Day 12.ipynb

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   "source": [
    "## Department Highest Salary Leetcode Task12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "814f2532",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "42bc36b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [[1, 'Joe', 70000, 1], [2, 'Jim', 90000, 1], [3, 'Henry', 80000, 2], [4, 'Sam', 60000, 2], [5, 'Max', 90000, 1]]\n",
    "Employee = pd.DataFrame(data, columns=['id', 'name', 'salary', 'departmentId']).astype({'id':'Int64', 'name':'object', 'salary':'Int64', 'departmentId':'Int64'})\n",
    "data = [[1, 'IT'], [2, 'Sales']]\n",
    "Department = pd.DataFrame(data, columns=['id', 'name']).astype({'id':'Int64', 'name':'object'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6cff6308",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>departmentId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Joe</td>\n",
       "      <td>70000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jim</td>\n",
       "      <td>90000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Henry</td>\n",
       "      <td>80000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Sam</td>\n",
       "      <td>60000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Max</td>\n",
       "      <td>90000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   id   name  salary  departmentId\n",
       "0   1    Joe   70000             1\n",
       "1   2    Jim   90000             1\n",
       "2   3  Henry   80000             2\n",
       "3   4    Sam   60000             2\n",
       "4   5    Max   90000             1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Employee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f8c9383e",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   id   name\n",
       "0   1     IT\n",
       "1   2  Sales"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Department"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f88f95eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name_x</th>\n",
       "      <th>salary</th>\n",
       "      <th>name_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Joe</td>\n",
       "      <td>70000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jim</td>\n",
       "      <td>90000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Max</td>\n",
       "      <td>90000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Henry</td>\n",
       "      <td>80000</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sam</td>\n",
       "      <td>60000</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "  name_x  salary name_y\n",
       "0    Joe   70000     IT\n",
       "1    Jim   90000     IT\n",
       "2    Max   90000     IT\n",
       "3  Henry   80000  Sales\n",
       "4    Sam   60000  Sales"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = pd.merge(Employee, Department, left_on='departmentId', right_on='id', how='inner')\n",
    "result = result.drop(columns=['departmentId','id_y','id_x'])\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3d54e612",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Employee</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Department</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Joe</td>\n",
       "      <td>70000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jim</td>\n",
       "      <td>90000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Max</td>\n",
       "      <td>90000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Henry</td>\n",
       "      <td>80000</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sam</td>\n",
       "      <td>60000</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Employee  Salary Department\n",
       "0      Joe   70000         IT\n",
       "1      Jim   90000         IT\n",
       "2      Max   90000         IT\n",
       "3    Henry   80000      Sales\n",
       "4      Sam   60000      Sales"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_column_names = {'name_x': 'Employee', 'salary': 'Salary' , 'name_y':'Department'}\n",
    "result= result.rename(columns=new_column_names)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "88c5ac91",
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>Jim</td>\n",
       "      <td>90000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Max</td>\n",
       "      <td>90000</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Henry</td>\n",
       "      <td>80000</td>\n",
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      "text/plain": [
       "  Employee  Salary Department\n",
       "0      Jim   90000         IT\n",
       "1      Max   90000         IT\n",
       "2    Henry   80000      Sales"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "highest_salary_rows = result.groupby('Department', as_index=False)['Salary'].max()\n",
    "result = pd.merge(result, highest_salary_rows, on=['Department', 'Salary'])\n",
    "result"
   ]
  }
 ],
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