Day 11.ipynb

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   "source": [
    "## Second Highest Salary Leetcode Task11"
   ]
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  {
   "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": 4,
   "id": "42bc36b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [[1, 100], [2, 200], [3, 300]]\n",
    "Employee = pd.DataFrame(data, columns=['id', 'salary']).astype({'id':'int64', 'salary':'int64'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   id  salary\n",
       "0   1     100\n",
       "1   2     200\n",
       "2   3     300"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Employee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d8fd6896",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    300\n",
       "1    200\n",
       "0    100\n",
       "Name: salary, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distinct_salaries = Employee['salary'].drop_duplicates()\n",
    "distinct_salaries_sorted = distinct_salaries.sort_values(ascending=False)\n",
    "distinct_salaries_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ae18b743",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "second_highest_salary = distinct_salaries_sorted.iloc[1] if 2 <= len(distinct_salaries) else None\n",
    "second_highest_salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "72b23e09",
   "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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SecondHighestSalary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   SecondHighestSalary\n",
       "0                  200"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output = pd.DataFrame([[second_highest_salary]], columns=['SecondHighestSalary'])\n",
    "output"
   ]
  }
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