ML_Fall24_EDA _Duong.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ML_Fall24 Review Exercise 2 Due at Mid-night 9/24/24 11:59 pm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### This Review Exercise will cover the following skills set\n",
    "* Using sql \n",
    "* Checking for null values and outliers\n",
    "* Calculate simple statistics using both SQL and Pandas \n",
    "* Calculate skew and correlation\n",
    "* Basic Data Visualization\n",
    "* How to fix missing values\n",
    "* Build simple linear regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)\n",
    "warnings.filterwarnings(\"ignore\", category=FutureWarning)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Make sure you have pandasql installed. If not, make sure you run the code in the following cell**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "try:\n",
    "    import pandasql as ps\n",
    "except:\n",
    "    print(\"Failed in import pandasql\")\n",
    "    os.system(\"pip install pandasql\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Import all standard libaries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pandasql as ps\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading Salary dataset ##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(403, 6)\n"
     ]
    },
    {
     "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>Rank</th>\n",
       "      <th>Discipline</th>\n",
       "      <th>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>139750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>173200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AsstProf</td>\n",
       "      <td>B</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>79750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>45.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>115000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>40.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>141500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Rank Discipline  YrsSincePhd  YrsOfService   Sex  Salary\n",
       "0      Prof          B         19.0          18.0  Male  139750\n",
       "1      Prof          B         20.0          16.0  Male  173200\n",
       "2  AsstProf          B          4.0           3.0  Male   79750\n",
       "3      Prof          B         45.0          39.0  Male  115000\n",
       "4      Prof          B         40.0          41.0  Male  141500"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary = pd.read_csv(\"data/Salaries2.csv\")\n",
    "print(salary.shape)\n",
    "salary\n",
    "salary.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>402.000000</td>\n",
       "      <td>402.000000</td>\n",
       "      <td>4.030000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>22.258706</td>\n",
       "      <td>17.684080</td>\n",
       "      <td>1.160301e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12.870455</td>\n",
       "      <td>13.571541</td>\n",
       "      <td>5.398971e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.780000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>9.116350e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>21.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>1.073090e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>1.343675e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>56.000000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>1.012100e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       YrsSincePhd  YrsOfService        Salary\n",
       "count   402.000000    402.000000  4.030000e+02\n",
       "mean     22.258706     17.684080  1.160301e+05\n",
       "std      12.870455     13.571541  5.398971e+04\n",
       "min       1.000000      0.000000  5.780000e+04\n",
       "25%      12.000000      7.000000  9.116350e+04\n",
       "50%      21.000000     16.000000  1.073090e+05\n",
       "75%      32.000000     26.000000  1.343675e+05\n",
       "max      56.000000    101.000000  1.012100e+06"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(403, 6)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 1. Check if there are any null or NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank            False\n",
       "Discipline      False\n",
       "YrsSincePhd      True\n",
       "YrsOfService     True\n",
       "Sex              True\n",
       "Salary          False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary.isnull().any() # Before Removing Rows that are null or NA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 2. Remove any rows that has null or NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank            False\n",
       "Discipline      False\n",
       "YrsSincePhd     False\n",
       "YrsOfService    False\n",
       "Sex             False\n",
       "Salary          False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary2 = salary[ ~np.isnan(salary.YrsSincePhd)] # Remove YrsSincePhd NA\n",
    "salary2 = salary2[ ~np.isnan(salary2.YrsOfService)] # Remove YrsOfService NA\n",
    "salary2 = salary2[ ~pd.isnull(salary2.Sex)] # Remove Sex Null\n",
    "salary2.isnull().any() # After Removing Rows that are null or NA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 3. Check if there is any outliers in all numerical fields using both scatter and boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YrsOfService', ylabel='YrsSincePhd'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='YrsOfService', y='YrsSincePhd', data=salary2) # Outlier in YrsOfService"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YrsOfService', ylabel='Salary'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='YrsOfService', y='Salary', data=salary2) # Outlier in Salary & YrsOfService"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YrsSincePhd', ylabel='Salary'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='YrsSincePhd', y='Salary', data=salary2) # Outlier in Salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='YrsSincePhd'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='YrsSincePhd', data=salary2) # No Outlier in YrsSincePhd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='YrsOfService'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0dOhQC1MCaE8Bz+xcc801euWVV/TZZ58pMzNT9957r7788ktt3rxZ1157bVDDjRo1Snv37vUb+/TTT9W/f39Jx6ajnU6nSkpKfOcbGxtVWlqq1NTUoGYB0DFERkYqMzNT27ZtU05OjiorK3XkyBFVVlYqJydH27Zt05133sniZOAMctr77LSH7du3KzU1Vfn5+ZoyZYrKy8s1bdo0LV26VBkZGZKkBQsWqLCwUMuWLVNycrIKCgq0ZcsW7d27V9HR0a36OdyNBZjnZPvsxMXF6c4772SfHcAQId9UsL3861//UnZ2tv7zn/8oMTFRM2fO1LRp03znWzYVfOaZZ/w2FUxJSWn1z6DsAGZqbGzUq6++qpqaGsXHx2vChAknvcECQMcU1LITGxurTz/9VGeffbZ69uz5k4t/O+IdDpQdwDzsoAyYr7Xv361aoLxo0SLfR0KLFi36ybIDAFZr2UH5oosu0oMPPqjExERVVVVp9erVys3NVX5+PoUHOIOE/cdY7YGZHcAc7KAMnDlCtoPyuHHj9Nxzz8ntdrcpIACEAjsoA/ixgMvOkCFDlJOTI6fTqUmTJumVV15RY2NjKLIBQMDYQRnAjwVcdv7617/qq6++0quvvqro6Gjdcsstcjqduv3221VaWhqKjADQauygDODHAi470rGp4LS0NC1fvlxff/21nnnmGZWXl/t2VAYAqxy/g3Jzc7PfOXZQBs5Mp1V2WrhcLj399NNasGCBKioqNGLEiGDlAoDTwg7KAH4s4LuxPB6P1q9frzVr1mjLli1KSkpSenq6MjIy9POf/zxUOUOKu7EA87CDMmC+kO2gHBUVpZ49e2rKlCnKyMjQBRdc0OawVqPsAGZqampSRUWFDh06pNjYWA0dOpQZHcAgQd1UsIXX69Xjjz+um266Sd26dWtzSAAIpcjISA0bNszqGAAsFtCaHa/Xq7vuuktfffVVqPIAAAAEVUBlJyIiQsnJyTp48GCo8gAAAARVwHdjFRUV6b777tPu3btDkQcAACCoAl6g3LNnTx05ckQ//PCDunTpoqioKL/zHXFXUhYoAwDQ8YRkgbIkLV68uC25AAAA2lXAZeeWW24JRQ7AKN9995327dtndQwgLPXr109du3a1OgbOIAGXHUn6/PPPtWzZMn3++ed6/PHH1adPH73++utKSEjQ4MGDg50R6HD27dun22+/3eoYQFhaunSpBgwYYHUMnEECXrNTWlqqK664QqNGjVJZWZk++eQTJSUlqaioSOXl5XrxxRdDlTVkWLODYGNmJ3xUV1dr/vz5mjt3rvr37291HIiZHQRPyNbszJkzR/PmzdPMmTMVHR3tGx83bpwef/zx00sLGKZr16785hpm+vfvz78T4AwV8K3nH3/8sa677roTxnv37s3+OwAAIOwEXHZ69OihAwcOnDC+a9cunXPOOUEJBQAAECwBl5309HTNnj1bLpdLNptNzc3NevfddzVr1izdfPPNocgIAABw2gIuO/Pnz1e/fv10zjnn6PDhwzrvvPM0evRopaamKicnJxQZAQAATlvAC5Q7d+6s1atX6+GHH9bOnTvV3NysYcOGKTk5ORT5AAAA2uS09tmRpKSkJCUlJemHH37Qd999F8xMAAAAQdPqj7E2btyolStX+o3Nnz9fP/vZz9SjRw+lpaWprq4u6AEBAADaotVl59FHH5XH4/Edb926VX/5y1/04IMP6oUXXtD+/fv18MMPhyQkAADA6Wp12dm9e7dSU1N9xy+++KLGjx+vuXPnauLEiXrsscf0z3/+MyQhAQAATlery059fb169erlO37nnXd0ySWX+I4HDx6smpqa4KYDAABoo1aXnfj4eH3yySeSpMOHD+ujjz7SqFGjfOcPHjyobt26BT8hAABAG7S67EyePFlZWVlauXKlpk2bJqfTqV//+te+8x988IF+8YtfhCQkAADA6Wr1ree5ubmqqanRPffcI6fTqVWrVikyMtJ3fu3atbr66qtDEhIAAOB0tarsbNiwQVdcccUJt54f76233gpaKAAAgGBp1cdY1113nf773/9KkiIjI1VbWxvKTAAAAEHTqrLTu3dvvffee5Ikr9crm80W0lAAAADB0qqPse644w5NmDBBNptNNptNTqfzlNc2NTUFLRwAAEBbtars5OXl6cYbb9Rnn32ma665RsuWLVOPHj1CHA0AAKDtWn031sCBAzVw4EDl5ubq+uuvZ08dAADQIQT8ree5ubmqqKjQp59+KpvNpuTkZA0dOjQU2QAAANosoLJTXl6u2267TXv27JHX65Uk2Ww2DR48WM8995wuuOCCkIQEAAA4Xa3eQXnPnj269NJLFRUVpVWrVmnnzp3asWOHVq5cKbvdrksvvVR79uwJZVYAAICABbSD8vjx47V+/Xq/W8+HDRumqVOnauLEicrLy9MLL7wQkqAAAACno9VlZ8uWLXrttddOuseOzWbTAw88oCuvvDKo4QAAANqq1R9j1dfXy+FwnPK80+lUfX19UEIBAAAES6vLzrnnnqvy8vJTnn///ffVv3//oIQCAAAIllaXnRtuuEEzZ87U7t27Tzj38ccfa9asWbrxxhuDGg4AAKCtWr1mJzs7W5s3b9Yvf/lLjR8/XoMGDZJ07C6tzZs368ILL1R2dnbIggIAAJyOVpedrl276q233tKiRYu0du1alZaWSpIGDBigefPm6c9//rPsdnvIggIAAJyOgDYV7NKli2bPnq3Zs2eHKg8AAEBQtXrNTov9+/fryy+/9B2Xl5crKytLS5cuDWowAACAYAi47KSnp+utt96SJLlcLl122WUqLy/XAw88oIceeijoAQEAANoi4LKze/duXXjhhZKkF154QUOGDNHWrVu1Zs0aLV++PNj5AAAA2iTgsvP999/7FiJv3rxZ11xzjSRp4MCBOnDgQHDTAQAAtFHAZWfw4MF6+umn9fbbb6ukpESXX365JKmmpka9evUKekAAAIC2CLjsLFiwQM8884zGjh2rqVOn6vzzz5ckbdiwwffxFgAAQLgIqOx4vV4lJiaqurpa33zzjf72t7/5zt1+++16+umngx7weIWFhbLZbMrKyvLLlJeXp/j4eEVFRWns2LGqrKwMaQ4AANBxBFx2kpOT9fXXX6tnz55+584991z16dMnqOGOt337di1dulRDhw71Gy8qKtLChQtVXFys7du3y+l0avz48XwpKQAAkBRg2YmIiFBycrIOHjwYqjwndfjwYWVkZOjZZ5/1K1ler1eLFy/W3LlzNXHiRKWkpGjFihU6cuSI1qxZ064ZAQBAeAp4zU5RUZHuu+++k34haKjMmDFDV111lS677DK/8aqqKrlcLqWlpfnG7Ha7xowZo61bt57y9RoaGuTxePweAADATAF9XYQk3XTTTTpy5IjOP/98denSRVFRUX7nDx06FLRwkrRu3Trt3LlT27dvP+Gcy+WSJDkcDr9xh8Oh6urqU75mYWGh8vPzg5oTAACEp1aXnS+//FJ9+/bVokWLZLPZQpnJZ//+/frTn/6kTZs2qWvXrqe87sd5vF7vT2bMzs7WzJkzfccej0cJCQltDwwAAMJOq8tOSkqKnnjiCd16660hjONvx44dqq2t1fDhw31jTU1NKisrU3Fxsfbu3Svp2AxPXFyc75ra2toTZnuOZ7fb+YZ2AADOEK1es1NQUKAZM2Zo0qRJ7bZA+dJLL9XHH3+sDz/80PcYMWKEMjIy9OGHHyopKUlOp1MlJSW+5zQ2Nqq0tFSpqantkhEAAIS3VpedzMxMffTRR6qrq9PgwYO1YcOGUOaSJEVHRyslJcXvcdZZZ6lXr15KSUnx7blTUFCgl19+Wbt379att96qbt26KT09PeT5AABA+AtogXJiYqLefPNNFRcXa9KkSRo0aJA6dfJ/iZ07dwY14P9y//336+jRo8rMzFRdXZ1GjhypTZs2KTo6ul1zAACA8BTw3VjV1dVav369YmNjNWHChBPKTqht2bLF79hmsykvL095eXntmgMAAHQMATWVZ599Vvfee68uu+wy7d69W7179w5VLgAAgKBoddm5/PLLVV5eruLiYt18882hzAQAABA0rS47TU1NqqioUN++fUOZBwAAIKhaXXaOv70bAACgowj4u7EAAAA6EsoOAAAwGmUHAAAYjbIDAACMRtkBAABGo+wAAACjUXYAAIDRKDsAAMBolB0AAGA0yg4AADAaZQcAABiNsgMAAIxG2QEAAEaj7AAAAKNRdgAAgNEoOwAAwGiUHQAAYDTKDgAAMBplBwAAGI2yAwAAjEbZAQAARqPsAAAAo1F2AACA0Sg7AADAaJQdAABgNMoOAAAwGmUHAAAYjbIDAACMRtkBAABGo+wAAACjUXYAAIDRKDsAAMBolB0AAGC0TlYHQHB9/fXXcrvdVscAwkZ1dbXfnwCOiYmJkcPhsDpGu7B5vV6v1SGs5vF4FBMTI7fbre7du1sd57R9/fXXuun3N+v7xgarowAAwlznLnatWvn3Dl14Wvv+zcyOQdxut75vbNDRpDFq7hpjdRwAQJiK+M4tfVEqt9vdoctOa1F2DNTcNUbNZ51tdQwAAMICC5QBAIDRKDsAAMBolB0AAGA0yg4AADAaZQcAABiNsgMAAIxG2QEAAEaj7AAAAKNRdgAAgNEoOwAAwGiUHQAAYDTKDgAAMBplBwAAGI2yAwAAjEbZAQAARgvrslNYWKgLLrhA0dHR6tOnj6699lrt3bvX7xqv16u8vDzFx8crKipKY8eOVWVlpUWJAQBAuAnrslNaWqoZM2bovffeU0lJiX744QelpaXp22+/9V1TVFSkhQsXqri4WNu3b5fT6dT48eNVX19vYXIAABAuOlkd4Ke8/vrrfsfLli1Tnz59tGPHDo0ePVper1eLFy/W3LlzNXHiREnSihUr5HA4tGbNGk2fPt2K2AAAIIyE9czOj7ndbklSbGysJKmqqkoul0tpaWm+a+x2u8aMGaOtW7ee8nUaGhrk8Xj8HgAAwEwdpux4vV7NnDlTF198sVJSUiRJLpdLkuRwOPyudTgcvnMnU1hYqJiYGN8jISEhdMEBAIClOkzZueuuu1RRUaG1a9eecM5ms/kde73eE8aOl52dLbfb7Xvs378/6HkBAEB4COs1Oy3uvvtubdiwQWVlZerbt69v3Ol0Sjo2wxMXF+cbr62tPWG253h2u112uz10gQEAQNgI65kdr9eru+66Sy+99JLefPNNJSYm+p1PTEyU0+lUSUmJb6yxsVGlpaVKTU1t77gAACAMhfXMzowZM7RmzRq9+uqrio6O9q3DiYmJUVRUlGw2m7KyslRQUKDk5GQlJyeroKBA3bp1U3p6usXpAQBAOAjrsvPUU09JksaOHes3vmzZMt16662SpPvvv19Hjx5VZmam6urqNHLkSG3atEnR0dHtnBYAAISjsC47Xq/3f15js9mUl5envLy80AcCAAAdTliv2QEAAGgryg4AADAaZQcAABiNsgMAAIxG2QEAAEYL67uxcHoijv7X6ggAgDB2pr1PUHYMFFVVZnUEAADCBmXHQEcTR6s5qofVMQAAYSri6H/PqF+MKTsGao7qoeazzrY6BgAAYYEFygAAwGiUHQAAYDTKDgAAMBplBwAAGI2yAwAAjEbZAQAARqPsAAAAo1F2AACA0Sg7AADAaJQdAABgNMoOAAAwGmUHAAAYjbIDAACMRtkBAABGo+wAAACjUXYAAIDRKDsAAMBolB0AAGA0yg4AADAaZQcAABiNsgMAAIxG2QEAAEaj7AAAAKNRdgAAgNEoOwAAwGiUHQAAYLROVgdA8EV857Y6AgAgjJ1p7xOUHYPExMSocxe79EWp1VEAAGGucxe7YmJirI7RLig7BnE4HFq18u9yu8+sxg78lOrqas2fP19z585V//79rY4DhI2YmBg5HA6rY7QLyo5hHA7HGfMfLxCI/v37a8CAAVbHAGABFigDAACjUXYAAIDRKDsAAMBolB0AAGA0yg4AADAaZQcAABiNsgMAAIxG2QEAAEaj7AAAAKNRdgAAgNEoOwAAwGiUHQAAYDTKDgAAMBplBwAAGI2yAwAAjEbZAQAARjOm7Dz55JNKTExU165dNXz4cL399ttWRwIAAGHAiLLz/PPPKysrS3PnztWuXbv0m9/8RldccYX27dtndTQAAGAxI8rOwoULddttt+mPf/yjBg0apMWLFyshIUFPPfWU1dEAAIDFOlkdoK0aGxu1Y8cOzZkzx288LS1NW7duPelzGhoa1NDQ4Dv2eDwhzYgzz3fffcfMYpiorq72+xPW69evn7p27Wp1DJxBOnzZ+eabb9TU1CSHw+E37nA45HK5TvqcwsJC5efnt0c8nKH27dun22+/3eoYOM78+fOtjoD/b+nSpRowYIDVMXAG6fBlp4XNZvM79nq9J4y1yM7O1syZM33HHo9HCQkJIc2HM0u/fv20dOlSq2MAYalfv35WR8AZpsOXnbPPPluRkZEnzOLU1taeMNvTwm63y263t0c8nKG6du3Kb64AECY6/ALlLl26aPjw4SopKfEbLykpUWpqqkWpAABAuOjwMzuSNHPmTP3+97/XiBEjdNFFF2np0qXat2+f7rjjDqujAQAAixlRdm644QYdPHhQDz30kA4cOKCUlBRt3LhR/fv3tzoaAACwmM3r9XqtDmE1j8ejmJgYud1ude/e3eo4AACgFVr7/t3h1+wAAAD8FMoOAAAwGmUHAAAYjbIDAACMRtkBAABGo+wAAACjUXYAAIDRKDsAAMBolB0AAGA0I74uoq1aNpH2eDwWJwEAAK3V8r79v74MgrIjqb6+XpKUkJBgcRIAABCo+vp6xcTEnPI8340lqbm5WTU1NYqOjpbNZrM6DoAg8ng8SkhI0P79+/nuO8AwXq9X9fX1io+PV0TEqVfmUHYAGI0v+gXAAmUAAGA0yg4AADAaZQeA0ex2u3Jzc2W3262OAsAirNkBAABGY2YHAAAYjbIDAACMRtkBAABGo+wAAACjUXYAAIDRKDsAAMBolB0AAGA0yg4AADDa/wPz60yIUpkOqgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='YrsOfService', data=salary2) # Outlier in YrsOfService"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Salary'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='Salary', data=salary2) # Outlier in Salary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 4. Display and Remove (the real) outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='YrsOfService', data=salary2) # Before Removing YrsOfService Outlier\n",
    "salary3 = salary2[ salary2['YrsOfService'] <= 80] # Remove Past 80 Years "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='YrsOfService'>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='YrsOfService', data=salary3) # After Removing YrsOfService Outlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='Salary', data=salary2) # Before Removing Salary Outlier\n",
    "salary3 = salary3[ salary3['Salary'] <= 300000] # Remove After $300,000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Salary'>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='Salary', data=salary3) # After Removing Salary Outlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YrsOfService', ylabel='YrsSincePhd'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='YrsOfService', y='YrsSincePhd', data=salary3) # After Removing YrsOfService Outlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YrsOfService', ylabel='Salary'>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='YrsOfService', y='Salary', data=salary3) # After Removing YrsOfService & Salary Outlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YrsSincePhd', ylabel='Salary'>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='YrsSincePhd', y='Salary', data=salary3) # After Removing Salary Outlier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 5. Calculate the count and average salary by Rank using SQL. Does the result make sense?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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>Rank</th>\n",
       "      <th>count(*)</th>\n",
       "      <th>avg(salary)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AssocProf</td>\n",
       "      <td>64</td>\n",
       "      <td>93876.437500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AsstProf</td>\n",
       "      <td>67</td>\n",
       "      <td>80775.985075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Prof</td>\n",
       "      <td>266</td>\n",
       "      <td>126697.360902</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Rank  count(*)    avg(salary)\n",
       "0  AssocProf        64   93876.437500\n",
       "1   AsstProf        67   80775.985075\n",
       "2       Prof       266  126697.360902"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql =\"select rank, count(*), avg(salary) from salary3 group by rank\"\n",
    "df = ps.sqldf(sql)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 6. Answer the above same question using Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           Discipline  YrsSincePhd  YrsOfService  Sex  Salary\n",
      "Rank                                                         \n",
      "AssocProf          64           64            64   64      64\n",
      "AsstProf           67           67            67   67      67\n",
      "Prof              266          266           266  266     266\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Rank\n",
       "AssocProf     93876.437500\n",
       "AsstProf      80775.985075\n",
       "Prof         126697.360902\n",
       "Name: Salary, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(salary3.groupby(['Rank']).count()) # Count of Enteries Per Column By Rank\n",
    "print()\n",
    "salary3.groupby(['Rank'])['Salary'].mean() # Average Salary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 7. Do a boxplot of Salary by Rank. Comment on the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Rank', ylabel='Salary'>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='Rank', y='Salary', data=salary3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 8. Calculate correlation among the nuermical attributes, find out which variables have the highest correlation with Salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "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>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>YrsSincePhd</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.909341</td>\n",
       "      <td>0.415792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YrsOfService</th>\n",
       "      <td>0.909341</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.330874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Salary</th>\n",
       "      <td>0.415792</td>\n",
       "      <td>0.330874</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              YrsSincePhd  YrsOfService    Salary\n",
       "YrsSincePhd      1.000000      0.909341  0.415792\n",
       "YrsOfService     0.909341      1.000000  0.330874\n",
       "Salary           0.415792      0.330874  1.000000"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary3.corr(method='pearson', min_periods=1, numeric_only=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 9. Calculate the Standard deviation, Skew and Kurtosis for the YrsSincePhd, YrsOfService, Salary by Rank. Comment on the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "series = salary3.groupby(['Rank'])[['YrsSincePhd', 'YrsOfService', 'Salary']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "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>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AssocProf</th>\n",
       "      <td>9.652584</td>\n",
       "      <td>10.100180</td>\n",
       "      <td>13831.699844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AsstProf</th>\n",
       "      <td>2.541381</td>\n",
       "      <td>1.495811</td>\n",
       "      <td>8174.112637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prof</th>\n",
       "      <td>10.127369</td>\n",
       "      <td>11.570051</td>\n",
       "      <td>27675.245455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           YrsSincePhd  YrsOfService        Salary\n",
       "Rank                                              \n",
       "AssocProf     9.652584     10.100180  13831.699844\n",
       "AsstProf      2.541381      1.495811   8174.112637\n",
       "Prof         10.127369     11.570051  27675.245455"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.std() # Standard Deviation by Rank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "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>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AssocProf</th>\n",
       "      <td>2.139123</td>\n",
       "      <td>2.420949</td>\n",
       "      <td>-0.085893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AsstProf</th>\n",
       "      <td>0.524578</td>\n",
       "      <td>-0.026995</td>\n",
       "      <td>0.082975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prof</th>\n",
       "      <td>0.370452</td>\n",
       "      <td>0.464453</td>\n",
       "      <td>0.597864</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           YrsSincePhd  YrsOfService    Salary\n",
       "Rank                                          \n",
       "AssocProf     2.139123      2.420949 -0.085893\n",
       "AsstProf      0.524578     -0.026995  0.082975\n",
       "Prof          0.370452      0.464453  0.597864"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.skew() # Skew by Rank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AssocProf</th>\n",
       "      <td>4.414356</td>\n",
       "      <td>6.350832</td>\n",
       "      <td>-0.586327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AsstProf</th>\n",
       "      <td>-0.358052</td>\n",
       "      <td>-0.658746</td>\n",
       "      <td>-0.920936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prof</th>\n",
       "      <td>-0.615530</td>\n",
       "      <td>-0.199387</td>\n",
       "      <td>0.401066</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           YrsSincePhd  YrsOfService    Salary\n",
       "Rank                                          \n",
       "AssocProf     4.414356      6.350832 -0.586327\n",
       "AsstProf     -0.358052     -0.658746 -0.920936\n",
       "Prof         -0.615530     -0.199387  0.401066"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.apply(pd.DataFrame.kurt) # Kurtosis by Rank"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 10. Build a linear regression model in predicting the salary using the variable that has the highest correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Intercept: [91910.7498152]\n",
      "Model Coefficient: [[976.91675041]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "salary3.isnull().any()\n",
    "salary3.head()\n",
    "\n",
    "Xarray = salary3['YrsSincePhd'].values\n",
    "Yarray = salary3['Salary'].values\n",
    "\n",
    "X = Xarray.reshape(-1, 1)\n",
    "Y = Yarray.reshape(-1, 1)\n",
    "\n",
    "model = LinearRegression()\n",
    "model.fit(X,Y)\n",
    "\n",
    "Y_pred = model.predict(X)\n",
    "\n",
    "plt.scatter(X,Y, color='gray')\n",
    "plt.plot(X, Y_pred, color='red', linewidth=2)\n",
    "plt.show()\n",
    "\n",
    "print(\"Model Intercept: {}\".format(model.intercept_))\n",
    "print(\"Model Coefficient: {}\".format(model.coef_))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question 11: Now investigate how the categorical variables affect the salary by using a FacetGrid with scatter plot of salary against each categorical variables (rank, sex and discipline). Comment on the results (such as under which categorical variable the above linear regression model would work better)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>Rank</th>\n",
       "      <th>Discipline</th>\n",
       "      <th>YrsSincePhd</th>\n",
       "      <th>YrsOfService</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>139750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>173200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AsstProf</td>\n",
       "      <td>B</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>79750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>45.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>115000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Prof</td>\n",
       "      <td>B</td>\n",
       "      <td>40.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>141500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Rank Discipline  YrsSincePhd  YrsOfService   Sex  Salary\n",
       "0      Prof          B         19.0          18.0  Male  139750\n",
       "1      Prof          B         20.0          16.0  Male  173200\n",
       "2  AsstProf          B          4.0           3.0  Male   79750\n",
       "3      Prof          B         45.0          39.0  Male  115000\n",
       "4      Prof          B         40.0          41.0  Male  141500"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 911.111x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(salary3, col = 'Rank')\n",
    "g = (g.map(plt.scatter, 'YrsSincePhd', 'Salary').add_legend())\n",
    "\n",
    "# Professors' range of YrsSincePhd (x) and Salary (Y) are higher than Assistant & Associate Professors\n",
    "# Assistant Professors' YrsSincePhd and Salary are very alike one another (concentrated data points)\n",
    "# Associate Professors' range of Salary are higher than Assistant Professors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 611.111x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(salary3, col = 'Sex')\n",
    "g = (g.map(plt.scatter, 'YrsSincePhd', 'Salary').add_legend())\n",
    "\n",
    "# There are significantly more datapoints for Male than Female\n",
    "# Males has more range for both YrsSincePhd and Salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 611.111x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(salary3, col = 'Discipline')\n",
    "g = (g.map(plt.scatter, 'YrsSincePhd', 'Salary').add_legend())\n",
    "\n",
    "# Discipline B has more points especially between 0 - 20 YrsSincePhd (x)\n",
    "# Discipline A and B are very alike\n",
    "\n",
    "# The linear progression model would work better under the categorical variable of Discipline.\n",
    "# Because the datapoints are concentrated and Discipline A and B are alike, the linear progression model would fit better."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}