ROI - Project1-Team5.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Dependencies \n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import scipy.stats as st\n",
    "import numpy as np\n",
    "from scipy.stats import linregress\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>School Name</th>\n",
       "      <th>School Type</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Mid-Career Median Salary</th>\n",
       "      <th>Mid-Career 10th Percentile Salary</th>\n",
       "      <th>Mid-Career 25th Percentile Salary</th>\n",
       "      <th>Mid-Career 75th Percentile Salary</th>\n",
       "      <th>Mid-Career 90th Percentile Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Massachusetts Institute of Technology (MIT)</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$72,200.00</td>\n",
       "      <td>$126,000.00</td>\n",
       "      <td>$76,800.00</td>\n",
       "      <td>$99,200.00</td>\n",
       "      <td>$168,000.00</td>\n",
       "      <td>$220,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>California Institute of Technology (CIT)</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$75,500.00</td>\n",
       "      <td>$123,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$104,000.00</td>\n",
       "      <td>$161,000.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Harvey Mudd College</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$71,800.00</td>\n",
       "      <td>$122,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$96,000.00</td>\n",
       "      <td>$180,000.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Polytechnic University of New York, Brooklyn</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$62,400.00</td>\n",
       "      <td>$114,000.00</td>\n",
       "      <td>$66,800.00</td>\n",
       "      <td>$94,300.00</td>\n",
       "      <td>$143,000.00</td>\n",
       "      <td>$190,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Cooper Union</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$62,200.00</td>\n",
       "      <td>$114,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$80,200.00</td>\n",
       "      <td>$142,000.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    School Name  School Type  \\\n",
       "0   Massachusetts Institute of Technology (MIT)  Engineering   \n",
       "1      California Institute of Technology (CIT)  Engineering   \n",
       "2                           Harvey Mudd College  Engineering   \n",
       "3  Polytechnic University of New York, Brooklyn  Engineering   \n",
       "4                                  Cooper Union  Engineering   \n",
       "\n",
       "  Starting Median Salary Mid-Career Median Salary  \\\n",
       "0            $72,200.00              $126,000.00    \n",
       "1            $75,500.00              $123,000.00    \n",
       "2            $71,800.00              $122,000.00    \n",
       "3            $62,400.00              $114,000.00    \n",
       "4            $62,200.00              $114,000.00    \n",
       "\n",
       "  Mid-Career 10th Percentile Salary Mid-Career 25th Percentile Salary  \\\n",
       "0                       $76,800.00                        $99,200.00    \n",
       "1                               NaN                      $104,000.00    \n",
       "2                               NaN                       $96,000.00    \n",
       "3                       $66,800.00                        $94,300.00    \n",
       "4                               NaN                       $80,200.00    \n",
       "\n",
       "  Mid-Career 75th Percentile Salary Mid-Career 90th Percentile Salary  \n",
       "0                      $168,000.00                       $220,000.00   \n",
       "1                      $161,000.00                                NaN  \n",
       "2                      $180,000.00                                NaN  \n",
       "3                      $143,000.00                       $190,000.00   \n",
       "4                      $142,000.00                                NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "college_data = \"Resources/salaries-by-college-type.csv\"\n",
    "region_data = \"Resources/salaries-by-region.csv\"\n",
    "with open(\"Resources/costOfAttendence1.csv\", encoding=\"utf8\", errors='ignore') as cost_data:\n",
    "#cost_data = \"Resources/costOfAttendence.csv\"\n",
    "# load colleges by state data\n",
    "\n",
    "# Read the mouse data and the study results into a pandas dataframe\n",
    "    college_data = pd.read_csv(college_data)\n",
    "    region_data = pd.read_csv(region_data)\n",
    "    cost_data = pd.read_csv(cost_data)\n",
    "college_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>School Name</th>\n",
       "      <th>Region</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Mid-Career Median Salary</th>\n",
       "      <th>Mid-Career 10th Percentile Salary</th>\n",
       "      <th>Mid-Career 25th Percentile Salary</th>\n",
       "      <th>Mid-Career 75th Percentile Salary</th>\n",
       "      <th>Mid-Career 90th Percentile Salary</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>University of Alaska, Anchorage</td>\n",
       "      <td>Western</td>\n",
       "      <td>$45,900.00</td>\n",
       "      <td>$72,600.00</td>\n",
       "      <td>$39,800.00</td>\n",
       "      <td>$56,600.00</td>\n",
       "      <td>$99,300.00</td>\n",
       "      <td>$137,000.00</td>\n",
       "      <td>AK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>University of Alabama at Birmingham (UAB)</td>\n",
       "      <td>Southern</td>\n",
       "      <td>$39,200.00</td>\n",
       "      <td>$70,100.00</td>\n",
       "      <td>$43,000.00</td>\n",
       "      <td>$53,400.00</td>\n",
       "      <td>$91,400.00</td>\n",
       "      <td>$125,000.00</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>University of Alabama, Tuscaloosa</td>\n",
       "      <td>Southern</td>\n",
       "      <td>$41,300.00</td>\n",
       "      <td>$81,400.00</td>\n",
       "      <td>$40,100.00</td>\n",
       "      <td>$56,500.00</td>\n",
       "      <td>$117,000.00</td>\n",
       "      <td>$161,000.00</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>University of Alabama at Huntsville (UAH)</td>\n",
       "      <td>Southern</td>\n",
       "      <td>$43,100.00</td>\n",
       "      <td>$82,700.00</td>\n",
       "      <td>$46,100.00</td>\n",
       "      <td>$67,800.00</td>\n",
       "      <td>$106,000.00</td>\n",
       "      <td>$132,000.00</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Auburn University</td>\n",
       "      <td>Southern</td>\n",
       "      <td>$45,400.00</td>\n",
       "      <td>$84,700.00</td>\n",
       "      <td>$45,400.00</td>\n",
       "      <td>$62,700.00</td>\n",
       "      <td>$109,000.00</td>\n",
       "      <td>$145,000.00</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 School Name    Region Starting Median Salary  \\\n",
       "0            University of Alaska, Anchorage   Western            $45,900.00    \n",
       "1  University of Alabama at Birmingham (UAB)  Southern            $39,200.00    \n",
       "2          University of Alabama, Tuscaloosa  Southern            $41,300.00    \n",
       "3  University of Alabama at Huntsville (UAH)  Southern            $43,100.00    \n",
       "4                          Auburn University  Southern            $45,400.00    \n",
       "\n",
       "  Mid-Career Median Salary Mid-Career 10th Percentile Salary  \\\n",
       "0              $72,600.00                        $39,800.00    \n",
       "1              $70,100.00                        $43,000.00    \n",
       "2              $81,400.00                        $40,100.00    \n",
       "3              $82,700.00                        $46,100.00    \n",
       "4              $84,700.00                        $45,400.00    \n",
       "\n",
       "  Mid-Career 25th Percentile Salary Mid-Career 75th Percentile Salary  \\\n",
       "0                       $56,600.00                        $99,300.00    \n",
       "1                       $53,400.00                        $91,400.00    \n",
       "2                       $56,500.00                       $117,000.00    \n",
       "3                       $67,800.00                       $106,000.00    \n",
       "4                       $62,700.00                       $109,000.00    \n",
       "\n",
       "  Mid-Career 90th Percentile Salary State  \n",
       "0                      $137,000.00     AK  \n",
       "1                      $125,000.00     AL  \n",
       "2                      $161,000.00     AL  \n",
       "3                      $132,000.00     AL  \n",
       "4                      $145,000.00     AL  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "region_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>School Name</th>\n",
       "      <th>School Type</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Mid-Career Median Salary</th>\n",
       "      <th>Mid-Career 10th Percentile Salary</th>\n",
       "      <th>Mid-Career 25th Percentile Salary</th>\n",
       "      <th>Mid-Career 75th Percentile Salary</th>\n",
       "      <th>Mid-Career 90th Percentile Salary</th>\n",
       "      <th>Region</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Massachusetts Institute of Technology (MIT)</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$72,200.00</td>\n",
       "      <td>$126,000.00</td>\n",
       "      <td>$76,800.00</td>\n",
       "      <td>$99,200.00</td>\n",
       "      <td>$168,000.00</td>\n",
       "      <td>$220,000.00</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>MA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>California Institute of Technology (CIT)</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$75,500.00</td>\n",
       "      <td>$123,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$104,000.00</td>\n",
       "      <td>$161,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Western</td>\n",
       "      <td>CA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Harvey Mudd College</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$71,800.00</td>\n",
       "      <td>$122,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$96,000.00</td>\n",
       "      <td>$180,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Western</td>\n",
       "      <td>CA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Polytechnic University of New York, Brooklyn</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$62,400.00</td>\n",
       "      <td>$114,000.00</td>\n",
       "      <td>$66,800.00</td>\n",
       "      <td>$94,300.00</td>\n",
       "      <td>$143,000.00</td>\n",
       "      <td>$190,000.00</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Cooper Union</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$62,200.00</td>\n",
       "      <td>$114,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$80,200.00</td>\n",
       "      <td>$142,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>NY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    School Name  School Type  \\\n",
       "0   Massachusetts Institute of Technology (MIT)  Engineering   \n",
       "1      California Institute of Technology (CIT)  Engineering   \n",
       "2                           Harvey Mudd College  Engineering   \n",
       "3  Polytechnic University of New York, Brooklyn  Engineering   \n",
       "4                                  Cooper Union  Engineering   \n",
       "\n",
       "  Starting Median Salary Mid-Career Median Salary  \\\n",
       "0            $72,200.00              $126,000.00    \n",
       "1            $75,500.00              $123,000.00    \n",
       "2            $71,800.00              $122,000.00    \n",
       "3            $62,400.00              $114,000.00    \n",
       "4            $62,200.00              $114,000.00    \n",
       "\n",
       "  Mid-Career 10th Percentile Salary Mid-Career 25th Percentile Salary  \\\n",
       "0                       $76,800.00                        $99,200.00    \n",
       "1                               NaN                      $104,000.00    \n",
       "2                               NaN                       $96,000.00    \n",
       "3                       $66,800.00                        $94,300.00    \n",
       "4                               NaN                       $80,200.00    \n",
       "\n",
       "  Mid-Career 75th Percentile Salary Mid-Career 90th Percentile Salary  \\\n",
       "0                      $168,000.00                       $220,000.00    \n",
       "1                      $161,000.00                                NaN   \n",
       "2                      $180,000.00                                NaN   \n",
       "3                      $143,000.00                       $190,000.00    \n",
       "4                      $142,000.00                                NaN   \n",
       "\n",
       "         Region State  \n",
       "0  Northeastern    MA  \n",
       "1       Western    CA  \n",
       "2       Western    CA  \n",
       "3  Northeastern    NY  \n",
       "4  Northeastern    NY  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge college data and region data dataframes\n",
    "merged_data = pd.merge(college_data, region_data, how='right', on=['School Name',\n",
    "                'Starting Median Salary',\n",
    "                'Mid-Career Median Salary',\n",
    "                'Mid-Career 10th Percentile Salary',\n",
    "                'Mid-Career 25th Percentile Salary',\n",
    "                'Mid-Career 75th Percentile Salary',\n",
    "                'Mid-Career 90th Percentile Salary'])\n",
    "merged_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add cost Of Attendence to Merged dataframe\n",
    "combined_merged_data = pd.merge(merged_data, cost_data, how='left',left_index=True, \n",
    "                        right_index=True,on=['School Name'])\n",
    "#combined_merged_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(340, 15)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine the shape of the data, how many rows and columns\n",
    "combined_merged_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 340 entries, 0 to 339\n",
      "Data columns (total 15 columns):\n",
      "School Name                          340 non-null object\n",
      "School Type                          260 non-null object\n",
      "Starting Median Salary               340 non-null object\n",
      "Mid-Career Median Salary             340 non-null object\n",
      "Mid-Career 10th Percentile Salary    292 non-null object\n",
      "Mid-Career 25th Percentile Salary    340 non-null object\n",
      "Mid-Career 75th Percentile Salary    340 non-null object\n",
      "Mid-Career 90th Percentile Salary    292 non-null object\n",
      "Region                               340 non-null object\n",
      "State                                340 non-null object\n",
      "Rank 2015                            340 non-null int64\n",
      "Rank 2014                            340 non-null int64\n",
      "Cost 2015                            340 non-null object\n",
      "Cost 2014                            340 non-null object\n",
      "% Change                             340 non-null object\n",
      "dtypes: int64(2), object(13)\n",
      "memory usage: 52.5+ KB\n"
     ]
    }
   ],
   "source": [
    "# review data information to see the type of data, columns with missing values\n",
    "combined_merged_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleanup & Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>School Name</th>\n",
       "      <th>School Type</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Mid-Career Median Salary</th>\n",
       "      <th>Mid-Career 10th Percentile Salary</th>\n",
       "      <th>Mid-Career 25th Percentile Salary</th>\n",
       "      <th>Mid-Career 75th Percentile Salary</th>\n",
       "      <th>Mid-Career 90th Percentile Salary</th>\n",
       "      <th>Region</th>\n",
       "      <th>State</th>\n",
       "      <th>Rank 2015</th>\n",
       "      <th>Rank 2014</th>\n",
       "      <th>Cost 2015</th>\n",
       "      <th>Cost 2014</th>\n",
       "      <th>% Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Massachusetts Institute of Technology (MIT)</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$72,200.00</td>\n",
       "      <td>$126,000.00</td>\n",
       "      <td>$76,800.00</td>\n",
       "      <td>$99,200.00</td>\n",
       "      <td>$168,000.00</td>\n",
       "      <td>$220,000.00</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>$82,824</td>\n",
       "      <td>$82,824</td>\n",
       "      <td>0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>California Institute of Technology (CIT)</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$75,500.00</td>\n",
       "      <td>$123,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$104,000.00</td>\n",
       "      <td>$161,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Western</td>\n",
       "      <td>CA</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>$66,400</td>\n",
       "      <td>$55,496</td>\n",
       "      <td>19.65%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Harvey Mudd College</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$71,800.00</td>\n",
       "      <td>$122,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$96,000.00</td>\n",
       "      <td>$180,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Western</td>\n",
       "      <td>CA</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>$64,988</td>\n",
       "      <td>$53,438</td>\n",
       "      <td>21.61%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Polytechnic University of New York, Brooklyn</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$62,400.00</td>\n",
       "      <td>$114,000.00</td>\n",
       "      <td>$66,800.00</td>\n",
       "      <td>$94,300.00</td>\n",
       "      <td>$143,000.00</td>\n",
       "      <td>$190,000.00</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>NY</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>$64,830</td>\n",
       "      <td>$50,800</td>\n",
       "      <td>27.62%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Cooper Union</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>$62,200.00</td>\n",
       "      <td>$114,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$80,200.00</td>\n",
       "      <td>$142,000.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>NY</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>$64,144</td>\n",
       "      <td>$45,396</td>\n",
       "      <td>41.30%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    School Name  School Type  \\\n",
       "0   Massachusetts Institute of Technology (MIT)  Engineering   \n",
       "1      California Institute of Technology (CIT)  Engineering   \n",
       "2                           Harvey Mudd College  Engineering   \n",
       "3  Polytechnic University of New York, Brooklyn  Engineering   \n",
       "4                                  Cooper Union  Engineering   \n",
       "\n",
       "  Starting Median Salary Mid-Career Median Salary  \\\n",
       "0            $72,200.00              $126,000.00    \n",
       "1            $75,500.00              $123,000.00    \n",
       "2            $71,800.00              $122,000.00    \n",
       "3            $62,400.00              $114,000.00    \n",
       "4            $62,200.00              $114,000.00    \n",
       "\n",
       "  Mid-Career 10th Percentile Salary Mid-Career 25th Percentile Salary  \\\n",
       "0                       $76,800.00                        $99,200.00    \n",
       "1                               NaN                      $104,000.00    \n",
       "2                               NaN                       $96,000.00    \n",
       "3                       $66,800.00                        $94,300.00    \n",
       "4                               NaN                       $80,200.00    \n",
       "\n",
       "  Mid-Career 75th Percentile Salary Mid-Career 90th Percentile Salary  \\\n",
       "0                      $168,000.00                       $220,000.00    \n",
       "1                      $161,000.00                                NaN   \n",
       "2                      $180,000.00                                NaN   \n",
       "3                      $143,000.00                       $190,000.00    \n",
       "4                      $142,000.00                                NaN   \n",
       "\n",
       "         Region State  Rank 2015  Rank 2014 Cost 2015 Cost 2014 % Change  \n",
       "0  Northeastern    MA          1          1  $82,824   $82,824     0.00%  \n",
       "1       Western    CA          2          2  $66,400   $55,496    19.65%  \n",
       "2       Western    CA          3          5  $64,988   $53,438    21.61%  \n",
       "3  Northeastern    NY          4          3  $64,830   $50,800    27.62%  \n",
       "4  Northeastern    NY          5          6  $64,144   $45,396    41.30%  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# count the number of missing values\n",
    "#combined_merged_data.isnull().sum()\n",
    "combined_merged_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "##covert data columns to numerical values in order to perform analysis on the data\n",
    "# for multiple columns, put them in a list like so:\n",
    "#cols = ['col1', 'col2', ..., 'colN']\n",
    "\n",
    "cols = ['Starting Median Salary', \n",
    "        'Mid-Career Median Salary',\n",
    "        'Mid-Career 10th Percentile Salary',\n",
    "        'Mid-Career 25th Percentile Salary',\n",
    "        'Mid-Career 75th Percentile Salary',\n",
    "        'Mid-Career 90th Percentile Salary',\n",
    "        'Cost 2015', 'Cost 2014','% Change']\n",
    "combined_merged_data[cols] = combined_merged_data[cols].astype(str)\n",
    "\n",
    "# pass them to df.replace(), specifying each char and it's replacement:\n",
    "combined_merged_data[cols] = combined_merged_data[cols].replace({'\\$': '', ',': '', '%': ''}, regex=True)\n",
    "combined_merged_data[cols] = combined_merged_data[cols].astype(float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>School Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Region</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Mid-Career Median Salary</th>\n",
       "      <th>Cost 2014</th>\n",
       "      <th>Cost 2015</th>\n",
       "      <th>% Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Massachusetts Institute of Technology (MIT)</td>\n",
       "      <td>MA</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>72200.0</td>\n",
       "      <td>126000.0</td>\n",
       "      <td>82824.0</td>\n",
       "      <td>82824.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>California Institute of Technology (CIT)</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>75500.0</td>\n",
       "      <td>123000.0</td>\n",
       "      <td>55496.0</td>\n",
       "      <td>66400.0</td>\n",
       "      <td>19.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Harvey Mudd College</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>71800.0</td>\n",
       "      <td>122000.0</td>\n",
       "      <td>53438.0</td>\n",
       "      <td>64988.0</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Polytechnic University of New York, Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>62400.0</td>\n",
       "      <td>114000.0</td>\n",
       "      <td>50800.0</td>\n",
       "      <td>64830.0</td>\n",
       "      <td>27.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Cooper Union</td>\n",
       "      <td>NY</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>62200.0</td>\n",
       "      <td>114000.0</td>\n",
       "      <td>45396.0</td>\n",
       "      <td>64144.0</td>\n",
       "      <td>41.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    School Name State        Region  \\\n",
       "0   Massachusetts Institute of Technology (MIT)    MA  Northeastern   \n",
       "1      California Institute of Technology (CIT)    CA       Western   \n",
       "2                           Harvey Mudd College    CA       Western   \n",
       "3  Polytechnic University of New York, Brooklyn    NY  Northeastern   \n",
       "4                                  Cooper Union    NY  Northeastern   \n",
       "\n",
       "   Starting Median Salary  Mid-Career Median Salary  Cost 2014  Cost 2015  \\\n",
       "0                 72200.0                  126000.0    82824.0    82824.0   \n",
       "1                 75500.0                  123000.0    55496.0    66400.0   \n",
       "2                 71800.0                  122000.0    53438.0    64988.0   \n",
       "3                 62400.0                  114000.0    50800.0    64830.0   \n",
       "4                 62200.0                  114000.0    45396.0    64144.0   \n",
       "\n",
       "   % Change  \n",
       "0      0.00  \n",
       "1     19.65  \n",
       "2     21.61  \n",
       "3     27.62  \n",
       "4     41.30  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a dataframe for the data i want to analyze\n",
    "regionSalary_df = combined_merged_data.loc[:,['School Name','State','Region','Starting Median Salary',\n",
    "                'Mid-Career Median Salary','Cost 2014','Cost 2015','% Change']] \n",
    "regionSalary_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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",
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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>School Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Region</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Mid-Career Median Salary</th>\n",
       "      <th>Cost 2014</th>\n",
       "      <th>Cost 2015</th>\n",
       "      <th>% Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>California Institute of Technology (CIT)</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>75500.0</td>\n",
       "      <td>123000.0</td>\n",
       "      <td>55496.0</td>\n",
       "      <td>66400.0</td>\n",
       "      <td>19.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Massachusetts Institute of Technology (MIT)</td>\n",
       "      <td>MA</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>72200.0</td>\n",
       "      <td>126000.0</td>\n",
       "      <td>82824.0</td>\n",
       "      <td>82824.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Harvey Mudd College</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>71800.0</td>\n",
       "      <td>122000.0</td>\n",
       "      <td>53438.0</td>\n",
       "      <td>64988.0</td>\n",
       "      <td>21.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>263</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>70400.0</td>\n",
       "      <td>129000.0</td>\n",
       "      <td>46500.0</td>\n",
       "      <td>49923.0</td>\n",
       "      <td>7.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>103</td>\n",
       "      <td>Princeton University</td>\n",
       "      <td>NY</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>66500.0</td>\n",
       "      <td>131000.0</td>\n",
       "      <td>56050.0</td>\n",
       "      <td>58559.0</td>\n",
       "      <td>4.48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     School Name State        Region  \\\n",
       "1       California Institute of Technology (CIT)    CA       Western   \n",
       "0    Massachusetts Institute of Technology (MIT)    MA  Northeastern   \n",
       "2                            Harvey Mudd College    CA       Western   \n",
       "263                          Stanford University    CA       Western   \n",
       "103                         Princeton University    NY  Northeastern   \n",
       "\n",
       "     Starting Median Salary  Mid-Career Median Salary  Cost 2014  Cost 2015  \\\n",
       "1                   75500.0                  123000.0    55496.0    66400.0   \n",
       "0                   72200.0                  126000.0    82824.0    82824.0   \n",
       "2                   71800.0                  122000.0    53438.0    64988.0   \n",
       "263                 70400.0                  129000.0    46500.0    49923.0   \n",
       "103                 66500.0                  131000.0    56050.0    58559.0   \n",
       "\n",
       "     % Change  \n",
       "1       19.65  \n",
       "0        0.00  \n",
       "2       21.61  \n",
       "263      7.36  \n",
       "103      4.48  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort values by starting median salary, so that our graph will be in order\n",
    "regionSalary_df.sort_values(by = 'Starting Median Salary', ascending = False, inplace=True)\n",
    "regionSalary_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create new index\n",
    "regionSalary_df.reset_index(drop=True, inplace=True)\n",
    "regionSalary_df\n",
    "# median salaries of the Top 30 schools\n",
    "TOPschoolsSalary_df=regionSalary_df.loc[0:29,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#TOPschoolsSalary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Return on Investment (ROI): Total Tution (4-years) vs. Starting Salary (first 4-years)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "#GIVE VALUES TO COLUMNS TO MANIPULATE\n",
    "starting_salary = combined_merged_data[\"Starting Median Salary\"]\n",
    "starting_salary_FourYrs = starting_salary*20\n",
    "cost_2015 = combined_merged_data[\"Cost 2015\"]\n",
    "cost_2014 = combined_merged_data[\"Cost 2014\"]\n",
    "school_name = combined_merged_data[\"School Name\"]\n",
    "per_change = combined_merged_data[\"% Change\"]\n",
    "state = combined_merged_data[\"State\"]\n",
    "region = combined_merged_data[\"Region\"]\n",
    "total_tuition = (cost_2014+cost_2015)*2\n",
    "mid_salary = combined_merged_data[\"Mid-Career Median Salary\"]\n",
    "#EARNINGS POTENTIAL\n",
    "#roi = NET PROFIT (income) / TOTAL INVESTMENT (invested capital)x100\n",
    "#Starting salary ~0-5 years\n",
    "roi = (total_tuition/starting_salary_FourYrs)*100\n",
    "roi2 = (total_tuition/mid_salary)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ADD NEW COLUMNS\n",
    "combined_merged_data[\"ROI\"] = roi\n",
    "combined_merged_data[\"ROI (Mid-Career)\"] = roi2\n",
    "combined_merged_data[\"Undergrad Tuition (4-Years)\"] = total_tuition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## OBSVERVATION:\n",
    "There are colleges that have an outstanding ROI when comparing the first four years in an entry-level (~3 years) position and the cost of a undergraduate degree (e.g. MIT, Georgia Tech, Brown University, etc.). \n",
    "\n",
    "*The ROIs are ONLY based on starting median salary (20 years) & cost of attendance (4 years)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>School Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Region</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Undergrad Tuition (4-Years)</th>\n",
       "      <th>ROI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>88</td>\n",
       "      <td>Colorado College (CC)</td>\n",
       "      <td>CO</td>\n",
       "      <td>Western</td>\n",
       "      <td>38500.0</td>\n",
       "      <td>238382.0</td>\n",
       "      <td>30.958701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>98</td>\n",
       "      <td>Lewis &amp; Clark College</td>\n",
       "      <td>OR</td>\n",
       "      <td>Western</td>\n",
       "      <td>38900.0</td>\n",
       "      <td>231940.0</td>\n",
       "      <td>29.812339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>94</td>\n",
       "      <td>Wittenberg University</td>\n",
       "      <td>OH</td>\n",
       "      <td>Midwestern</td>\n",
       "      <td>39200.0</td>\n",
       "      <td>232252.0</td>\n",
       "      <td>29.623980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>University of Alabama, Tuscaloosa</td>\n",
       "      <td>AL</td>\n",
       "      <td>Southern</td>\n",
       "      <td>41300.0</td>\n",
       "      <td>242004.0</td>\n",
       "      <td>29.298305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>101</td>\n",
       "      <td>Evergreen State College</td>\n",
       "      <td>WA</td>\n",
       "      <td>Western</td>\n",
       "      <td>39500.0</td>\n",
       "      <td>230382.0</td>\n",
       "      <td>29.162278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>University of Alabama, Tuscaloosa</td>\n",
       "      <td>AL</td>\n",
       "      <td>Southern</td>\n",
       "      <td>41300.0</td>\n",
       "      <td>240356.0</td>\n",
       "      <td>29.098789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>University of Mississippi</td>\n",
       "      <td>MS</td>\n",
       "      <td>Southern</td>\n",
       "      <td>41400.0</td>\n",
       "      <td>240300.0</td>\n",
       "      <td>29.021739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>University of Mississippi</td>\n",
       "      <td>MS</td>\n",
       "      <td>Southern</td>\n",
       "      <td>41400.0</td>\n",
       "      <td>240240.0</td>\n",
       "      <td>29.014493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>89</td>\n",
       "      <td>Reed College</td>\n",
       "      <td>OR</td>\n",
       "      <td>Western</td>\n",
       "      <td>40500.0</td>\n",
       "      <td>234776.0</td>\n",
       "      <td>28.984691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>University of New Hampshire (UNH)</td>\n",
       "      <td>NH</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>41800.0</td>\n",
       "      <td>241544.0</td>\n",
       "      <td>28.892823</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           School Name State        Region  \\\n",
       "88               Colorado College (CC)    CO       Western   \n",
       "98               Lewis & Clark College    OR       Western   \n",
       "94               Wittenberg University    OH    Midwestern   \n",
       "45   University of Alabama, Tuscaloosa    AL      Southern   \n",
       "101            Evergreen State College    WA       Western   \n",
       "44   University of Alabama, Tuscaloosa    AL      Southern   \n",
       "47           University of Mississippi    MS      Southern   \n",
       "46           University of Mississippi    MS      Southern   \n",
       "89                        Reed College    OR       Western   \n",
       "48   University of New Hampshire (UNH)    NH  Northeastern   \n",
       "\n",
       "     Starting Median Salary  Undergrad Tuition (4-Years)        ROI  \n",
       "88                  38500.0                     238382.0  30.958701  \n",
       "98                  38900.0                     231940.0  29.812339  \n",
       "94                  39200.0                     232252.0  29.623980  \n",
       "45                  41300.0                     242004.0  29.298305  \n",
       "101                 39500.0                     230382.0  29.162278  \n",
       "44                  41300.0                     240356.0  29.098789  \n",
       "47                  41400.0                     240300.0  29.021739  \n",
       "46                  41400.0                     240240.0  29.014493  \n",
       "89                  40500.0                     234776.0  28.984691  \n",
       "48                  41800.0                     241544.0  28.892823  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "roi_salaries_df = combined_merged_data[[\"School Name\",\"State\",\"Region\",\"Starting Median Salary\",\\\n",
    "                                       \"Undergrad Tuition (4-Years)\", \"ROI\"]]\n",
    "#,\"% Change\",\"Mid-Career Median Salary\",\"ROI (Mid-Career)\"]]\n",
    "#Sorting from highest to lowest 'difference'\n",
    "roi_highest = roi_salaries_df.sort_values(\"ROI\",ascending=False)\n",
    "roi_highest.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## OBSVERVATION:\n",
    "The universities with the lowest ROI include top universities such as Stanford, Rice, and Duke. Thus, leading us to the conclusion that ivy league education doesn't necessarily mean you'll be earning higher wages. \n",
    "\n",
    "*The ROIs are ONLY based on starting median salary (20 years) & cost of attendance (4 years)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>School Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Region</th>\n",
       "      <th>Starting Median Salary</th>\n",
       "      <th>Undergrad Tuition (4-Years)</th>\n",
       "      <th>ROI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>263</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>70400.0</td>\n",
       "      <td>192846.0</td>\n",
       "      <td>13.696449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>332</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>TX</td>\n",
       "      <td>Southern</td>\n",
       "      <td>64000.0</td>\n",
       "      <td>186242.0</td>\n",
       "      <td>14.550156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>311</td>\n",
       "      <td>Pace University</td>\n",
       "      <td>NY</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>53200.0</td>\n",
       "      <td>159040.0</td>\n",
       "      <td>14.947368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>321</td>\n",
       "      <td>Lehigh University</td>\n",
       "      <td>PA</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>59200.0</td>\n",
       "      <td>187564.0</td>\n",
       "      <td>15.841554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>294</td>\n",
       "      <td>Duke University</td>\n",
       "      <td>NC</td>\n",
       "      <td>Southern</td>\n",
       "      <td>58900.0</td>\n",
       "      <td>189540.0</td>\n",
       "      <td>16.089983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>California Institute of Technology (CIT)</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>75500.0</td>\n",
       "      <td>243792.0</td>\n",
       "      <td>16.145166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>University of Texas (UT) - Austin</td>\n",
       "      <td>TX</td>\n",
       "      <td>Southern</td>\n",
       "      <td>49700.0</td>\n",
       "      <td>160680.0</td>\n",
       "      <td>16.164990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Harvey Mudd College</td>\n",
       "      <td>CA</td>\n",
       "      <td>Western</td>\n",
       "      <td>71800.0</td>\n",
       "      <td>236852.0</td>\n",
       "      <td>16.493872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>320</td>\n",
       "      <td>Villanova University</td>\n",
       "      <td>PA</td>\n",
       "      <td>Northeastern</td>\n",
       "      <td>55800.0</td>\n",
       "      <td>185076.0</td>\n",
       "      <td>16.583871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>312</td>\n",
       "      <td>Case Western Reserve University</td>\n",
       "      <td>OH</td>\n",
       "      <td>Midwestern</td>\n",
       "      <td>56200.0</td>\n",
       "      <td>188852.0</td>\n",
       "      <td>16.801779</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  School Name State        Region  \\\n",
       "263                       Stanford University    CA       Western   \n",
       "332                           Rice University    TX      Southern   \n",
       "311                           Pace University    NY  Northeastern   \n",
       "321                         Lehigh University    PA  Northeastern   \n",
       "294                           Duke University    NC      Southern   \n",
       "1    California Institute of Technology (CIT)    CA       Western   \n",
       "25          University of Texas (UT) - Austin    TX      Southern   \n",
       "2                         Harvey Mudd College    CA       Western   \n",
       "320                      Villanova University    PA  Northeastern   \n",
       "312           Case Western Reserve University    OH    Midwestern   \n",
       "\n",
       "     Starting Median Salary  Undergrad Tuition (4-Years)        ROI  \n",
       "263                 70400.0                     192846.0  13.696449  \n",
       "332                 64000.0                     186242.0  14.550156  \n",
       "311                 53200.0                     159040.0  14.947368  \n",
       "321                 59200.0                     187564.0  15.841554  \n",
       "294                 58900.0                     189540.0  16.089983  \n",
       "1                   75500.0                     243792.0  16.145166  \n",
       "25                  49700.0                     160680.0  16.164990  \n",
       "2                   71800.0                     236852.0  16.493872  \n",
       "320                 55800.0                     185076.0  16.583871  \n",
       "312                 56200.0                     188852.0  16.801779  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Sorting from highest to lowest 'difference'\n",
    "roi_lowest = roi_salaries_df.sort_values(\"ROI\",ascending=True)\n",
    "roi_lowest.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#DELETE INDEX\n",
    "#del TOPschoolsSalary_df.index.name\n",
    "#TOPschoolsSalary_df.reset_index\n",
    "#TOPschoolsSalary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sorting from highest to lowest 'difference'\n",
    "#roi_highest = combined_merged_data.sort_values(\"ROI\",ascending=False)\n",
    "#roi_highest"
   ]
  }
 ],
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