Class 1.ipynb

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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Orange</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mango</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kiwi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pineapple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Papaya</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "           0\n",
       "0      Apple\n",
       "1     Orange\n",
       "2      Mango\n",
       "3       Kiwi\n",
       "4  Pineapple\n",
       "5     Papaya"
      ]
     },
     "execution_count": 1,
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    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "lst = ['Apple', 'Orange', 'Mango', 'Kiwi', 'Pineapple', 'Papaya']\n",
    "\n",
    "df = pd.DataFrame(lst)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d16b6893",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reg. No</th>\n",
       "      <th>Name</th>\n",
       "      <th>Mark 1</th>\n",
       "      <th>Mark 2</th>\n",
       "      <th>Mark 3</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19BCE0001</td>\n",
       "      <td>Alex</td>\n",
       "      <td>30</td>\n",
       "      <td>50</td>\n",
       "      <td>70</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19BCE0002</td>\n",
       "      <td>Bob</td>\n",
       "      <td>50</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19BCE0003</td>\n",
       "      <td>Cynthia</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>50</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "     Reg. No     Name  Mark 1  Mark 2  Mark 3  total\n",
       "0  19BCE0001     Alex      30      50      70    150\n",
       "1  19BCE0002      Bob      50      70      30    150\n",
       "2  19BCE0003  Cynthia      70      30      50    150"
      ]
     },
     "execution_count": 2,
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   ],
   "source": [
    "reg_no = ['19BCE0001', '19BCE0002', '19BCE0003']\n",
    "name = ['Alex', 'Bob', 'Cynthia']\n",
    "m1 = [30, 50, 70]\n",
    "m2 = [50, 70, 30]\n",
    "m3 = [70, 30, 50]\n",
    "\n",
    "data = {\n",
    "    \"Reg. No\": reg_no,\n",
    "    \"Name\": name,\n",
    "    \"Mark 1\": m1,\n",
    "    \"Mark 2\": m2,\n",
    "    \"Mark 3\": m3\n",
    "}\n",
    "\n",
    "d = pd.DataFrame(data)\n",
    "d['total'] = d['Mark 1'] + d['Mark 2'] + d['Mark 3']\n",
    "d.to_csv('data.csv')\n",
    "\n",
    "d"
   ]
  }
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