{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading in sample data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dt</th>\n",
       "      <th>10</th>\n",
       "      <th>index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2006-01-03</td>\n",
       "      <td>73.29</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2006-01-04</td>\n",
       "      <td>74.69</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2006-01-05</td>\n",
       "      <td>72.86</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2006-01-06</td>\n",
       "      <td>69.12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2006-01-09</td>\n",
       "      <td>64.90</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          dt     10  index\n",
       "0 2006-01-03  73.29      0\n",
       "1 2006-01-04  74.69      1\n",
       "2 2006-01-05  72.86      2\n",
       "3 2006-01-06  69.12      3\n",
       "4 2006-01-09  64.90      4"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import featuretools as ft\n",
    "\n",
    "df = pd.read_csv('feature_tools_example.csv',parse_dates=['dt'])\n",
    "df['index'] = df.index\n",
    "df.columns = ['dt',10,'index'] # Calling 10 an int dtype to create error\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating EntitySet running section will generate stack trace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'int' object has no attribute 'lower'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-cb45b2a7dd95>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      3\u001b[0m                             \u001b[0mentity_id\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'test'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m                             \u001b[1;33m,\u001b[0m \u001b[0mdataframe\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m                             , index='index')\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[0mes\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\python36\\lib\\site-packages\\featuretools\\entityset\\entityset.py\u001b[0m in \u001b[0;36mentity_from_dataframe\u001b[1;34m(self, entity_id, dataframe, index, variable_types, make_index, time_index, secondary_time_index, encoding, already_sorted)\u001b[0m\n\u001b[0;32m    736\u001b[0m                                            \u001b[0mvariable_types\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvariable_types\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    737\u001b[0m                                            \u001b[0mencoding\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mencoding\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 738\u001b[1;33m                                            already_sorted=already_sorted)\n\u001b[0m\u001b[0;32m    739\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    740\u001b[0m     def normalize_entity(self, base_entity_id, new_entity_id, index,\n",
      "\u001b[1;32mc:\\python36\\lib\\site-packages\\featuretools\\entityset\\entityset.py\u001b[0m in \u001b[0;36m_import_from_dataframe\u001b[1;34m(self, entity_id, dataframe, index, variable_types, make_index, time_index, secondary_time_index, last_time_index, parse_date_cols, encoding, already_sorted)\u001b[0m\n\u001b[0;32m   1227\u001b[0m                         \u001b[0mrelationships\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcurrent_relationships\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1228\u001b[0m                         \u001b[0malready_sorted\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0malready_sorted\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1229\u001b[1;33m                         created_index=created_index)\n\u001b[0m\u001b[0;32m   1230\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mentity_dict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mentity\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mid\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mentity\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1231\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreset_metadata\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\python36\\lib\\site-packages\\featuretools\\entityset\\entity.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, id, df, entityset, variable_types, index, time_index, secondary_time_index, last_time_index, encoding, relationships, already_sorted, created_index, verbose)\u001b[0m\n\u001b[0;32m     92\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     93\u001b[0m         inferred_variable_types = self.infer_variable_types(ignore=list(variable_types.keys()),\n\u001b[1;32m---> 94\u001b[1;33m                                                             link_vars=link_vars)\n\u001b[0m\u001b[0;32m     95\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mvar_id\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdesired_type\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mvariable_types\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     96\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdesired_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\python36\\lib\\site-packages\\featuretools\\entityset\\entity.py\u001b[0m in \u001b[0;36minfer_variable_types\u001b[1;34m(self, ignore, link_vars)\u001b[0m\n\u001b[0;32m    404\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mvariable\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mignore\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    405\u001b[0m                 \u001b[1;32mcontinue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 406\u001b[1;33m             \u001b[1;32melif\u001b[0m \u001b[0mvariable\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlower\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'id'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    407\u001b[0m                 \u001b[0minferred_type\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvtypes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIndex\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'int' object has no attribute 'lower'"
     ]
    }
   ],
   "source": [
    "es = ft.EntitySet(id='Example')\n",
    "es = es.entity_from_dataframe(\n",
    "                            entity_id='test'\n",
    "                            , dataframe=df\n",
    "                            , index='index')\n",
    "es"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setting 10 as str to fix error and allow EntitySet to be created"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Entityset: Example\n",
       "  Entities:\n",
       "    test [Rows: 3168, Columns: 3]\n",
       "  Relationships:\n",
       "    No relationships"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = ['dt','10','index']\n",
    "es2 = ft.EntitySet(id='Example')\n",
    "es2 = es2.entity_from_dataframe(\n",
    "                            entity_id='test'\n",
    "                            , dataframe=df\n",
    "                            , index='index')\n",
    "es2"
   ]
  }
 ],
 "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}