2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b4abee8d-4f10-41a6-a82f-de4c813862d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d8c0d25a-d46e-4aab-9725-319370e86376",
   "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>mid</th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q2</th>\n",
       "      <th>HW1</th>\n",
       "      <th>HW2</th>\n",
       "      <th>end</th>\n",
       "      <th>Final Grade</th>\n",
       "      <th>Grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>90.0</td>\n",
       "      <td>100</td>\n",
       "      <td>40.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>42.86</td>\n",
       "      <td>93.75</td>\n",
       "      <td>86.56</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>65.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>57.14</td>\n",
       "      <td>73.75</td>\n",
       "      <td>86.31</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>92.5</td>\n",
       "      <td>100</td>\n",
       "      <td>60.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>42.86</td>\n",
       "      <td>83.75</td>\n",
       "      <td>85.56</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97.5</td>\n",
       "      <td>100</td>\n",
       "      <td>40.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>76.19</td>\n",
       "      <td>70.00</td>\n",
       "      <td>83.75</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>70.0</td>\n",
       "      <td>95</td>\n",
       "      <td>75.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>38.09</td>\n",
       "      <td>95.00</td>\n",
       "      <td>80.75</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>10.0</td>\n",
       "      <td>85</td>\n",
       "      <td>67.5</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9.63</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>57.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>33.33</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.63</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>7.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>163 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       mid   Q1    Q2   HW1    HW2    end  Final Grade Grade\n",
       "0     90.0  100  40.0  70.0  42.86  93.75        86.56     A\n",
       "1    100.0  100  65.0  85.0  57.14  73.75        86.31     A\n",
       "2     92.5  100  60.0  80.0  42.86  83.75        85.56     A\n",
       "3     97.5  100  40.0  85.0  76.19  70.00        83.75     A\n",
       "4     70.0   95  75.0  85.0  38.09  95.00        80.75     A\n",
       "..     ...  ...   ...   ...    ...    ...          ...   ...\n",
       "158   10.0   85  67.5  20.0   4.05   0.00         9.63     F\n",
       "159    0.0    0  57.5  60.0  33.33   0.00         7.63     F\n",
       "160    7.5    0   0.0   0.0   0.00   0.00         3.00     F\n",
       "161    0.0    0   0.0   0.0   0.00   0.00         0.00     F\n",
       "162    0.0    0   0.0   0.0   0.00   0.00         0.00     F\n",
       "\n",
       "[163 rows x 8 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_excel('Grade_data.xlsx')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "667357d6-e01f-495a-8ff8-8a1e67c56a68",
   "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>mid</th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q2</th>\n",
       "      <th>HW1</th>\n",
       "      <th>HW2</th>\n",
       "      <th>end</th>\n",
       "      <th>Final Grade</th>\n",
       "      <th>Grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mid</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.364243</td>\n",
       "      <td>0.405941</td>\n",
       "      <td>0.414565</td>\n",
       "      <td>0.313209</td>\n",
       "      <td>0.799242</td>\n",
       "      <td>0.936046</td>\n",
       "      <td>-0.222346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q1</th>\n",
       "      <td>0.364243</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.270686</td>\n",
       "      <td>0.320933</td>\n",
       "      <td>0.347420</td>\n",
       "      <td>0.479135</td>\n",
       "      <td>0.534124</td>\n",
       "      <td>-0.000975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q2</th>\n",
       "      <td>0.405941</td>\n",
       "      <td>0.270686</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.317591</td>\n",
       "      <td>0.151497</td>\n",
       "      <td>0.357931</td>\n",
       "      <td>0.458432</td>\n",
       "      <td>-0.188155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HW1</th>\n",
       "      <td>0.414565</td>\n",
       "      <td>0.320933</td>\n",
       "      <td>0.317591</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.446609</td>\n",
       "      <td>0.413654</td>\n",
       "      <td>0.528293</td>\n",
       "      <td>-0.076735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HW2</th>\n",
       "      <td>0.313209</td>\n",
       "      <td>0.347420</td>\n",
       "      <td>0.151497</td>\n",
       "      <td>0.446609</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.355081</td>\n",
       "      <td>0.445505</td>\n",
       "      <td>-0.110564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>end</th>\n",
       "      <td>0.799242</td>\n",
       "      <td>0.479135</td>\n",
       "      <td>0.357931</td>\n",
       "      <td>0.413654</td>\n",
       "      <td>0.355081</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.934001</td>\n",
       "      <td>-0.167051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Final Grade</th>\n",
       "      <td>0.936046</td>\n",
       "      <td>0.534124</td>\n",
       "      <td>0.458432</td>\n",
       "      <td>0.528293</td>\n",
       "      <td>0.445505</td>\n",
       "      <td>0.934001</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.205600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grade</th>\n",
       "      <td>-0.222346</td>\n",
       "      <td>-0.000975</td>\n",
       "      <td>-0.188155</td>\n",
       "      <td>-0.076735</td>\n",
       "      <td>-0.110564</td>\n",
       "      <td>-0.167051</td>\n",
       "      <td>-0.205600</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  mid        Q1        Q2       HW1       HW2       end  \\\n",
       "mid          1.000000  0.364243  0.405941  0.414565  0.313209  0.799242   \n",
       "Q1           0.364243  1.000000  0.270686  0.320933  0.347420  0.479135   \n",
       "Q2           0.405941  0.270686  1.000000  0.317591  0.151497  0.357931   \n",
       "HW1          0.414565  0.320933  0.317591  1.000000  0.446609  0.413654   \n",
       "HW2          0.313209  0.347420  0.151497  0.446609  1.000000  0.355081   \n",
       "end          0.799242  0.479135  0.357931  0.413654  0.355081  1.000000   \n",
       "Final Grade  0.936046  0.534124  0.458432  0.528293  0.445505  0.934001   \n",
       "Grade       -0.222346 -0.000975 -0.188155 -0.076735 -0.110564 -0.167051   \n",
       "\n",
       "             Final Grade     Grade  \n",
       "mid             0.936046 -0.222346  \n",
       "Q1              0.534124 -0.000975  \n",
       "Q2              0.458432 -0.188155  \n",
       "HW1             0.528293 -0.076735  \n",
       "HW2             0.445505 -0.110564  \n",
       "end             0.934001 -0.167051  \n",
       "Final Grade     1.000000 -0.205600  \n",
       "Grade          -0.205600  1.000000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "le=LabelEncoder()\n",
    "df['Grade']=le.fit_transform(df['Grade'])\n",
    "correlation_matrix = df.corr()\n",
    "correlation_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "97998686-2763-493b-9c74-bda36ddb3f06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(correlation_matrix,annot=True)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}