redoules.github.io/content/python/.ipynb_checkpoints/Iterating_over_a_dataframe-checkpoint.ipynb

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   "source": [
    "Title: Iterating over a DataFrame\n",
    "Slug: Iterating_over_a_dataframe\n",
    "Summary: Iterating over a Pandas DataFrame with a generator\n",
    "Date: 2017-10-14 20:33  \n",
    "Category: Python  \n",
    "Tags: Data Wrangling  \n",
    "Authors: Guillaume Redoulès"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a sample dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import modules\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fruit</th>\n",
       "      <th>color</th>\n",
       "      <th>kcal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Banana</td>\n",
       "      <td>yellow</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Orange</td>\n",
       "      <td>orange</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Apple</td>\n",
       "      <td>red</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>lemon</td>\n",
       "      <td>yellow</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>lime</td>\n",
       "      <td>green</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>plum</td>\n",
       "      <td>purple</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "    fruit   color  kcal\n",
       "0  Banana  yellow    89\n",
       "1  Orange  orange    47\n",
       "2   Apple     red    52\n",
       "3   lemon  yellow    15\n",
       "4    lime   green    30\n",
       "5    plum  purple    28"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example dataframe\n",
    "\n",
    "raw_data  = {'fruit': ['Banana', 'Orange', 'Apple', 'lemon', \"lime\", \"plum\"], \n",
    "        'color': ['yellow', 'orange', 'red', 'yellow', \"green\", \"purple\"], \n",
    "        'kcal': [89, 47, 52, 15, 30, 28]\n",
    "    }\n",
    "\n",
    "df = pd.DataFrame(raw_data, columns = ['fruit', 'color', 'kcal'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using the iterrows method\n",
    "\n",
    "Pandas DataFrames can return a generator with the iterrrows method. It can then be used to loop over the rows of the DataFrame\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "At line 0 there is a Banana which is yellow and contains 89 kcal\n",
      "At line 1 there is a Orange which is orange and contains 47 kcal\n",
      "At line 2 there is a Apple which is red and contains 52 kcal\n",
      "At line 3 there is a lemon which is yellow and contains 15 kcal\n",
      "At line 4 there is a lime which is green and contains 30 kcal\n",
      "At line 5 there is a plum which is purple and contains 28 kcal\n"
     ]
    }
   ],
   "source": [
    "for index, row in df.iterrows():\n",
    "    print(\"At line {0} there is a {1} which is {2} and contains {3} kcal\".format(index, row[\"fruit\"], row[\"color\"], row[\"kcal\"]))"
   ]
  }
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