cleaning_data.ipynb

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  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "308bfed7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e6f33b6f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>66.0</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>94.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Dr. Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>67.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>97.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Bryan Miranda</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Sheena Carter</td>\n",
       "      <td>F</td>\n",
       "      <td>11th</td>\n",
       "      <td>82.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Nicole Baker</td>\n",
       "      <td>F</td>\n",
       "      <td>12th</td>\n",
       "      <td>96.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Student ID       student_name gender grade  reading_score  math_score\n",
       "0           0       Paul Bradley      M   9th           66.0        79.0\n",
       "1           1       Victor Smith      M  12th           94.0        61.0\n",
       "2           2    Kevin Rodriguez      M  12th            NaN        60.0\n",
       "3           3  Dr. Richard Scott      M  12th           67.0        58.0\n",
       "4           4         Bonnie Ray      F   9th           97.0        84.0\n",
       "5           5      Bryan Miranda      M   9th           94.0         NaN\n",
       "6           6      Sheena Carter      F  11th           82.0        80.0\n",
       "7           7       Nicole Baker      F  12th           96.0        69.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Files to load\n",
    "file_to_load = \"Resources/missing_grades.csv\"\n",
    "\n",
    "# Read the CSV into a DataFrame\n",
    "missing_grade_df = pd.read_csv(file_to_load)\n",
    "missing_grade_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b657a53b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>66.0</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>94.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Dr. Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>67.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>97.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Sheena Carter</td>\n",
       "      <td>F</td>\n",
       "      <td>11th</td>\n",
       "      <td>82.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Nicole Baker</td>\n",
       "      <td>F</td>\n",
       "      <td>12th</td>\n",
       "      <td>96.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID       student_name gender grade  reading_score  math_score\n",
       "0           0       Paul Bradley      M   9th           66.0        79.0\n",
       "1           1       Victor Smith      M  12th           94.0        61.0\n",
       "3           3  Dr. Richard Scott      M  12th           67.0        58.0\n",
       "4           4         Bonnie Ray      F   9th           97.0        84.0\n",
       "6           6      Sheena Carter      F  11th           82.0        80.0\n",
       "7           7       Nicole Baker      F  12th           96.0        69.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop the NaNs.\n",
    "missing_grade_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4bc833b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill in the empty rows with \"85\".\n",
    "missing_grade_df.fillna(85)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2189d98",
   "metadata": {},
   "outputs": [],
   "source": []
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   "cell_type": "code",
   "execution_count": null,
   "id": "7c10ae35",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34819c77",
   "metadata": {},
   "outputs": [],
   "source": []
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