visualization.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in /usr/local/lib/python3.11/site-packages (1.5.3)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.11/site-packages (1.24.2)\n",
      "Requirement already satisfied: statsmodels in /usr/local/lib/python3.11/site-packages (0.13.5)\n",
      "Requirement already satisfied: matplotlib in /usr/local/lib/python3.11/site-packages (3.7.0)\n",
      "Requirement already satisfied: seaborn in /usr/local/lib/python3.11/site-packages (0.12.2)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in /Users/TrinahMaulion/Library/Python/3.11/lib/python/site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/site-packages (from pandas) (2022.7.1)\n",
      "Requirement already satisfied: patsy>=0.5.2 in /usr/local/lib/python3.11/site-packages (from statsmodels) (0.5.3)\n",
      "Requirement already satisfied: packaging>=21.3 in /Users/TrinahMaulion/Library/Python/3.11/lib/python/site-packages (from statsmodels) (23.0)\n",
      "Requirement already satisfied: scipy>=1.3 in /usr/local/lib/python3.11/site-packages (from statsmodels) (1.10.1)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/site-packages (from matplotlib) (1.0.7)\n",
      "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/site-packages (from matplotlib) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/site-packages (from matplotlib) (4.38.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.11/site-packages (from matplotlib) (1.4.4)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.11/site-packages (from matplotlib) (9.4.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/site-packages (from matplotlib) (3.0.9)\n",
      "Requirement already satisfied: six in /Users/TrinahMaulion/Library/Python/3.11/lib/python/site-packages (from patsy>=0.5.2->statsmodels) (1.16.0)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.0.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython3.11 -m pip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install pandas numpy statsmodels matplotlib seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import math\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import statsmodels.api as sm\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape:  (4424, 35)\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Application mode</th>\n",
       "      <th>Application order</th>\n",
       "      <th>Course</th>\n",
       "      <th>Daytime/evening attendance</th>\n",
       "      <th>Previous qualification</th>\n",
       "      <th>Nacionality</th>\n",
       "      <th>Mother's qualification</th>\n",
       "      <th>Father's qualification</th>\n",
       "      <th>Mother's occupation</th>\n",
       "      <th>...</th>\n",
       "      <th>Curricular units 2nd sem (credited)</th>\n",
       "      <th>Curricular units 2nd sem (enrolled)</th>\n",
       "      <th>Curricular units 2nd sem (evaluations)</th>\n",
       "      <th>Curricular units 2nd sem (approved)</th>\n",
       "      <th>Curricular units 2nd sem (grade)</th>\n",
       "      <th>Curricular units 2nd sem (without evaluations)</th>\n",
       "      <th>Unemployment rate</th>\n",
       "      <th>Inflation rate</th>\n",
       "      <th>GDP</th>\n",
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       "      <td>1.4</td>\n",
       "      <td>1.74</td>\n",
       "      <td>Dropout</td>\n",
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       "      <td>13.9</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>0.79</td>\n",
       "      <td>Graduate</td>\n",
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       "      <td>10.8</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.74</td>\n",
       "      <td>Dropout</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
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       "      <td>9.4</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>-3.12</td>\n",
       "      <td>Graduate</td>\n",
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       "    <tr>\n",
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       "      <td>2</td>\n",
       "      <td>12</td>\n",
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       "      <td>13.9</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>0.79</td>\n",
       "      <td>Graduate</td>\n",
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      "text/plain": [
       "   Marital status  Application mode  Application order  Course  \\\n",
       "0               1                 8                  5       2   \n",
       "1               1                 6                  1      11   \n",
       "2               1                 1                  5       5   \n",
       "3               1                 8                  2      15   \n",
       "4               2                12                  1       3   \n",
       "\n",
       "   Daytime/evening attendance  Previous qualification  Nacionality  \\\n",
       "0                           1                       1            1   \n",
       "1                           1                       1            1   \n",
       "2                           1                       1            1   \n",
       "3                           1                       1            1   \n",
       "4                           0                       1            1   \n",
       "\n",
       "   Mother's qualification  Father's qualification  Mother's occupation  ...  \\\n",
       "0                      13                      10                    6  ...   \n",
       "1                       1                       3                    4  ...   \n",
       "2                      22                      27                   10  ...   \n",
       "3                      23                      27                    6  ...   \n",
       "4                      22                      28                   10  ...   \n",
       "\n",
       "   Curricular units 2nd sem (credited)  Curricular units 2nd sem (enrolled)  \\\n",
       "0                                    0                                    0   \n",
       "1                                    0                                    6   \n",
       "2                                    0                                    6   \n",
       "3                                    0                                    6   \n",
       "4                                    0                                    6   \n",
       "\n",
       "   Curricular units 2nd sem (evaluations)  \\\n",
       "0                                       0   \n",
       "1                                       6   \n",
       "2                                       0   \n",
       "3                                      10   \n",
       "4                                       6   \n",
       "\n",
       "   Curricular units 2nd sem (approved)  Curricular units 2nd sem (grade)  \\\n",
       "0                                    0                          0.000000   \n",
       "1                                    6                         13.666667   \n",
       "2                                    0                          0.000000   \n",
       "3                                    5                         12.400000   \n",
       "4                                    6                         13.000000   \n",
       "\n",
       "   Curricular units 2nd sem (without evaluations)  Unemployment rate  \\\n",
       "0                                               0               10.8   \n",
       "1                                               0               13.9   \n",
       "2                                               0               10.8   \n",
       "3                                               0                9.4   \n",
       "4                                               0               13.9   \n",
       "\n",
       "   Inflation rate   GDP    Target  \n",
       "0             1.4  1.74   Dropout  \n",
       "1            -0.3  0.79  Graduate  \n",
       "2             1.4  1.74   Dropout  \n",
       "3            -0.8 -3.12  Graduate  \n",
       "4            -0.3  0.79  Graduate  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('./dataset.csv')\n",
    "print(\"Shape: \", df.shape)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dropping unecessary columns\n",
    "df = df.drop(['Application order', 'Nacionality', 'International',\n",
    "        'Inflation rate', 'GDP', 'Unemployment rate', 'Displaced'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <th>Daytime/evening attendance</th>\n",
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       "      <th>Father's occupation</th>\n",
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       "      <td>Graduate</td>\n",
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       "   Marital status  Application mode  Course  Daytime/evening attendance  \\\n",
       "0               1                 8       2                           1   \n",
       "1               1                 6      11                           1   \n",
       "2               1                 1       5                           1   \n",
       "3               1                 8      15                           1   \n",
       "4               2                12       3                           0   \n",
       "\n",
       "   Previous qualification  Mother's qualification  Father's qualification  \\\n",
       "0                       1                      13                      10   \n",
       "1                       1                       1                       3   \n",
       "2                       1                      22                      27   \n",
       "3                       1                      23                      27   \n",
       "4                       1                      22                      28   \n",
       "\n",
       "   Mother's occupation  Father's occupation  Educational special needs  ...  \\\n",
       "0                    6                   10                          0  ...   \n",
       "1                    4                    4                          0  ...   \n",
       "2                   10                   10                          0  ...   \n",
       "3                    6                    4                          0  ...   \n",
       "4                   10                   10                          0  ...   \n",
       "\n",
       "   Curricular units 1st sem (approved)  Curricular units 1st sem (grade)  \\\n",
       "0                                    0                          0.000000   \n",
       "1                                    6                         14.000000   \n",
       "2                                    0                          0.000000   \n",
       "3                                    6                         13.428571   \n",
       "4                                    5                         12.333333   \n",
       "\n",
       "   Curricular units 1st sem (without evaluations)  \\\n",
       "0                                               0   \n",
       "1                                               0   \n",
       "2                                               0   \n",
       "3                                               0   \n",
       "4                                               0   \n",
       "\n",
       "   Curricular units 2nd sem (credited)  Curricular units 2nd sem (enrolled)  \\\n",
       "0                                    0                                    0   \n",
       "1                                    0                                    6   \n",
       "2                                    0                                    6   \n",
       "3                                    0                                    6   \n",
       "4                                    0                                    6   \n",
       "\n",
       "   Curricular units 2nd sem (evaluations)  \\\n",
       "0                                       0   \n",
       "1                                       6   \n",
       "2                                       0   \n",
       "3                                      10   \n",
       "4                                       6   \n",
       "\n",
       "   Curricular units 2nd sem (approved)  Curricular units 2nd sem (grade)  \\\n",
       "0                                    0                          0.000000   \n",
       "1                                    6                         13.666667   \n",
       "2                                    0                          0.000000   \n",
       "3                                    5                         12.400000   \n",
       "4                                    6                         13.000000   \n",
       "\n",
       "   Curricular units 2nd sem (without evaluations)    Target  \n",
       "0                                               0   Dropout  \n",
       "1                                               0  Graduate  \n",
       "2                                               0   Dropout  \n",
       "3                                               0  Graduate  \n",
       "4                                               0  Graduate  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creating dataframe with only graduate and dropout students\n",
    "df = df[df.Target != 'Enrolled']\n",
    "# changing categroical values to numerical\n",
    "# df['Target'] = pd.factorize(df['Target'])[0]\n",
    "\n",
    "df.head(5)\n",
    "# df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Course'] = df['Course'].replace(1, 'Biofuel Production Technologies')\n",
    "df['Course'] = df['Course'].replace(2, 'Animation and Multimedia Design')\n",
    "df['Course'] = df['Course'].replace(3, 'Social Service (evening attendance)')\n",
    "df['Course'] = df['Course'].replace(4, 'Agronomy')\n",
    "df['Course'] = df['Course'].replace(5, 'Communication Design')\n",
    "df['Course'] = df['Course'].replace(6, 'Veterinary Nursing')\n",
    "df['Course'] = df['Course'].replace(7, 'Informatics Engineering')\n",
    "df['Course'] = df['Course'].replace(8, 'Equiniculture')\n",
    "df['Course'] = df['Course'].replace(9, 'Management')\n",
    "df['Course'] = df['Course'].replace(10, 'Social Service')\n",
    "df['Course'] = df['Course'].replace(11, 'Tourism')\n",
    "df['Course'] = df['Course'].replace(12, 'Nursing')\n",
    "df['Course'] = df['Course'].replace(13, 'Oral Hygiene')\n",
    "df['Course'] = df['Course'].replace(14, 'Advertising and Marketing Management')\n",
    "df['Course'] = df['Course'].replace(15, 'Journalism and Communication')\n",
    "df['Course'] = df['Course'].replace(16, 'Basic Education')\n",
    "df['Course'] = df['Course'].replace(17, 'Management (evening attendance)')\n",
    "\n",
    "df['Gender'] = df['Gender'].replace(0, 'female')\n",
    "df['Gender'] = df['Gender'].replace(1, 'male')\n",
    "\n",
    "df['Tuition fees up to date'] = df['Tuition fees up to date'].replace(0, 'no')\n",
    "df['Tuition fees up to date'] = df['Tuition fees up to date'].replace(1, 'yes')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender\n",
       "female    2381\n",
       "male      1249\n",
       "Name: Gender, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df.groupby([\"Gender\"])[\"Gender\"].count()\n",
    "\n",
    "df2.plot(kind=\"bar\", rot=0, figsize=(4,3), title=\"Gender Distribution\")\n",
    "df2.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Course\n",
       "Advertising and Marketing Management    220\n",
       "Agronomy                                173\n",
       "Animation and Multimedia Design         178\n",
       "Basic Education                         142\n",
       "Biofuel Production Technologies           9\n",
       "Name: Course, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df.groupby([\"Course\"])[\"Course\"].count()\n",
    "\n",
    "df2.plot(kind=\"barh\", rot=0, figsize=(5, 4), title=\"Course Distribution\")\n",
    "df2.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Target\n",
       "Dropout     1421\n",
       "Graduate    2209\n",
       "Name: Target, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df.groupby([\"Target\"])[\"Target\"].count()\n",
    "\n",
    "df2.plot(kind=\"bar\", rot=0, figsize=(4, 3), title=\"Target Distribution\")\n",
    "df2.head()"
   ]
  },
  {
   "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>Target</th>\n",
       "      <th>Dropout</th>\n",
       "      <th>Graduate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tuition fees up to date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
       "      <td>457</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yes</th>\n",
       "      <td>964</td>\n",
       "      <td>2180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Target                   Dropout  Graduate\n",
       "Tuition fees up to date                   \n",
       "no                           457        29\n",
       "yes                          964      2180"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df.groupby([\"Tuition fees up to date\", \"Target\"])[\"Target\"].count().unstack('Target')\n",
    "\n",
    "df2.plot(kind='barh', rot=0, figsize=(5, 3), stacked=False,\n",
    "         title=\"Dropout/Grad Distribution by Tuition Fees\")\n",
    "df2.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",
       "        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>Target</th>\n",
       "      <th>Dropout</th>\n",
       "      <th>Graduate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gender</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>720</td>\n",
       "      <td>1661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>701</td>\n",
       "      <td>548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Target  Dropout  Graduate\n",
       "Gender                   \n",
       "female      720      1661\n",
       "male        701       548"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df.groupby([\"Gender\", \"Target\"])[\"Target\"].count().unstack('Target')\n",
    "\n",
    "df2.plot(kind='barh', rot=0, figsize=(5,3), stacked=True, title=\"Dropout/Grad Distribution by Gender\")\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Dropout/Grad Distribution by Course'}, ylabel='Course'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df.groupby([\"Course\", \"Target\"])[\"Target\"].count().unstack('Target')\n",
    "\n",
    "df2.plot(kind='barh', rot=0, stacked=False, title=\"Dropout/Grad Distribution by Course\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/tg/t3qylscs4wl_v1vx1w0bpbzm0000gn/T/ipykernel_12049/2955970935.py:4: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  df2 = df.groupby(\"Course\")[\"Curricular units 2nd sem (grade)\",\"Curricular units 1st sem (grade)\"].mean()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x128f53990>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2 = df[[\"Course\",\n",
    "          \"Curricular units 1st sem (grade)\", \"Curricular units 2nd sem (grade)\"]]\n",
    "\n",
    "df2 = df.groupby(\"Course\")[\"Curricular units 2nd sem (grade)\",\"Curricular units 1st sem (grade)\"].mean()\n",
    "\n",
    "df2.plot(kind='barh', rot=0, stacked=False, figsize=(8, 10), title=\" Avg Course Grades by Semester\").legend(loc='center left',bbox_to_anchor=(1.0, 0.5))"
   ]
  }
 ],
 "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": "3.11.0"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "1a1af0ee75eeea9e2e1ee996c87e7a2b11a0bebd85af04bb136d915cefc0abce"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}