{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Exam 1</th>\n",
       "      <th>Exam 2</th>\n",
       "      <th>Exam 3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Student</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Thorny</th>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mac</th>\n",
       "      <td>88</td>\n",
       "      <td>99</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Farva</th>\n",
       "      <td>45</td>\n",
       "      <td>56</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rabbit</th>\n",
       "      <td>59</td>\n",
       "      <td>61</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ursula</th>\n",
       "      <td>73</td>\n",
       "      <td>79</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Foster</th>\n",
       "      <td>89</td>\n",
       "      <td>97</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Exam 1  Exam 2  Exam 3\n",
       "Student                        \n",
       "Thorny      100      90      80\n",
       "Mac          88      99     111\n",
       "Farva        45      56      67\n",
       "Rabbit       59      61      67\n",
       "Ursula       73      79      83\n",
       "Foster       89      97     101"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "sgs = pd.read_csv('super-grades.csv', index_col=0)\n",
    "sgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Farva': 56.0,\n",
       " 'Foster': 95.666666666666671,\n",
       " 'Mac': 99.333333333333329,\n",
       " 'Rabbit': 62.333333333333336,\n",
       " 'Thorny': 90.0,\n",
       " 'Ursula': 78.333333333333329}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{stud: np.mean(sgs.loc[stud]) for stud in sgs.index}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Farva     56.000000\n",
       "Foster    95.666667\n",
       "Mac       99.333333\n",
       "Rabbit    62.333333\n",
       "Thorny    90.000000\n",
       "Ursula    78.333333\n",
       "dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avgs = pd.Series({stud: np.mean(sgs.loc[stud]) for stud in sgs.index})\n",
    "avgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Exam 1</th>\n",
       "      <th>Exam 2</th>\n",
       "      <th>Exam 3</th>\n",
       "      <th>avg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Student</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Thorny</th>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>80</td>\n",
       "      <td>90.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mac</th>\n",
       "      <td>88</td>\n",
       "      <td>99</td>\n",
       "      <td>111</td>\n",
       "      <td>99.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Farva</th>\n",
       "      <td>45</td>\n",
       "      <td>56</td>\n",
       "      <td>67</td>\n",
       "      <td>56.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rabbit</th>\n",
       "      <td>59</td>\n",
       "      <td>61</td>\n",
       "      <td>67</td>\n",
       "      <td>62.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ursula</th>\n",
       "      <td>73</td>\n",
       "      <td>79</td>\n",
       "      <td>83</td>\n",
       "      <td>78.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Foster</th>\n",
       "      <td>89</td>\n",
       "      <td>97</td>\n",
       "      <td>101</td>\n",
       "      <td>95.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Exam 1  Exam 2  Exam 3        avg\n",
       "Student                                   \n",
       "Thorny      100      90      80  90.000000\n",
       "Mac          88      99     111  99.333333\n",
       "Farva        45      56      67  56.000000\n",
       "Rabbit       59      61      67  62.333333\n",
       "Ursula       73      79      83  78.333333\n",
       "Foster       89      97     101  95.666667"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sgs['avg'] = avgs\n",
    "sgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75.666666666666671"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " np.mean(sgs['Exam 1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Exam 1': {'Item Avg': 75.666666666666671},\n",
       " 'Exam 2': {'Item Avg': 80.333333333333329},\n",
       " 'Exam 3': {'Item Avg': 84.833333333333329},\n",
       " 'avg': {'Item Avg': 80.277777777777771}}"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_avgs = {col: {'Item Avg': np.mean(sgs[col])} for col in sgs.columns}\n",
    "item_avgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Exam 1</th>\n",
       "      <th>Exam 2</th>\n",
       "      <th>Exam 3</th>\n",
       "      <th>avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Item Avg</th>\n",
       "      <td>75.666667</td>\n",
       "      <td>80.333333</td>\n",
       "      <td>84.833333</td>\n",
       "      <td>80.277778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Exam 1     Exam 2     Exam 3        avg\n",
       "Item Avg  75.666667  80.333333  84.833333  80.277778"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_avgs_df = pd.DataFrame(item_avgs)\n",
    "item_avgs_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Exam 1</th>\n",
       "      <th>Exam 2</th>\n",
       "      <th>Exam 3</th>\n",
       "      <th>avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Thorny</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>90.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mac</th>\n",
       "      <td>88.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>99.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Farva</th>\n",
       "      <td>45.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>56.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rabbit</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>62.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ursula</th>\n",
       "      <td>73.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>78.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Foster</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>95.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Item Avg</th>\n",
       "      <td>75.666667</td>\n",
       "      <td>80.333333</td>\n",
       "      <td>84.833333</td>\n",
       "      <td>80.277778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Exam 1     Exam 2      Exam 3        avg\n",
       "Thorny    100.000000  90.000000   80.000000  90.000000\n",
       "Mac        88.000000  99.000000  111.000000  99.333333\n",
       "Farva      45.000000  56.000000   67.000000  56.000000\n",
       "Rabbit     59.000000  61.000000   67.000000  62.333333\n",
       "Ursula     73.000000  79.000000   83.000000  78.333333\n",
       "Foster     89.000000  97.000000  101.000000  95.666667\n",
       "Item Avg   75.666667  80.333333   84.833333  80.277778"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sgs = sgs.append(item_avgs_df)\n",
    "sgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Exam 1</th>\n",
       "      <th>Exam 2</th>\n",
       "      <th>Exam 3</th>\n",
       "      <th>avg</th>\n",
       "      <th>Grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Thorny</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mac</th>\n",
       "      <td>88.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>99.333333</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Farva</th>\n",
       "      <td>45.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rabbit</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>62.333333</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ursula</th>\n",
       "      <td>73.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>78.333333</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Foster</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>95.666667</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Item Avg</th>\n",
       "      <td>75.666667</td>\n",
       "      <td>80.333333</td>\n",
       "      <td>84.833333</td>\n",
       "      <td>80.277778</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Exam 1     Exam 2      Exam 3        avg Grade\n",
       "Thorny    100.000000  90.000000   80.000000  90.000000     A\n",
       "Mac        88.000000  99.000000  111.000000  99.333333     A\n",
       "Farva      45.000000  56.000000   67.000000  56.000000     D\n",
       "Rabbit     59.000000  61.000000   67.000000  62.333333     D\n",
       "Ursula     73.000000  79.000000   83.000000  78.333333     C\n",
       "Foster     89.000000  97.000000  101.000000  95.666667     A\n",
       "Item Avg   75.666667  80.333333   84.833333  80.277778     B"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sgs['Grade'] = np.where(sgs['avg'] >= 90, 'A',\n",
    "                        np.where(sgs['avg'] >= 80, 'B',\n",
    "                                 np.where(sgs['avg'] >= 70, 'C',\n",
    "                                          np.where(sgs['avg'] >= 60, 'D',\n",
    "                                                   'D'))))\n",
    "sgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Grade\n",
       "A    3\n",
       "B    1\n",
       "C    1\n",
       "D    2\n",
       "Name: Grade, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sgs['Grade'].groupby(sgs['Grade']).count()\n"
   ]
  }
 ],
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