exp2 (1).ipynb

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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import random \n",
    "import statistics"
   ]
  },
  {
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   "execution_count": null,
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       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>parental level of education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation course</th>\n",
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       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
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       "      <th>0</th>\n",
       "      <td>female</td>\n",
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       "      <td>72.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>74.0</td>\n",
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       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>69.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
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       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
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       "      <td>57.0</td>\n",
       "      <td>44.0</td>\n",
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       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>76.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>75.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>88.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>completed</td>\n",
       "      <td>59.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>female</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>68.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>77.0</td>\n",
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       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>female</td>\n",
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       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>77.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>86.0</td>\n",
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       "  </tbody>\n",
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       "<p>1000 rows × 8 columns</p>\n",
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      "text/plain": [
       "     gender race/ethnicity parental level of education         lunch  \\\n",
       "0    female        group B           bachelor's degree      standard   \n",
       "1    female        group C                some college      standard   \n",
       "2    female        group B             master's degree      standard   \n",
       "3      male        group A          associate's degree  free/reduced   \n",
       "4      male        group C                some college      standard   \n",
       "..      ...            ...                         ...           ...   \n",
       "995  female        group E             master's degree      standard   \n",
       "996    male        group C                 high school  free/reduced   \n",
       "997  female        group C                 high school  free/reduced   \n",
       "998  female        group D                some college      standard   \n",
       "999  female        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course  math score  reading score  writing score  \n",
       "0                      none        72.0           72.0           74.0  \n",
       "1                 completed        69.0           90.0           88.0  \n",
       "2                      none        90.0           95.0           93.0  \n",
       "3                      none         NaN           57.0           44.0  \n",
       "4                      none        76.0           78.0           75.0  \n",
       "..                      ...         ...            ...            ...  \n",
       "995               completed        88.0           99.0           95.0  \n",
       "996                    none        62.0           55.0           55.0  \n",
       "997               completed        59.0           71.0            NaN  \n",
       "998               completed        68.0           78.0           77.0  \n",
       "999                    none        77.0           86.0           86.0  \n",
       "\n",
       "[1000 rows x 8 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data=pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/StudentsPerformance.csv\")\n",
    "stud_data"
   ]
  },
  {
   "cell_type": "code",
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     "elapsed": 12,
     "status": "ok",
     "timestamp": 1652628865040,
     "user": {
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    },
    "id": "cWEfJ1dOGB6Q",
    "outputId": "72fe31c1-ca4a-480d-d4c9-9939f0485823"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 8 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   gender                       1000 non-null   object \n",
      " 1   race/ethnicity               1000 non-null   object \n",
      " 2   parental level of education  1000 non-null   object \n",
      " 3   lunch                        1000 non-null   object \n",
      " 4   test preparation course      1000 non-null   object \n",
      " 5   math score                   963 non-null    float64\n",
      " 6   reading score                956 non-null    float64\n",
      " 7   writing score                962 non-null    float64\n",
      "dtypes: float64(3), object(5)\n",
      "memory usage: 62.6+ KB\n"
     ]
    }
   ],
   "source": [
    "stud_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 11,
     "status": "ok",
     "timestamp": 1652628865042,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
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    },
    "id": "V4T6YoVPIMhi",
    "outputId": "5548d742-57c3-4a81-bee6-d45b5b3c9bc1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender                          0\n",
       "race/ethnicity                  0\n",
       "parental level of education     0\n",
       "lunch                           0\n",
       "test preparation course         0\n",
       "math score                     37\n",
       "reading score                  44\n",
       "writing score                  38\n",
       "dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "stud_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
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    },
    "executionInfo": {
     "elapsed": 11,
     "status": "ok",
     "timestamp": 1652628866004,
     "user": {
      "displayName": "Tejas Kamble",
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    },
    "id": "TZuuochtKTai",
    "outputId": "a8529886-ce6c-4e59-8e20-9087d2b8ceee"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1000, 8)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "stud_data.shape #rows and columns in dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 15,
     "status": "ok",
     "timestamp": 1652628866009,
     "user": {
      "displayName": "Tejas Kamble",
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    },
    "id": "GmMMo7S0SR5B",
    "outputId": "60ed0fbe-f7bc-43ea-aebf-52027e4f5f1d"
   },
   "outputs": [
    {
     "data": {
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       "8000"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data.size #total data cells in dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
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    "executionInfo": {
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    },
    "id": "NcO310Y2STMv",
    "outputId": "8e63c721-9b54-4abb-855e-4db58231ef65"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['gender', 'race/ethnicity', 'parental level of education', 'lunch',\n",
       "       'test preparation course', 'math score', 'reading score',\n",
       "       'writing score'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data.columns"
   ]
  },
  {
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       "      <td>78.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>71.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>88.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>male</td>\n",
       "      <td>group B</td>\n",
       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>40.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>male</td>\n",
       "      <td>group D</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>completed</td>\n",
       "      <td>64.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>38.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "  "
      ],
      "text/plain": [
       "   gender race/ethnicity parental level of education         lunch  \\\n",
       "0  female        group B           bachelor's degree      standard   \n",
       "1  female        group C                some college      standard   \n",
       "2  female        group B             master's degree      standard   \n",
       "3    male        group A          associate's degree  free/reduced   \n",
       "4    male        group C                some college      standard   \n",
       "5  female        group B          associate's degree      standard   \n",
       "6  female        group B                some college      standard   \n",
       "7    male        group B                some college  free/reduced   \n",
       "8    male        group D                 high school  free/reduced   \n",
       "9  female        group B                 high school  free/reduced   \n",
       "\n",
       "  test preparation course  math score  reading score  writing score  \n",
       "0                    none        72.0           72.0           74.0  \n",
       "1               completed        69.0           90.0           88.0  \n",
       "2                    none        90.0           95.0           93.0  \n",
       "3                    none         NaN           57.0           44.0  \n",
       "4                    none        76.0           78.0           75.0  \n",
       "5                    none        71.0           83.0           78.0  \n",
       "6               completed        88.0           95.0           92.0  \n",
       "7                    none        40.0           43.0           39.0  \n",
       "8               completed        64.0           64.0           67.0  \n",
       "9                    none        38.0           60.0           50.0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 13,
     "status": "ok",
     "timestamp": 1652628866012,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "w6CNMNMjS7cV",
    "outputId": "e917e811-7c1b-40ad-b109-6f53e63668d1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    72.000000\n",
       "1    69.000000\n",
       "2    90.000000\n",
       "3    66.127726\n",
       "4    76.000000\n",
       "Name: math score, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data[\"math score\"]=stud_data['math score'].replace(np.NaN,stud_data['math score'].mean())  #replacing nan value with mean\n",
    "stud_data['math score'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 588,
     "status": "ok",
     "timestamp": 1652628866589,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "Iih2Bzpbd8Ta",
    "outputId": "354be4ef-e13e-4646-c486-2d8ba4cd524b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     72.0\n",
       "1     90.0\n",
       "2     95.0\n",
       "3     57.0\n",
       "4     78.0\n",
       "5     83.0\n",
       "6     95.0\n",
       "7     43.0\n",
       "8     64.0\n",
       "9     60.0\n",
       "10    54.0\n",
       "11    52.0\n",
       "12    81.0\n",
       "13    72.0\n",
       "14    53.0\n",
       "15    75.0\n",
       "16    89.0\n",
       "17    32.0\n",
       "18    42.0\n",
       "19    58.0\n",
       "20    69.0\n",
       "21    75.0\n",
       "22    54.0\n",
       "23    73.0\n",
       "24    71.0\n",
       "25    74.0\n",
       "26    54.0\n",
       "27    69.0\n",
       "28    70.0\n",
       "29     NaN\n",
       "30    74.0\n",
       "31    65.0\n",
       "32    72.0\n",
       "33    42.0\n",
       "34    87.0\n",
       "35    81.0\n",
       "36    81.0\n",
       "37    64.0\n",
       "38    90.0\n",
       "39    56.0\n",
       "40     NaN\n",
       "41    73.0\n",
       "42    58.0\n",
       "43    65.0\n",
       "44    56.0\n",
       "45    54.0\n",
       "46    65.0\n",
       "47    71.0\n",
       "48    74.0\n",
       "49    84.0\n",
       "Name: reading score, dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data['reading score'].head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 11,
     "status": "ok",
     "timestamp": 1652628866590,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "8YwpI0ktXVcC",
    "outputId": "245a04e7-9c2b-4282-df8b-e7a7735b475c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     72.0\n",
       "1     90.0\n",
       "2     95.0\n",
       "3     57.0\n",
       "4     78.0\n",
       "5     83.0\n",
       "6     95.0\n",
       "7     43.0\n",
       "8     64.0\n",
       "9     60.0\n",
       "10    54.0\n",
       "11    52.0\n",
       "12    81.0\n",
       "13    72.0\n",
       "14    53.0\n",
       "15    75.0\n",
       "16    89.0\n",
       "17    32.0\n",
       "18    42.0\n",
       "19    58.0\n",
       "20    69.0\n",
       "21    75.0\n",
       "22    54.0\n",
       "23    73.0\n",
       "24    71.0\n",
       "25    74.0\n",
       "26    54.0\n",
       "27    69.0\n",
       "28    70.0\n",
       "29    70.0\n",
       "30    74.0\n",
       "31    65.0\n",
       "32    72.0\n",
       "33    42.0\n",
       "34    87.0\n",
       "35    81.0\n",
       "36    81.0\n",
       "37    64.0\n",
       "38    90.0\n",
       "39    56.0\n",
       "40    70.0\n",
       "41    73.0\n",
       "42    58.0\n",
       "43    65.0\n",
       "44    56.0\n",
       "45    54.0\n",
       "46    65.0\n",
       "47    71.0\n",
       "48    74.0\n",
       "49    84.0\n",
       "Name: reading score, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data['reading score']=stud_data['reading score'].replace(np.NaN,stud_data['reading score'].median())\n",
    "stud_data['reading score'].head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1652628866591,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "fjKJiWnSecT6",
    "outputId": "3c27cb71-9b36-4fd0-a252-3ac49b3fbf49"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     74.0\n",
       "1     88.0\n",
       "2     93.0\n",
       "3     44.0\n",
       "4     75.0\n",
       "5     78.0\n",
       "6     92.0\n",
       "7     39.0\n",
       "8     67.0\n",
       "9     50.0\n",
       "10    52.0\n",
       "11    43.0\n",
       "12    73.0\n",
       "13    70.0\n",
       "14    58.0\n",
       "15    78.0\n",
       "16    86.0\n",
       "17     NaN\n",
       "18    46.0\n",
       "19    61.0\n",
       "20    63.0\n",
       "21    70.0\n",
       "22    53.0\n",
       "23    73.0\n",
       "24    80.0\n",
       "25    72.0\n",
       "26    55.0\n",
       "27    75.0\n",
       "28    65.0\n",
       "29     NaN\n",
       "30    74.0\n",
       "31    61.0\n",
       "32    65.0\n",
       "33    38.0\n",
       "34    82.0\n",
       "35    79.0\n",
       "36    83.0\n",
       "37    59.0\n",
       "38    88.0\n",
       "39    57.0\n",
       "40    54.0\n",
       "41    68.0\n",
       "42    65.0\n",
       "43    66.0\n",
       "44    54.0\n",
       "45    57.0\n",
       "46    62.0\n",
       "47    76.0\n",
       "48    76.0\n",
       "49    82.0\n",
       "Name: writing score, dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "stud_data['writing score'].head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1652628866592,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "0KltAFe6XqzX",
    "outputId": "6adb8bb1-ca60-4c49-9c08-163a38d03572"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     74.0\n",
       "1     88.0\n",
       "2     93.0\n",
       "3     44.0\n",
       "4     75.0\n",
       "5     78.0\n",
       "6     92.0\n",
       "7     39.0\n",
       "8     67.0\n",
       "9     50.0\n",
       "10    52.0\n",
       "11    43.0\n",
       "12    73.0\n",
       "13    70.0\n",
       "14    58.0\n",
       "15    78.0\n",
       "16    86.0\n",
       "17    74.0\n",
       "18    46.0\n",
       "19    61.0\n",
       "20    63.0\n",
       "21    70.0\n",
       "22    53.0\n",
       "23    73.0\n",
       "24    80.0\n",
       "25    72.0\n",
       "26    55.0\n",
       "27    75.0\n",
       "28    65.0\n",
       "29    74.0\n",
       "30    74.0\n",
       "31    61.0\n",
       "32    65.0\n",
       "33    38.0\n",
       "34    82.0\n",
       "35    79.0\n",
       "36    83.0\n",
       "37    59.0\n",
       "38    88.0\n",
       "39    57.0\n",
       "40    54.0\n",
       "41    68.0\n",
       "42    65.0\n",
       "43    66.0\n",
       "44    54.0\n",
       "45    57.0\n",
       "46    62.0\n",
       "47    76.0\n",
       "48    76.0\n",
       "49    82.0\n",
       "Name: writing score, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data['writing score']=stud_data['writing score'].replace(np.NaN,statistics.mode(stud_data['writing score']))\n",
    "stud_data['writing score'].head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 424
    },
    "executionInfo": {
     "elapsed": 12,
     "status": "ok",
     "timestamp": 1652628867559,
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    "id": "VVdxySUjaJgB",
    "outputId": "39c4070b-fd0c-4118-f7ab-59e7b108b34e"
   },
   "outputs": [
    {
     "data": {
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       "      <th>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>parental level of education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation course</th>\n",
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       "      <td>group B</td>\n",
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       "      <th>1</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>90.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>76.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>75.0</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>995</th>\n",
       "      <td>female</td>\n",
       "      <td>group E</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>88.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>completed</td>\n",
       "      <td>59.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>female</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>68.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>female</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>77.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 8 columns</p>\n",
       "</div>\n",
       "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3eb77e04-4e99-4fb4-9963-43976ebe0c5e')\"\n",
       "              title=\"Convert this dataframe to an interactive table.\"\n",
       "              style=\"display:none;\">\n",
       "        \n",
       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
       "       width=\"24px\">\n",
       "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
       "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
       "  </svg>\n",
       "      </button>\n",
       "      \n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      flex-wrap:wrap;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
       "      cursor: pointer;\n",
       "      display: none;\n",
       "      fill: #1967D2;\n",
       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "      fill: #174EA6;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "      <script>\n",
       "        const buttonEl =\n",
       "          document.querySelector('#df-3eb77e04-4e99-4fb4-9963-43976ebe0c5e button.colab-df-convert');\n",
       "        buttonEl.style.display =\n",
       "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "        async function convertToInteractive(key) {\n",
       "          const element = document.querySelector('#df-3eb77e04-4e99-4fb4-9963-43976ebe0c5e');\n",
       "          const dataTable =\n",
       "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                     [key], {});\n",
       "          if (!dataTable) return;\n",
       "\n",
       "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "            + ' to learn more about interactive tables.';\n",
       "          element.innerHTML = '';\n",
       "          dataTable['output_type'] = 'display_data';\n",
       "          await google.colab.output.renderOutput(dataTable, element);\n",
       "          const docLink = document.createElement('div');\n",
       "          docLink.innerHTML = docLinkHtml;\n",
       "          element.appendChild(docLink);\n",
       "        }\n",
       "      </script>\n",
       "    </div>\n",
       "  </div>\n",
       "  "
      ],
      "text/plain": [
       "     gender race/ethnicity parental level of education         lunch  \\\n",
       "0    female        group B           bachelor's degree      standard   \n",
       "1    female        group C                some college      standard   \n",
       "2    female        group B             master's degree      standard   \n",
       "3      male        group A          associate's degree  free/reduced   \n",
       "4      male        group C                some college      standard   \n",
       "..      ...            ...                         ...           ...   \n",
       "995  female        group E             master's degree      standard   \n",
       "996    male        group C                 high school  free/reduced   \n",
       "997  female        group C                 high school  free/reduced   \n",
       "998  female        group D                some college      standard   \n",
       "999  female        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course  math score  reading score  writing score  \n",
       "0                      none        72.0           72.0           74.0  \n",
       "1                 completed        69.0           90.0           88.0  \n",
       "2                      none        90.0           95.0           93.0  \n",
       "3                      none         NaN           57.0           44.0  \n",
       "4                      none        76.0           78.0           75.0  \n",
       "..                      ...         ...            ...            ...  \n",
       "995               completed        88.0           99.0           95.0  \n",
       "996                    none        62.0           55.0           55.0  \n",
       "997               completed        59.0           71.0            NaN  \n",
       "998               completed        68.0           78.0           77.0  \n",
       "999                    none        77.0           86.0           86.0  \n",
       "\n",
       "[1000 rows x 8 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using fill na drop na\n",
    "df1=pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/StudentsPerformance.csv\")\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1652628868229,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "KRhDIglReIOM",
    "outputId": "6dee9124-321d-4c45-a9d3-fe251f604e6c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender                          0\n",
       "race/ethnicity                  0\n",
       "parental level of education     0\n",
       "lunch                           0\n",
       "test preparation course         0\n",
       "math score                     37\n",
       "reading score                  44\n",
       "writing score                  38\n",
       "dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0Sz8iGejfBhZ"
   },
   "outputs": [],
   "source": [
    "df1.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 424
    },
    "executionInfo": {
     "elapsed": 16,
     "status": "ok",
     "timestamp": 1652628869103,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "LsNITNU_fGdE",
    "outputId": "0e65633b-0b69-4c87-81f3-bbf7b706c792"
   },
   "outputs": [
    {
     "data": {
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       "      <th>2</th>\n",
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       "      <td>standard</td>\n",
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       "    <tr>\n",
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       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>76.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>75.0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>71.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>78.0</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",
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       "      <th>994</th>\n",
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       "      <td>standard</td>\n",
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       "      <td>63.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>62.0</td>\n",
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       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>female</td>\n",
       "      <td>group E</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>88.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
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       "      <th>996</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
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       "      <td>none</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>55.0</td>\n",
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       "      <th>998</th>\n",
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       "      <td>78.0</td>\n",
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       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>77.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>885 rows × 8 columns</p>\n",
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       "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-48c4c90f-5fa0-4f39-b27b-9dc5dbfbeddf')\"\n",
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       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
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       "      background-color: #434B5C;\n",
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       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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       "      <script>\n",
       "        const buttonEl =\n",
       "          document.querySelector('#df-48c4c90f-5fa0-4f39-b27b-9dc5dbfbeddf button.colab-df-convert');\n",
       "        buttonEl.style.display =\n",
       "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "        async function convertToInteractive(key) {\n",
       "          const element = document.querySelector('#df-48c4c90f-5fa0-4f39-b27b-9dc5dbfbeddf');\n",
       "          const dataTable =\n",
       "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                     [key], {});\n",
       "          if (!dataTable) return;\n",
       "\n",
       "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "            + ' to learn more about interactive tables.';\n",
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       "  "
      ],
      "text/plain": [
       "     gender race/ethnicity parental level of education         lunch  \\\n",
       "0    female        group B           bachelor's degree      standard   \n",
       "1    female        group C                some college      standard   \n",
       "2    female        group B             master's degree      standard   \n",
       "4      male        group C                some college      standard   \n",
       "5    female        group B          associate's degree      standard   \n",
       "..      ...            ...                         ...           ...   \n",
       "994    male        group A                 high school      standard   \n",
       "995  female        group E             master's degree      standard   \n",
       "996    male        group C                 high school  free/reduced   \n",
       "998  female        group D                some college      standard   \n",
       "999  female        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course  math score  reading score  writing score  \n",
       "0                      none        72.0           72.0           74.0  \n",
       "1                 completed        69.0           90.0           88.0  \n",
       "2                      none        90.0           95.0           93.0  \n",
       "4                      none        76.0           78.0           75.0  \n",
       "5                      none        71.0           83.0           78.0  \n",
       "..                      ...         ...            ...            ...  \n",
       "994                    none        63.0           63.0           62.0  \n",
       "995               completed        88.0           99.0           95.0  \n",
       "996                    none        62.0           55.0           55.0  \n",
       "998               completed        68.0           78.0           77.0  \n",
       "999                    none        77.0           86.0           86.0  \n",
       "\n",
       "[885 rows x 8 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1  #dropped the whole row having null value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "executionInfo": {
     "elapsed": 15,
     "status": "ok",
     "timestamp": 1652628869105,
     "user": {
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    },
    "id": "KJdltKBefIkP",
    "outputId": "61cae39d-101f-4a5c-e6de-59ab7777f77a"
   },
   "outputs": [
    {
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      "text/plain": [
       "   gender race/ethnicity parental level of education         lunch  \\\n",
       "0  female        group B           bachelor's degree      standard   \n",
       "1  female        group C                some college      standard   \n",
       "2  female        group B             master's degree      standard   \n",
       "3    male        group A          associate's degree  free/reduced   \n",
       "4    male        group C                some college      standard   \n",
       "\n",
       "  test preparation course  math score  reading score  writing score  \n",
       "0                    none        72.0           72.0           74.0  \n",
       "1               completed        69.0           90.0           88.0  \n",
       "2                    none        90.0           95.0           93.0  \n",
       "3                    none         NaN           57.0           44.0  \n",
       "4                    none        76.0           78.0           75.0  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#by using fillna\n",
    "\n",
    "stud_per=pd.read_csv('/content/drive/MyDrive/Colab Notebooks/StudentsPerformance.csv')\n",
    "stud_per.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 5,
     "status": "ok",
     "timestamp": 1652628869764,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "3CDAhW6KfalL",
    "outputId": "e36ebbba-6f61-4d96-cdc6-0318ba0f5608"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender                          0\n",
       "race/ethnicity                  0\n",
       "parental level of education     0\n",
       "lunch                           0\n",
       "test preparation course         0\n",
       "math score                      0\n",
       "reading score                  44\n",
       "writing score                  38\n",
       "dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_per['math score']=stud_per['math score'].fillna(0)\n",
    "stud_per.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 5,
     "status": "ok",
     "timestamp": 1652628869765,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "9-mTBHxvfzb9",
    "outputId": "ca98fa53-0199-47c5-82b1-98b79016d381"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      72.0\n",
       "1      90.0\n",
       "2      95.0\n",
       "3      57.0\n",
       "4      78.0\n",
       "       ... \n",
       "995    99.0\n",
       "996    55.0\n",
       "997    71.0\n",
       "998    78.0\n",
       "999    86.0\n",
       "Name: reading score, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_per['reading score']=stud_per['reading score'].fillna(method='ffill')\n",
    "stud_per['reading score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 7,
     "status": "ok",
     "timestamp": 1652628870223,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "bqhOGJI_gXPr",
    "outputId": "f46281be-3a9d-4ec2-f7a0-6e9e6ea59ec6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    72.0\n",
       "1    90.0\n",
       "2    95.0\n",
       "3    57.0\n",
       "4    78.0\n",
       "Name: reading score, dtype: float64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_per['reading score']=stud_per['reading score'].interpolate(method='linear',limit_direction='forward',axis=0)\n",
    "stud_per['reading score'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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    },
    "executionInfo": {
     "elapsed": 7,
     "status": "ok",
     "timestamp": 1652628870224,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
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    "id": "ujT_tLDfhJQH",
    "outputId": "cdf44702-7671-427e-b8c2-eda9aafff8db"
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    {
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
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       "      <td>none</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>55.0</td>\n",
       "      <td>55.0</td>\n",
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       "      <td>free/reduced</td>\n",
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       "<p>1000 rows × 8 columns</p>\n",
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       "     gender race/ethnicity parental level of education         lunch  \\\n",
       "0    female        group B           bachelor's degree      standard   \n",
       "1    female        group C                some college      standard   \n",
       "2    female        group B             master's degree      standard   \n",
       "3      male        group A          associate's degree  free/reduced   \n",
       "4      male        group C                some college      standard   \n",
       "..      ...            ...                         ...           ...   \n",
       "995  female        group E             master's degree      standard   \n",
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       "998  female        group D                some college      standard   \n",
       "999  female        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course  math score  reading score  writing score  \n",
       "0                      none   72.000000           72.0           74.0  \n",
       "1                 completed   69.000000           90.0           88.0  \n",
       "2                      none   90.000000           95.0           93.0  \n",
       "3                      none   66.127726           57.0           44.0  \n",
       "4                      none   76.000000           78.0           75.0  \n",
       "..                      ...         ...            ...            ...  \n",
       "995               completed   88.000000           99.0           95.0  \n",
       "996                    none   62.000000           55.0           55.0  \n",
       "997               completed   59.000000           71.0           74.0  \n",
       "998               completed   68.000000           78.0           77.0  \n",
       "999                    none   77.000000           86.0           86.0  \n",
       "\n",
       "[1000 rows x 8 columns]"
      ]
     },
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      "text/plain": [
       "     gender race/ethnicity parental level of education         lunch  \\\n",
       "0    female        group B           bachelor's degree      standard   \n",
       "1    female        group C                some college      standard   \n",
       "2    female        group B             master's degree      standard   \n",
       "3      male        group A          associate's degree  free/reduced   \n",
       "4      male        group C                some college      standard   \n",
       "..      ...            ...                         ...           ...   \n",
       "995  female        group E             master's degree      standard   \n",
       "996    male        group C                 high school  free/reduced   \n",
       "997  female        group C                 high school  free/reduced   \n",
       "998  female        group D                some college      standard   \n",
       "999  female        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course  math score  reading score  writing score  \n",
       "0                      none   72.000000           72.0           74.0  \n",
       "1                 completed   69.000000           90.0           88.0  \n",
       "2                      none   90.000000           95.0           93.0  \n",
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       "4                      none   76.000000           78.0           75.0  \n",
       "..                      ...         ...            ...            ...  \n",
       "995               completed   88.000000           99.0           95.0  \n",
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       "997               completed   59.000000           71.0           74.0  \n",
       "998               completed   68.000000           78.0           77.0  \n",
       "999                    none   77.000000           86.0           86.0  \n",
       "\n",
       "[1000 rows x 8 columns]"
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     "execution_count": 55,
     "metadata": {},
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    }
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    {
     "data": {
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       "0      0\n",
       "1      0\n",
       "2      0\n",
       "3      1\n",
       "4      1\n",
       "      ..\n",
       "995    0\n",
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       "999    0\n",
       "Name: gender, Length: 1000, dtype: int64"
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     "execution_count": 56,
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   ],
   "source": [
    "\n",
    "stud_data['gender']=np.where(stud_data['gender']=='female',0,1)\n",
    "stud_data['gender']\n"
   ]
  },
  {
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       "      <td>90.000000</td>\n",
       "      <td>95.0</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>66.127726</td>\n",
       "      <td>57.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>78.0</td>\n",
       "      <td>75.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
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       "      <td>group E</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>99.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>55.0</td>\n",
       "      <td>55.0</td>\n",
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       "    <tr>\n",
       "      <th>997</th>\n",
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       "      <td>completed</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>71.0</td>\n",
       "      <td>74.0</td>\n",
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       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>0</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>78.0</td>\n",
       "      <td>77.0</td>\n",
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       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>0</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>86.0</td>\n",
       "      <td>86.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 8 columns</p>\n",
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       "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                     [key], {});\n",
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       "\n",
       "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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       "  </div>\n",
       "  "
      ],
      "text/plain": [
       "     gender race/ethnicity parental level of education         lunch  \\\n",
       "0         0        group B           bachelor's degree      standard   \n",
       "1         0        group C                some college      standard   \n",
       "2         0        group B             master's degree      standard   \n",
       "3         1        group A          associate's degree  free/reduced   \n",
       "4         1        group C                some college      standard   \n",
       "..      ...            ...                         ...           ...   \n",
       "995       0        group E             master's degree      standard   \n",
       "996       1        group C                 high school  free/reduced   \n",
       "997       0        group C                 high school  free/reduced   \n",
       "998       0        group D                some college      standard   \n",
       "999       0        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course  math score  reading score  writing score  \n",
       "0                      none   72.000000           72.0           74.0  \n",
       "1                 completed   69.000000           90.0           88.0  \n",
       "2                      none   90.000000           95.0           93.0  \n",
       "3                      none   66.127726           57.0           44.0  \n",
       "4                      none   76.000000           78.0           75.0  \n",
       "..                      ...         ...            ...            ...  \n",
       "995               completed   88.000000           99.0           95.0  \n",
       "996                    none   62.000000           55.0           55.0  \n",
       "997               completed   59.000000           71.0           74.0  \n",
       "998               completed   68.000000           78.0           77.0  \n",
       "999                    none   77.000000           86.0           86.0  \n",
       "\n",
       "[1000 rows x 8 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stud_data"
   ]
  },
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       "     gender  math score  reading score  writing score\n",
       "0         0   72.000000           72.0           74.0\n",
       "1         0   69.000000           90.0           88.0\n",
       "2         0   90.000000           95.0           93.0\n",
       "3         1   66.127726           57.0           44.0\n",
       "4         1   76.000000           78.0           75.0\n",
       "..      ...         ...            ...            ...\n",
       "995       0   88.000000           99.0           95.0\n",
       "996       1   62.000000           55.0           55.0\n",
       "997       0   59.000000           71.0           74.0\n",
       "998       0   68.000000           78.0           77.0\n",
       "999       0   77.000000           86.0           86.0\n",
       "\n",
       "[1000 rows x 4 columns]"
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     },
     "execution_count": 58,
     "metadata": {},
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   ],
   "source": [
    "#normalizing the data\n",
    "\n",
    "stud_data=stud_data.drop(['race/ethnicity', 'parental level of education',\t'lunch', 'test preparation course'],axis=1)\n",
    "stud_data\n"
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       "      <td>0.661277</td>\n",
       "      <td>0.481928</td>\n",
       "      <td>0.377778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.760000</td>\n",
       "      <td>0.734940</td>\n",
       "      <td>0.722222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>0.987952</td>\n",
       "      <td>0.944444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.620000</td>\n",
       "      <td>0.457831</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.590000</td>\n",
       "      <td>0.650602</td>\n",
       "      <td>0.711111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>0.734940</td>\n",
       "      <td>0.744444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.770000</td>\n",
       "      <td>0.831325</td>\n",
       "      <td>0.844444</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 4 columns</p>\n",
       "</div>\n",
       "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aed071ee-ec3f-4371-908a-5522bd873649')\"\n",
       "              title=\"Convert this dataframe to an interactive table.\"\n",
       "              style=\"display:none;\">\n",
       "        \n",
       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
       "       width=\"24px\">\n",
       "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
       "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
       "  </svg>\n",
       "      </button>\n",
       "      \n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      flex-wrap:wrap;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
       "      cursor: pointer;\n",
       "      display: none;\n",
       "      fill: #1967D2;\n",
       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "      fill: #174EA6;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "      <script>\n",
       "        const buttonEl =\n",
       "          document.querySelector('#df-aed071ee-ec3f-4371-908a-5522bd873649 button.colab-df-convert');\n",
       "        buttonEl.style.display =\n",
       "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "        async function convertToInteractive(key) {\n",
       "          const element = document.querySelector('#df-aed071ee-ec3f-4371-908a-5522bd873649');\n",
       "          const dataTable =\n",
       "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                     [key], {});\n",
       "          if (!dataTable) return;\n",
       "\n",
       "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "            + ' to learn more about interactive tables.';\n",
       "          element.innerHTML = '';\n",
       "          dataTable['output_type'] = 'display_data';\n",
       "          await google.colab.output.renderOutput(dataTable, element);\n",
       "          const docLink = document.createElement('div');\n",
       "          docLink.innerHTML = docLinkHtml;\n",
       "          element.appendChild(docLink);\n",
       "        }\n",
       "      </script>\n",
       "    </div>\n",
       "  </div>\n",
       "  "
      ],
      "text/plain": [
       "     gender  math score  reading score  writing score\n",
       "0       0.0    0.720000       0.662651       0.711111\n",
       "1       0.0    0.690000       0.879518       0.866667\n",
       "2       0.0    0.900000       0.939759       0.922222\n",
       "3       1.0    0.661277       0.481928       0.377778\n",
       "4       1.0    0.760000       0.734940       0.722222\n",
       "..      ...         ...            ...            ...\n",
       "995     0.0    0.880000       0.987952       0.944444\n",
       "996     1.0    0.620000       0.457831       0.500000\n",
       "997     0.0    0.590000       0.650602       0.711111\n",
       "998     0.0    0.680000       0.734940       0.744444\n",
       "999     0.0    0.770000       0.831325       0.844444\n",
       "\n",
       "[1000 rows x 4 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#scaling\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler=MinMaxScaler(feature_range=(0,1))\n",
    "\n",
    "stud_data=pd.DataFrame(scaler.fit_transform(stud_data), columns=stud_data.columns)\n",
    "stud_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "executionInfo": {
     "elapsed": 966,
     "status": "ok",
     "timestamp": 1652628884122,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "3TKYB9G18baP",
    "outputId": "028752eb-3534-4674-b2ab-8c888d5766e7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f38f663ab10>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#using boxplot\n",
    "cols=['math score','reading score','writing score']\n",
    "stud_data.boxplot(cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 143
    },
    "executionInfo": {
     "elapsed": 443,
     "status": "ok",
     "timestamp": 1652629473454,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "IU-XgF2mWaOa",
    "outputId": "49db9ac6-93cf-40ee-f88f-d909596bff1c"
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'stud_data' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-c5afc78e5ba3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mstud_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mstud_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'math score'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m<\u001b[0m\u001b[0;36m25\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'stud_data' is not defined"
     ]
    }
   ],
   "source": [
    "stud_data[stud_data['math score']<25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 81
    },
    "executionInfo": {
     "elapsed": 458,
     "status": "ok",
     "timestamp": 1652629449655,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "965LX_OZWmwQ",
    "outputId": "94c5b5a7-5091-4226-a71d-ccace203fb1f"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"df-684ce956-6cba-4004-b936-ca3d05f29e49\">\n",
       "    <div class=\"colab-df-container\">\n",
       "      <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>gender</th>\n",
       "      <th>math score</th>\n",
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      "text/plain": [
       "    gender  math score  reading score  writing score\n",
       "59       0         0.0           17.0           10.0"
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       "     gender  math score  reading score  writing score\n",
       "59        0         0.0           17.0           10.0\n",
       "327       1        28.0           23.0           19.0\n",
       "596       1        30.0           24.0           15.0"
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#importing matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "#using scatterplot \n",
    "scat=plt.subplot()\n",
    "scat.scatter(stud_data['reading score'],stud_data['writing score'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0KqLuaT4acak"
   },
   "outputs": [],
   "source": [
    "scat.set_xlabel('reading score')\n",
    "scat.set_ylabel('Writing score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 431,
     "status": "ok",
     "timestamp": 1652630641053,
     "user": {
      "displayName": "Tejas Kamble",
      "userId": "12387425670622637522"
     },
     "user_tz": -330
    },
    "id": "pV6BdHv1bicu",
    "outputId": "329eda3c-1579-456d-8129-e2e09195006e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([59]),)"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where((stud_data['reading score']<20)&(stud_data['writing score']>1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "nn14_LLugDTr"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "exp2.ipynb",
   "provenance": []
  },
  "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}