type: ignore[no-any-return]\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\dash.py\", line 1376, in dispatch\n",
|
||
" ctx.run(\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 507, in add_context\n",
|
||
" raise err\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 496, in add_context\n",
|
||
" output_value = _invoke_callback(func, *func_args, **func_kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 43, in _invoke_callback\n",
|
||
" return func(*args, **kwargs) # %% callback invoked %%\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\views.py\", line 1377, in group_values\n",
|
||
" group_vals = build_group_val_options(group_vals, group_cols)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\layout\\layout.py\", line 1341, in build_group_val_options\n",
|
||
" group_vals = find_group_vals(df, group_cols)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\charts\\utils.py\", line 1064, in find_group_vals\n",
|
||
" group_vals, _ = retrieve_chart_data(df, group_cols)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\charts\\utils.py\", line 368, in retrieve_chart_data\n",
|
||
" all_data = pd.concat(all_data, axis=1)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py\", line 407, in concat\n",
|
||
" objs, keys, ndims = _clean_keys_and_objs(objs, keys)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\reshape\\concat.py\", line 808, in _clean_keys_and_objs\n",
|
||
" raise ValueError(\"No objects to concatenate\")\n",
|
||
"ValueError: No objects to concatenate\n",
|
||
"2026-02-22 10:04:23,850 - ERROR - Exception on /dtale/charts/_dash-update-component [POST]\n",
|
||
"Traceback (most recent call last):\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 1473, in wsgi_app\n",
|
||
" response = self.full_dispatch_request()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 882, in full_dispatch_request\n",
|
||
" rv = self.handle_user_exception(e)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 880, in full_dispatch_request\n",
|
||
" rv = self.dispatch_request()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\flask\\app.py\", line 865, in dispatch_request\n",
|
||
" return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) # type: ignore[no-any-return]\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\dash.py\", line 1376, in dispatch\n",
|
||
" ctx.run(\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 507, in add_context\n",
|
||
" raise err\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 496, in add_context\n",
|
||
" output_value = _invoke_callback(func, *func_args, **func_kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dash\\_callback.py\", line 43, in _invoke_callback\n",
|
||
" return func(*args, **kwargs) # %% callback invoked %%\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\saved_charts.py\", line 215, in load_saved_chart\n",
|
||
" return dict(display=\"block\"), charts, config, build_saved_header(config)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\dash_application\\saved_charts.py\", line 106, in build_saved_header\n",
|
||
" if chart_type == \"scatter\" and config[\"trendline\"]:\n",
|
||
" ~~~~~~^^^^^^^^^^^^^\n",
|
||
"KeyError: 'trendline'\n",
|
||
"2026-02-22 10:23:45,299 - ERROR - Exception occurred while processing request: 'SeriesGroupBy' object has no attribute 'mad'\n",
|
||
"Traceback (most recent call last):\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\views.py\", line 121, in _handle_exceptions\n",
|
||
" return func(*args, **kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\views.py\", line 3192, in get_column_analysis\n",
|
||
" return jsonify(**analysis.build())\n",
|
||
" ^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\column_analysis.py\", line 140, in build\n",
|
||
" return_data, code = self.analysis.build(self)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\dtale\\column_analysis.py\", line 327, in build\n",
|
||
" ].agg(self.aggs)\n",
|
||
" ^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\groupby\\generic.py\", line 2291, in aggregate\n",
|
||
" result = op.agg()\n",
|
||
" ^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\apply.py\", line 297, in agg\n",
|
||
" return self.agg_list_like()\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\apply.py\", line 414, in agg_list_like\n",
|
||
" return self.agg_or_apply_list_like(op_name=\"agg\")\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\apply.py\", line 1640, in agg_or_apply_list_like\n",
|
||
" keys, results = self.compute_list_like(op_name, selected_obj, kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\apply.py\", line 473, in compute_list_like\n",
|
||
" new_res = getattr(colg, op_name)(func, *args, **kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\groupby\\generic.py\", line 464, in aggregate\n",
|
||
" ret = self._aggregate_multiple_funcs(func, *args, **kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\groupby\\generic.py\", line 522, in _aggregate_multiple_funcs\n",
|
||
" results[key] = self.aggregate(func, *args, **kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\groupby\\generic.py\", line 456, in aggregate\n",
|
||
" return getattr(self, func)(*args, **kwargs)\n",
|
||
" ^^^^^^^^^^^^^^^^^^^\n",
|
||
" File \"d:\\Projects\\43679_InteractiveVis\\VI_Lab_01_EDA\\.venv\\Lib\\site-packages\\pandas\\core\\groupby\\groupby.py\", line 1115, in __getattr__\n",
|
||
" raise AttributeError(\n",
|
||
"AttributeError: 'SeriesGroupBy' object has no attribute 'mad'\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"d = dtale.show(df, host='localhost')\n",
|
||
"d.open_browser()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "7c6e0b13",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6c82bcfd",
|
||
"metadata": {},
|
||
"source": [
|
||
"\n",
|
||
"Use D‑Tale to:\n",
|
||
"\n",
|
||
"- Sort values\n",
|
||
"- Filter rows\n",
|
||
"- Inspect unique values\n",
|
||
"- Look at correlations\n",
|
||
"\n",
|
||
"---\n",
|
||
"\n",
|
||
"## 7️⃣ Reflection Questions\n",
|
||
"\n",
|
||
"1. Why is it dangerous to rely only on summary statistics?\n",
|
||
"2. What new information did visualization reveal?\n",
|
||
"3. What would you check before doing any modeling?\n",
|
||
"4. What kinds of problems might real datasets contain?\n",
|
||
"\n",
|
||
"---\n",
|
||
"\n",
|
||
"Next classes: you will receive *messy datasets* that require cleaning and preparation.\n"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": ".venv",
|
||
"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": "3.11.9"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|