triestpa/ageagg.ipynb Secret

## ageagg.ipynb
{
 "cells": [
{
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1115a58d0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAEtCAYAAAD+y1AoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAFidJREFUeJzt3X+w5Xdd3/Hna7OhirSJGCe37rJsJxhJEKMIi1Ql1wTK\nxk7ZVC0kIIqVNtM2ArU6q07bbMc2IzN0hmGC0mQyCMgQqm0IFTDxRw5qIWTBJPzazQbFJdmEMAFC\nCTGyhnf/OGc3Z++ee+/37n73fs9n9/mYOTP3fM8n3+/rnpt93e/9fr/n+0lVIUlq04ahA0iSjp0l\nLkkNs8QlqWGWuCQ1zBKXpIZZ4pLUsE4lnmR7kr1J9iXZucyYxSR3JPlUklv7jSlJmiWrXSeeZAOw\nD7gYuB/YDVxWVXunxpwBfBj4J1V1IMlZVfXQiYstSYJue+LbgHuqan9VHQRuAHYsGfMK4H9V1QEA\nC1yS1keXEt8E3Dv1/L7JsmnnAk9NcmuS3Ule1VdASdLyNva4nucAFwHfBnwkyUeq6rM9rV+SNEOX\nEj8AbJl6vnmybNp9wENV9RjwWJI/BS4AjijxJN6oRZKOQVVl1vIuh1N2A89I8vQkTwIuA963ZMxN\nwI8kOS3Jk4HnA3uWCdLr46qrrup9nSfiYU5zzuujhYynes6VrLonXlWPJ7kSuIVx6V9fVXuSXDF+\nua6tqr1JbgY+ATwOXFtVn1lt3ZKk49PpmHhV/QHwPUuW/Y8lz98IvLG/aJKk1TT/ic3FxcWhI3Ri\nzn6Zsz8tZARzLmfVD/v0urGk1nN7knQySEIdx4lNSdKcmtsSX1jYSpJeHwsLW4f+tiSpV3N7OCUJ\n0He2rHq5jiTNGw+nSNJJyhKXpIZZ4pLUMEtckhpmiUtSwyxxSWqYJS5JDbPEJalhlrgkNcwSl6SG\nWeKS1DBLXJIaZolLUsMscUlqmCUuSQ2zxCWpYZa4JDXMEpekhlniktQwS1ySGmaJS1LDLHFJapgl\nLkkN61TiSbYn2ZtkX5KdM16/MMnDSf5i8viP/UeVJC21cbUBSTYA1wAXA/cDu5PcVFV7lwz906p6\n6QnIKElaRpc98W3APVW1v6oOAjcAO2aMS6/JJEmr6lLim4B7p57fN1m21AuS3Jnk/UnO7yWdJGlF\nqx5O6ejjwJaqejTJJcB7gXN7WrckaRldSvwAsGXq+ebJssOq6pGprz+Y5DeTPLWqvrx0Zbt27Tr8\n9eLiIouLi2uMLEknt9FoxGg06jQ2VbXygOQ04G7GJzYfAG4HLq+qPVNjzq6qBydfbwP+Z1VtnbGu\nWm17U2OBbmO7C123L0nzIglVNfO846p74lX1eJIrgVsYH0O/vqr2JLli/HJdC/xUkn8DHAT+Bnh5\nf/ElSctZdU+81425Jy5Ja7bSnrif2JSkhlniktQwS1w6SS0sbCVJr4+Fha1Df1tawmPi0knKf0Mn\nD4+JS9JJyhKXpIZZ4pLUMEtckhpmiUtSwyxxSWqYJS5JDbPEJalhlrgkNcwSl6SGWeKS1DBLXJIa\nZolLUsMscUlqmCUuSQ2zxCWpYZa4JDXMEpekhlniktQwS1ySGmaJS1LDLHHNjYWFrSTp9bGwsHXo\nb0s6oVJV67expLpuLwnQd7awnt+v1safeb98P08eSaiqzHrNPXFJapglLkkN61TiSbYn2ZtkX5Kd\nK4x7XpKDSX6iv4iSpOWsWuJJNgDXAC8BngVcnuSZy4z7DeDmvkNKkmbrsie+DbinqvZX1UHgBmDH\njHG/APwe8MUe80mSVtClxDcB9049v2+y7LAk3wVcWlW/Bcw8gypJ6l9fJzbfBEwfK7fIJWkdbOww\n5gCwZer55smyac8Fbsj4wtSzgEuSHKyq9y1d2a5duw5/vbi4yOLi4hojS9LJbTQaMRqNOo1d9cM+\nSU4D7gYuBh4Abgcur6o9y4x/G/B/qup/z3jtpPuwz8LCVh58cH9v6zv77KfzhS/8dW/ra0krP/NW\n+H6ePI7rwz5V9ThwJXAL8Gnghqrak+SKJP961n9yXGkbMy7w6u3R5y8EnRjeHkDzxI/dH+8ae895\n6u7pnLo/cziVc2p1fuxekk5SlrgkNcwSl6SGWeKS1DBLXJIaZolLUsMs8VOA1zVLJy+vEz/eNTZw\nnfip+16COec/p1bndeKSdJKyxCWpYZa4JDXMEpekhlniktQwS1ySGmaJS1LDLHFJapglLkkNs8Ql\nqWGWuCQ1zBKXpIZZ4pLUwbzeDdS7GB7vGr2LYX9rNGe/a2wkZyuGfD+9i6EknaQscUlqmCUuSQ2z\nxCWpYZa4JDXMEpekhnUq8STbk+xNsi/JzhmvvzTJXUnuSPKxJBf1H1WStNSq14kn2QDsAy4G7gd2\nA5dV1d6pMU+uqkcnXz8buLGqnjFjXV4nvvoaG8gI5jTnqabl68S3AfdU1f6qOgjcAOyYHnCowCee\nAjzUYb2SpOPUpcQ3AfdOPb9vsuwISS5Nsgf4APDafuJJklbS24nNqnpvVZ0H/DPgnX2tV5K0vI0d\nxhwAtkw93zxZNlNV/XmSjUm+o6q+tPT1Xbt2Hf56cXGRxcXFzmEl6VQwGo0YjUadxnY5sXkacDfj\nE5sPALcDl1fVnqkx51TVX06+fg7wu1V1zox1eWJz9TU2kBHMac5Tzbye2Fx1T7yqHk9yJXAL48Mv\n11fVniRXjF+ua4GfTPIzwDeArwMvX8N3IUk6Rt6K9njX6J54f2s0Z79rbCRnK+Z1T9xPbEpSwyxx\nSWqYJS5JDbPEJalhlrgkNcwSl6SGWeKS1DBLXJIaZolLUsMscUlqmCUuSQ2zxCWpYZa4JDXMEpek\nhlniktQwS1ySGmaJS1LDLHFJapglLkkNs8QlqWGWuCQ1zBKXpIZZ4pLUMEtckhpmiUtSwyxxSYNa\nWNhKkl4fCwtbh/621k2qav02llTX7SUB+s4W+v5++8/ZQkYwpzl7W6M5O227qjLrNffEJalhnUo8\nyfYke5PsS7JzxuuvSHLX5PHnSZ7df1RJ0lKrlniSDcA1wEuAZwGXJ3nmkmF/Bbywqi4A/itwXd9B\nJUlH67Invg24p6r2V9VB4AZgx/SAqrqtqr46eXobsKnfmJKkWbqU+Cbg3qnn97FySb8G+ODxhJIk\ndbOxz5Ul+THg54Af6XO9kqTZupT4AWDL1PPNk2VHSPJ9wLXA9qr6ynIr27Vr1+GvFxcXWVxc7BhV\nkk4No9GI0WjUaeyq14knOQ24G7gYeAC4Hbi8qvZMjdkC/DHwqqq6bYV1eZ346mtsICOY05y9rdGc\nnba93HXiq+6JV9XjSa4EbmF8DP36qtqT5Irxy3Ut8J+ApwK/mfF3erCqtq3hO5EkHQM/sXm8a3RP\nvL81mrPfNZqz3zXO6Z64n9iUpIZZ4pLUMEtckhpmiUtSwyxxSWqYJS5JDbPEJalhlrgkNcwSl6SG\nWeKS1DBLXJIaZolLUsMscUlqmCUuSQ2zxCWpYZa4JDXMEpekhlniktQwS1ySGmaJS1LDLHFJapgl\nLkkNs8QlqWGWuCQ1zBKXpIZZ4pLUMEtckhpmiUtSwzqVeJLtSfYm2Zdk54zXvyfJh5M8luQX+48p\nSZpl42oDkmwArgEuBu4Hdie5qar2Tg37EvALwKUnJKUkaaYue+LbgHuqan9VHQRuAHZMD6iqh6rq\n48DfnYCMkqRldCnxTcC9U8/vmyyTJA3ME5uS1LBVj4kDB4AtU883T5Ydk127dh3+enFxkcXFxWNd\nlSSdlEajEaPRqNPYVNXKA5LTgLsZn9h8ALgduLyq9swYexXwSFX992XWVattb2os0G1sd6Hr9juv\nsfecLWQEc5qztzWas9O2qyqzXlt1T7yqHk9yJXAL48Mv11fVniRXjF+ua5OcDXwM+PvAN5O8Dji/\nqh5Zw3cjSVqjVffEe92Ye+Jd1thARjCnOXtbozk7bXu5PXFPbEpSwyxxSWqYJS5JDbPEJalhlrgk\nNcwSl6SGWeKS1DBLXJIaZolLUsMscUlqmCUuSQ2zxCWpYZa4JDXMEpekhlniktQwS1ySGmaJS1LD\nLHFJapglLkkNs8QlqWGWuCQ1zBKXpIZZ4pLUMEtckhpmiUtSwyxxSWqYJS5JDbPEJalhnUo8yfYk\ne5PsS7JzmTFvTnJPkjuTfH+/MSVJs6xa4kk2ANcALwGeBVye5JlLxlwCnFNV3w1cAbz1BGRdxmj9\nNnVcRkMH6Gg0dICORkMH6Gg0dIAORkMH6Gg0dICORuu6tS574tuAe6pqf1UdBG4AdiwZswN4B0BV\nfRQ4I8nZvSZd1mh9NnPcRkMH6Gg0dICORkMH6Gg0dIAORkMH6Gg0dICORuu6tS4lvgm4d+r5fZNl\nK405MGOMJKlnntiUpIalqlYekPwQsKuqtk+e/wpQVfWGqTFvBW6tqvdMnu8FLqyqB5esa+WNSZJm\nqqrMWr6xw3+7G3hGkqcDDwCXAZcvGfM+4N8B75mU/sNLC3ylEJKkY7NqiVfV40muBG5hfPjl+qra\nk+SK8ct1bVV9IMmPJ/ks8HXg505sbEkSdDicIkmaX57YlKSGWeKS1LAuJzbnQpKf6DDssar6wAkP\ns4Ik7+sw7MtV9eoTnWUl5uxXCzlbyAjmXKtmShy4DrgJWOkKlxcCg5Y4cB7wmhVeD/CWdcqyEnP2\nq4WcLWQEc65NVTXxAH6njzHrkPNlfYwxpzlPxYzmXPvDq1MkqWEtHU4hyRnAdp64L8sB4Oaqeni4\nVEdKshH4eeCfA981WXyA8aGg62t8E7HBmbNfLeRsISOYc805WtkTT/IzwFWMP3R0YLJ4M/Bi4L9U\n1TuGyjYtybuBh4G3M75ZGIxz/izw1Kp6+VDZppmzXy3kbCEjmHPNORoq8buB5y/d607y7cBHq+rc\nYZIdKcm+5bKs9Np6M2e/WsjZQkYw51q1dJ14gFm/cb7JylesrLcvJ/kXk8k0gPHEGkleDnxlwFxL\nmbNfLeRsISOYc01a2hP/WeA/Mz6ccuje5VsYH0759ar67YGiHSHJVuANwEU88YM8E7gV+JWq+tww\nyY40I2eAM5j/nADfDvwJ851z7t7PZTKeyfy/l9DOv6F1fz+bKXE4fOjkJRx9YnOefjsfluQ7AKrq\nS0NnWYk5+9VCzhYygjk7bbulEm9Fkn8AfGdV/eWS5d9XVZ8YKNZRkmwGHq2qLyc5B/h+4JNVtW/g\naCtKcnVV/drQOVaS5B8BPwB8pqr2Dp0HIMkW4ItV9ViSAK8GngN8Briuqv5uyHyHJHkp452zvx06\ny2qSvBB4sKruTvLDwAuAPVX1/nXLcDKUeJJPVtWzh84BkORlwJuALwKnA6+uqt2T1/6iqp4zZL5D\nkrwO+PfANxjnfT3wZ8APA/+tqt45YLzDkrx56SLgVTwxp+tr1z3UDEneW1WXTr7ewfg9HTF+P6+e\nh8N9ST4FbKuqR5O8ATgHeC/jwwFU1b8cMt8hSf6G8S2tPwi8m3GhPz5sqqMleRPjOYg3AjcDFzPO\nfCFwR1X98rrkaKXEV7h3SoC3VtV3rmee5SS5E7ikqh5Iso1x2fxqVd2Y5I6q+oGBIwJP/IMGvhX4\nPHBOVX1hcsjqj+fol829wIcYnws5dAL7jcAvAVTV2weKdoTpn22SDwOvrKrPJTmL8ft5wbAJIcln\nqur8ydcfB55XVd+cPL9rHjLC+L1k/IvlpxhPQvO9wI3Au6vqQ0Nmm5bk04yzfSuTeYUnvyBPZ1zi\n37seOVr6sM97gHcx+wqVb1nnLCs5raoeAKiq25P8GPD7SZ7G7OxD+UZVPQo8muSzVfUFgKr6yuRP\n7XlxPvDrjD/k9UtVdX+Sq+alvKdM/2yfdOikVlU9lOSbA2Va6t4kF1XVnwB/DTwN2H/oeO4cqcl5\nruuA65IsAC8DfiPJ5qp62rDxnlBVNfXzPfT/wLr+vFsq8U8Ab6yqTy19IcmLBsiznK8lOefQ8fDJ\nHvki4z9bnzVosiNVktMnnyr7p4cWJvkW5ujS06r6GvD6JD8IvCvJ+5mjfFMuSPL/GP+18PeS/MPJ\nz/5JwGkDZzvkNcA7kuwCvgrcOfnL8UzgF4cMtsQROxGTHYw3A2/OeJrIefFHSf4MeBJwDfCHSQ4d\nTvnD9QrR0uGUHwX2V9XnZ7z23Kr62ACxjpLkAuDrVfXZJctPZ3wznHcNk+xIk5Nc9y89mZVkE3Be\nVf3RMMmWN/kL4d8CL6iqnx46TxdJzmT8fn5k6CyHJDkPOJfxTtx9wO5Dh1XmQZLFqhoNnaOLJBcy\nPlm8Z9JRLwD2VlWX29T2k6GVEpckHW0e/yyVJHVkiUtSwyxxSWpY8yWeZEeS5w+dYzVJ3p7kt5Ks\ny7Wjx8qc/WohZwsZwZzLbq/1E5tJrgaeDWysqkuGzrOcJM9jfMOubVW1c+g8yzFnv1rI2UJGMOey\n22u9xCXpVNbSh32cnq1H5uxXCzlbyAjmXHOOVvbE4/RsvTJnv1rI2UJGMOeaczRU4k7P1iNz9quF\nnC1kBHOuVUtXpzg9W7/M2a8WcraQEcy5Ji3tiTs9W48azjl3057Bsu/nXE0j1/B76TRyK+VopcTh\n8KETp2frmTn71ULOFjKCOTttu5UST5JaJWyXMUNK8uKqWrdbVK4mTiN3QmXOp5HLHE4hB4fvsOk0\ncl1zzHHnHSHJh4DfB25a+o83ybmML/P58aq6cIh8XST5fFVtGToH4DRyPUsD08ilgSnkAKeRW6OW\nrhN/MfBK4C2Tj7MeugH/U4BPMZ7158XDxRtLstx9hAPM0wwqvwb8YD0xjdw7k/xqVd3IfJ0o/leM\nZ/eZOY0cMBclzngnYuk0cpcBHx8s0dGmJ1TYCVxUU1PIAb89SKqjbajxrFMAL+KJaeR+J8ldA+Za\nai9PTCP3H4C3JVn3aeSaKfGq+gbwNsZv1AbgrMlLD83TDe2BHwV+GnhkyfIwntNyXjiNXL9amEau\nhSnkwGnk1qSZEp82Ke0vDp1jGbcxPn571G/iybXu88Jp5HpUbUwj18IUcuA0cmsL0coxcfUr42nk\nHq2qe5Ysdxq54zT5C6GZaeQyh1PIgdPIdc5hiferlatozNmvFnK2kLFrBnM+Yd7+3DsZjJL88uSK\nmSMkOTfJTsZXBAzNnP1qIWcLGcGca+KeeM8mxxdfCbyC8bHlr3H0VTTvnpyoHYw5+9VCzhYywlE5\nl7sSbd5yDvZ+WuIn0JxfRXOYOfvVQs4WMoI5O23bEpekdnlMXJIaZolLUsMscUlqmCUuSQ2zxCWp\nYZa4ThlJbkyyO8knk7xmsuznk9yd5LYk1x66pWySs5L8XpKPTh7/eNj00mxeYqhTRpIzq+rhyc2z\ndjOeJer/Mp5k4hHG02rdWVWvTfIu4C1V9eHJnR1vrqrzBwsvLaPJuxhKx+j1SS6dfL2Z8aQNo6r6\nKkCS3wW+e/L6i4Dzpm53+5QkT566z7U0FyxxnRKSXMj4Bv7Pr6q/TXIrsAc4b7n/ZDL24HpllI6F\nx8R1qjgD+MqkwJ8J/BDje1y8MMkZSTYCPzk1/hbgdYeeTG7dK80dS1ynij8ATk/yaeBq4COM71F9\nNXA743k7P8d4EgIYF/hzk9yV8ZyPV6x/ZGl1ntjUKS3Jt1XV15OcBtwIXF9VNw2dS+rKPXGd6nYl\nuQP4JPBXFrha4564JDXMPXFJapglLkkNs8QlqWGWuCQ1zBKXpIZZ4pLUsP8P9uROv4hkkg0AAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1115b90b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "group_by_age = pd.cut(titanic_df[\"age\"], np.arange(0, 90, 10))\n",
    "age_grouping = titanic_df.groupby(group_by_age).mean()\n",
    "age_grouping['survived'].plot.bar()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.4.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 7,
	"metadata": {
	"collapsed": false,
	"scrolled": true
	},
	"outputs": [
	{
	"data": {
	"text/plain": [
	"<matplotlib.axes._subplots.AxesSubplot at 0x1115a58d0>"
	]
	},
	"execution_count": 7,
	"metadata": {},
	"output_type": "execute_result"
	},
	{
	"data": {
	"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAEtCAYAAAD+y1AoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
	"text/plain": [
	"<matplotlib.figure.Figure at 0x1115b90b8>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"group_by_age = pd.cut(titanic_df[\"age\"], np.arange(0, 90, 10))\n",
	"age_grouping = titanic_df.groupby(group_by_age).mean()\n",
	"age_grouping['survived'].plot.bar()"
	]
	}
	],
	"metadata": {
	"kernelspec": {
	"display_name": "Python 3",
	"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": "3.4.2"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 0
	}