Bonus.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Homework BONUS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import dependencies\n",
    "from sqlalchemy import create_engine, inspect, func\n",
    "from sqlalchemy.ext.automap import automap_base\n",
    "from sqlalchemy.orm import Session\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import sqlalchemy\n",
    "import psycopg2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<connection object at 0x00000266229B69D0; dsn: 'user=postgres password=xxx dbname=employee_db host=localhost', closed: 0>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create connection to enter postgres db\n",
    "connection = psycopg2.connect('dbname=employee_db user=postgres password=5290 host=localhost')\n",
    "connection\n",
    "\n",
    "# engine = create_engine(f\"sqlite:///{database_path}\")\n",
    "# data = engine.execute(\"SELECT * FROM departments)\n",
    "# database_path = \"../EmployeeSQL/departments.csv\"\n",
    "# a = pd.read_csv(\"EmployeeSQL/departments.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Activate connection cursor\n",
    "cur = connection.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "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>dept_no</th>\n",
       "      <th>dept_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>d001</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>d002</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>d003</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d004</td>\n",
       "      <td>Production</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>d005</td>\n",
       "      <td>Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>d006</td>\n",
       "      <td>Quality Management</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>d007</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>d008</td>\n",
       "      <td>Research</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>d009</td>\n",
       "      <td>Customer Service</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dept_no           dept_name\n",
       "0    d001           Marketing\n",
       "1    d002             Finance\n",
       "2    d003     Human Resources\n",
       "3    d004          Production\n",
       "4    d005         Development\n",
       "5    d006  Quality Management\n",
       "6    d007               Sales\n",
       "7    d008            Research\n",
       "8    d009    Customer Service"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Select table, make variable and display as dataframe\n",
    "cur.execute('SELECT dept_no, dept_name FROM \"Departments\"')\n",
    "departments = cur.fetchall()\n",
    "departments_df = pd.DataFrame(departments, columns = ['dept_no','dept_name'])\n",
    "departments_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "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>dept_no</th>\n",
       "      <th>emp_no</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>d007</td>\n",
       "      <td>10002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>d004</td>\n",
       "      <td>10003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>d004</td>\n",
       "      <td>10004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d003</td>\n",
       "      <td>10005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>d005</td>\n",
       "      <td>10006</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dept_no  emp_no\n",
       "0    d007   10002\n",
       "1    d004   10003\n",
       "2    d004   10004\n",
       "3    d003   10005\n",
       "4    d005   10006"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Query the employees table\n",
    "cur.execute('SELECT dept_no, emp_no FROM \"Dept_emp\"')\n",
    "dept_emp = cur.fetchall()\n",
    "dept_emp_df = pd.DataFrame(dept_emp, columns = ['dept_no','emp_no'])\n",
    "dept_emp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>dept_no</th>\n",
       "      <th>emp_no</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>d001</td>\n",
       "      <td>110022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>d001</td>\n",
       "      <td>110039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>d002</td>\n",
       "      <td>110085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d002</td>\n",
       "      <td>110114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>d003</td>\n",
       "      <td>110183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>d003</td>\n",
       "      <td>110228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>d004</td>\n",
       "      <td>110303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>d004</td>\n",
       "      <td>110344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>d004</td>\n",
       "      <td>110386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>d004</td>\n",
       "      <td>110420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>d005</td>\n",
       "      <td>110511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>d005</td>\n",
       "      <td>110567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>d006</td>\n",
       "      <td>110725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>d006</td>\n",
       "      <td>110765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>d006</td>\n",
       "      <td>110800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>d006</td>\n",
       "      <td>110854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>d007</td>\n",
       "      <td>111035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>d007</td>\n",
       "      <td>111133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>d008</td>\n",
       "      <td>111400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>d008</td>\n",
       "      <td>111534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>d009</td>\n",
       "      <td>111692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>d009</td>\n",
       "      <td>111784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>d009</td>\n",
       "      <td>111877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>d009</td>\n",
       "      <td>111939</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   dept_no  emp_no\n",
       "0     d001  110022\n",
       "1     d001  110039\n",
       "2     d002  110085\n",
       "3     d002  110114\n",
       "4     d003  110183\n",
       "5     d003  110228\n",
       "6     d004  110303\n",
       "7     d004  110344\n",
       "8     d004  110386\n",
       "9     d004  110420\n",
       "10    d005  110511\n",
       "11    d005  110567\n",
       "12    d006  110725\n",
       "13    d006  110765\n",
       "14    d006  110800\n",
       "15    d006  110854\n",
       "16    d007  111035\n",
       "17    d007  111133\n",
       "18    d008  111400\n",
       "19    d008  111534\n",
       "20    d009  111692\n",
       "21    d009  111784\n",
       "22    d009  111877\n",
       "23    d009  111939"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Query the managers\n",
    "cur.execute('SELECT dept_no, emp_no FROM \"Dept_manager\"')\n",
    "dept_manager = cur.fetchall()\n",
    "dept_manager_df = pd.DataFrame(dept_manager, columns = ['dept_no','emp_no'])\n",
    "dept_manager_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>emp_no</th>\n",
       "      <th>title_id</th>\n",
       "      <th>birth_date</th>\n",
       "      <th>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>sex</th>\n",
       "      <th>hire_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>473302</td>\n",
       "      <td>s0001</td>\n",
       "      <td>7/25/1953</td>\n",
       "      <td>Hideyuki</td>\n",
       "      <td>Zallocco</td>\n",
       "      <td>M</td>\n",
       "      <td>4/28/1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>475053</td>\n",
       "      <td>e0002</td>\n",
       "      <td>11/18/1954</td>\n",
       "      <td>Byong</td>\n",
       "      <td>Delgrande</td>\n",
       "      <td>F</td>\n",
       "      <td>9/7/1991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>57444</td>\n",
       "      <td>e0002</td>\n",
       "      <td>1/30/1958</td>\n",
       "      <td>Berry</td>\n",
       "      <td>Babb</td>\n",
       "      <td>F</td>\n",
       "      <td>3/21/1992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>421786</td>\n",
       "      <td>s0001</td>\n",
       "      <td>9/28/1957</td>\n",
       "      <td>Xiong</td>\n",
       "      <td>Verhoeff</td>\n",
       "      <td>M</td>\n",
       "      <td>11/26/1987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>282238</td>\n",
       "      <td>e0003</td>\n",
       "      <td>10/28/1952</td>\n",
       "      <td>Abdelkader</td>\n",
       "      <td>Baumann</td>\n",
       "      <td>F</td>\n",
       "      <td>1/18/1991</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   emp_no title_id  birth_date  first_name  last_name sex   hire_date\n",
       "0  473302    s0001   7/25/1953    Hideyuki   Zallocco   M   4/28/1990\n",
       "1  475053    e0002  11/18/1954       Byong  Delgrande   F    9/7/1991\n",
       "2   57444    e0002   1/30/1958       Berry       Babb   F   3/21/1992\n",
       "3  421786    s0001   9/28/1957       Xiong   Verhoeff   M  11/26/1987\n",
       "4  282238    e0003  10/28/1952  Abdelkader    Baumann   F   1/18/1991"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Query the employee table\n",
    "cur.execute('SELECT emp_no, title_id, birth_date, first_name, last_name, sex, hire_date FROM \"Employees\"')\n",
    "employees = cur.fetchall()\n",
    "employees_df = pd.DataFrame(employees, columns = ['emp_no', 'title_id', 'birth_date', 'first_name', 'last_name', 'sex', 'hire_date'])\n",
    "employees_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>emp_no</th>\n",
       "      <th>salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001</td>\n",
       "      <td>60117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>65828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10003</td>\n",
       "      <td>40006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10004</td>\n",
       "      <td>40054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10005</td>\n",
       "      <td>78228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   emp_no  salary\n",
       "0   10001   60117\n",
       "1   10002   65828\n",
       "2   10003   40006\n",
       "3   10004   40054\n",
       "4   10005   78228"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Query the salaries table\n",
    "cur.execute('SELECT emp_no, salary FROM \"Salaries\"')\n",
    "salaries = cur.fetchall()\n",
    "salaries_df = pd.DataFrame(salaries, columns = ['emp_no', 'salary'])\n",
    "salaries_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "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>title_id</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>s0001</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>s0002</td>\n",
       "      <td>Senior Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>e0001</td>\n",
       "      <td>Assistant Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>e0002</td>\n",
       "      <td>Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e0003</td>\n",
       "      <td>Senior Engineer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>e0004</td>\n",
       "      <td>Technique Leader</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>m0001</td>\n",
       "      <td>Manager</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  title_id               title\n",
       "0    s0001               Staff\n",
       "1    s0002        Senior Staff\n",
       "2    e0001  Assistant Engineer\n",
       "3    e0002            Engineer\n",
       "4    e0003     Senior Engineer\n",
       "5    e0004    Technique Leader\n",
       "6    m0001             Manager"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Query the titles table\n",
    "cur.execute('SELECT title_id, title FROM \"Titles\"')\n",
    "titles = cur.fetchall()\n",
    "titles_df = pd.DataFrame(title, columns = ['title_id', 'title'])\n",
    "titles_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "# inspect db\n",
    "# inspector = inspect(employees_df)\n",
    "# inspector.get_table_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "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>emp_no</th>\n",
       "      <th>title_id</th>\n",
       "      <th>birth_date</th>\n",
       "      <th>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>sex</th>\n",
       "      <th>hire_date</th>\n",
       "      <th>salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>473302</td>\n",
       "      <td>s0001</td>\n",
       "      <td>7/25/1953</td>\n",
       "      <td>Hideyuki</td>\n",
       "      <td>Zallocco</td>\n",
       "      <td>M</td>\n",
       "      <td>4/28/1990</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>475053</td>\n",
       "      <td>e0002</td>\n",
       "      <td>11/18/1954</td>\n",
       "      <td>Byong</td>\n",
       "      <td>Delgrande</td>\n",
       "      <td>F</td>\n",
       "      <td>9/7/1991</td>\n",
       "      <td>53422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>57444</td>\n",
       "      <td>e0002</td>\n",
       "      <td>1/30/1958</td>\n",
       "      <td>Berry</td>\n",
       "      <td>Babb</td>\n",
       "      <td>F</td>\n",
       "      <td>3/21/1992</td>\n",
       "      <td>48973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>421786</td>\n",
       "      <td>s0001</td>\n",
       "      <td>9/28/1957</td>\n",
       "      <td>Xiong</td>\n",
       "      <td>Verhoeff</td>\n",
       "      <td>M</td>\n",
       "      <td>11/26/1987</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>282238</td>\n",
       "      <td>e0003</td>\n",
       "      <td>10/28/1952</td>\n",
       "      <td>Abdelkader</td>\n",
       "      <td>Baumann</td>\n",
       "      <td>F</td>\n",
       "      <td>1/18/1991</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   emp_no title_id  birth_date  first_name  last_name sex   hire_date  salary\n",
       "0  473302    s0001   7/25/1953    Hideyuki   Zallocco   M   4/28/1990   40000\n",
       "1  475053    e0002  11/18/1954       Byong  Delgrande   F    9/7/1991   53422\n",
       "2   57444    e0002   1/30/1958       Berry       Babb   F   3/21/1992   48973\n",
       "3  421786    s0001   9/28/1957       Xiong   Verhoeff   M  11/26/1987   40000\n",
       "4  282238    e0003  10/28/1952  Abdelkader    Baumann   F   1/18/1991   40000"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Join \n",
    "#first, join salaries to employees on emp_no\n",
    "emp_sal = employees_df.merge(salaries_df, on = \"emp_no\")\n",
    "emp_sal.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>emp_no</th>\n",
       "      <th>title_id</th>\n",
       "      <th>birth_date</th>\n",
       "      <th>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>sex</th>\n",
       "      <th>hire_date</th>\n",
       "      <th>salary</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>473302</td>\n",
       "      <td>s0001</td>\n",
       "      <td>7/25/1953</td>\n",
       "      <td>Hideyuki</td>\n",
       "      <td>Zallocco</td>\n",
       "      <td>M</td>\n",
       "      <td>4/28/1990</td>\n",
       "      <td>40000</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>421786</td>\n",
       "      <td>s0001</td>\n",
       "      <td>9/28/1957</td>\n",
       "      <td>Xiong</td>\n",
       "      <td>Verhoeff</td>\n",
       "      <td>M</td>\n",
       "      <td>11/26/1987</td>\n",
       "      <td>40000</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>273487</td>\n",
       "      <td>s0001</td>\n",
       "      <td>4/14/1957</td>\n",
       "      <td>Christoph</td>\n",
       "      <td>Parfitt</td>\n",
       "      <td>M</td>\n",
       "      <td>6/28/1991</td>\n",
       "      <td>56087</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>246449</td>\n",
       "      <td>s0001</td>\n",
       "      <td>3/23/1958</td>\n",
       "      <td>Subbu</td>\n",
       "      <td>Bultermann</td>\n",
       "      <td>F</td>\n",
       "      <td>3/25/1988</td>\n",
       "      <td>87084</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48085</td>\n",
       "      <td>s0001</td>\n",
       "      <td>1/19/1964</td>\n",
       "      <td>Venkatesan</td>\n",
       "      <td>Gilg</td>\n",
       "      <td>M</td>\n",
       "      <td>6/28/1993</td>\n",
       "      <td>63016</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   emp_no title_id birth_date  first_name   last_name sex   hire_date  salary  \\\n",
       "0  473302    s0001  7/25/1953    Hideyuki    Zallocco   M   4/28/1990   40000   \n",
       "1  421786    s0001  9/28/1957       Xiong    Verhoeff   M  11/26/1987   40000   \n",
       "2  273487    s0001  4/14/1957   Christoph     Parfitt   M   6/28/1991   56087   \n",
       "3  246449    s0001  3/23/1958       Subbu  Bultermann   F   3/25/1988   87084   \n",
       "4   48085    s0001  1/19/1964  Venkatesan        Gilg   M   6/28/1993   63016   \n",
       "\n",
       "   title  \n",
       "0  Staff  \n",
       "1  Staff  \n",
       "2  Staff  \n",
       "3  Staff  \n",
       "4  Staff  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Join the titles table to the newly created db on emp_title_id and␣ title_id\n",
    "final_db = emp_sal.merge(titles_df, left_on = \"title_id\", right_on = \"title_id\")\n",
    "final_db.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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>salary</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40000</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40000</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56087</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>87084</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>63016</td>\n",
       "      <td>Staff</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   salary  title\n",
       "0   40000  Staff\n",
       "1   40000  Staff\n",
       "2   56087  Staff\n",
       "3   87084  Staff\n",
       "4   63016  Staff"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Extract a db of only the titles and salaries\n",
    "sal_title_db = final_db[['salary','title']]\n",
    "sal_title_db.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "Assistant Engineer    48564.0\n",
       "Engineer              48535.0\n",
       "Manager               51531.0\n",
       "Senior Engineer       48507.0\n",
       "Senior Staff          58550.0\n",
       "Staff                 58465.0\n",
       "Technique Leader      48583.0\n",
       "Name: salary, dtype: float64"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#groupby and mean() for the salaries\n",
    "#edited to round() to zero digits\n",
    "sal_title_db.groupby('title')['salary'].mean().round(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Salary Average Distribution')"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now we can graph these salaries\n",
    "sal_title_db.hist(column='salary',color = 'blue')\n",
    "plt.xlabel('Salary Range')\n",
    "plt.ylabel('Salary Frequency/Count')\n",
    "plt.title('Salary Average Distribution')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}