{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":12596975,"sourceType":"datasetVersion","datasetId":7956323}],"dockerImageVersionId":31090,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:51:11.132969Z","iopub.execute_input":"2025-08-12T06:51:11.133185Z","iopub.status.idle":"2025-08-12T06:51:12.924665Z","shell.execute_reply.started":"2025-08-12T06:51:11.133167Z","shell.execute_reply":"2025-08-12T06:51:12.923939Z"}},"outputs":[{"name":"stdout","text":"/kaggle/input/exploring-mental-health-data/train.csv\n/kaggle/input/exploring-mental-health-data/test.csv\n","output_type":"stream"}],"execution_count":1},{"cell_type":"code","source":"df=pd.read_csv('/kaggle/input/exploring-mental-health-data/test.csv')\ndf","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:51:12.925983Z","iopub.execute_input":"2025-08-12T06:51:12.926280Z","iopub.status.idle":"2025-08-12T06:51:13.397648Z","shell.execute_reply.started":"2025-08-12T06:51:12.926261Z","shell.execute_reply":"2025-08-12T06:51:13.396780Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[{"name":"stderr","text":"/usr/local/lib/python3.11/dist-packages/pandas/io/formats/format.py:1458: RuntimeWarning: invalid value encountered in greater\n  has_large_values = (abs_vals > 1e6).any()\n/usr/local/lib/python3.11/dist-packages/pandas/io/formats/format.py:1459: RuntimeWarning: invalid value encountered in less\n  has_small_values = ((abs_vals < 10 ** (-self.digits)) & (abs_vals > 0)).any()\n/usr/local/lib/python3.11/dist-packages/pandas/io/formats/format.py:1459: RuntimeWarning: invalid value encountered in greater\n  has_small_values = ((abs_vals < 10 ** (-self.digits)) & (abs_vals > 0)).any()\n","output_type":"stream"},{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"           id     Name  Gender   Age           City  \\\n0      140700   Shivam    Male  53.0  Visakhapatnam   \n1      140701    Sanya  Female  58.0        Kolkata   \n2      140702     Yash    Male  53.0         Jaipur   \n3      140703   Nalini  Female  23.0         Rajkot   \n4      140704  Shaurya    Male  47.0         Kalyan   \n...       ...      ...     ...   ...            ...   \n93795  234495     Zoya  Female  49.0         Jaipur   \n93796  234496    Shlok    Male  29.0      Ahmedabad   \n93797  234497    Rishi    Male  24.0  Visakhapatnam   \n93798  234498   Eshita  Female  23.0         Kalyan   \n93799  234499    Gauri  Female  43.0       Varanasi   \n\n      Working Professional or Student              Profession  \\\n0                Working Professional                   Judge   \n1                Working Professional  Educational Consultant   \n2                Working Professional                 Teacher   \n3                             Student                     NaN   \n4                Working Professional                 Teacher   \n...                               ...                     ...   \n93795            Working Professional                   Pilot   \n93796            Working Professional                   Pilot   \n93797                         Student                     NaN   \n93798            Working Professional       Marketing Manager   \n93799            Working Professional  Educational Consultant   \n\n       Academic Pressure  Work Pressure  CGPA  Study Satisfaction  \\\n0                    NaN            2.0   NaN                 NaN   \n1                    NaN            2.0   NaN                 NaN   \n2                    NaN            4.0   NaN                 NaN   \n3                    5.0            NaN  6.84                 1.0   \n4                    NaN            5.0   NaN                 NaN   \n...                  ...            ...   ...                 ...   \n93795                NaN            3.0   NaN                 NaN   \n93796                NaN            5.0   NaN                 NaN   \n93797                1.0            NaN  7.51                 4.0   \n93798                NaN            4.0   NaN                 NaN   \n93799                NaN            5.0   NaN                 NaN   \n\n       Job Satisfaction     Sleep Duration Dietary Habits  Degree  \\\n0                   5.0  Less than 5 hours       Moderate     LLB   \n1                   4.0  Less than 5 hours       Moderate    B.Ed   \n2                   1.0          7-8 hours       Moderate  B.Arch   \n3                   NaN  More than 8 hours       Moderate     BSc   \n4                   5.0          7-8 hours       Moderate     BCA   \n...                 ...                ...            ...     ...   \n93795               5.0  Less than 5 hours       Moderate     BSc   \n93796               1.0          7-8 hours       Moderate      BE   \n93797               NaN          7-8 hours       Moderate  B.Tech   \n93798               2.0          5-6 hours        Healthy      BA   \n93799               2.0  More than 8 hours        Healthy    B.Ed   \n\n      Have you ever had suicidal thoughts ?  Work/Study Hours  \\\n0                                        No               9.0   \n1                                        No               6.0   \n2                                       Yes              12.0   \n3                                       Yes              10.0   \n4                                       Yes               3.0   \n...                                     ...               ...   \n93795                                   Yes               2.0   \n93796                                   Yes              11.0   \n93797                                    No               7.0   \n93798                                   Yes               7.0   \n93799                                    No              11.0   \n\n       Financial Stress Family History of Mental Illness  \n0                   3.0                              Yes  \n1                   4.0                               No  \n2                   4.0                               No  \n3                   4.0                               No  \n4                   4.0                               No  \n...                 ...                              ...  \n93795               2.0                              Yes  \n93796               3.0                              Yes  \n93797               1.0                               No  \n93798               5.0                              Yes  \n93799               2.0                               No  \n\n[93800 rows x 19 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>Name</th>\n      <th>Gender</th>\n      <th>Age</th>\n      <th>City</th>\n      <th>Working Professional or Student</th>\n      <th>Profession</th>\n      <th>Academic Pressure</th>\n      <th>Work Pressure</th>\n      <th>CGPA</th>\n      <th>Study Satisfaction</th>\n      <th>Job Satisfaction</th>\n      <th>Sleep Duration</th>\n      <th>Dietary Habits</th>\n      <th>Degree</th>\n      <th>Have you ever had suicidal thoughts ?</th>\n      <th>Work/Study Hours</th>\n      <th>Financial Stress</th>\n      <th>Family History of Mental Illness</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>140700</td>\n      <td>Shivam</td>\n      <td>Male</td>\n      <td>53.0</td>\n      <td>Visakhapatnam</td>\n      <td>Working Professional</td>\n      <td>Judge</td>\n      <td>NaN</td>\n      <td>2.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>Less than 5 hours</td>\n      <td>Moderate</td>\n      <td>LLB</td>\n      <td>No</td>\n      <td>9.0</td>\n      <td>3.0</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>140701</td>\n      <td>Sanya</td>\n      <td>Female</td>\n      <td>58.0</td>\n      <td>Kolkata</td>\n      <td>Working Professional</td>\n      <td>Educational Consultant</td>\n      <td>NaN</td>\n      <td>2.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.0</td>\n      <td>Less than 5 hours</td>\n      <td>Moderate</td>\n      <td>B.Ed</td>\n      <td>No</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>140702</td>\n      <td>Yash</td>\n      <td>Male</td>\n      <td>53.0</td>\n      <td>Jaipur</td>\n      <td>Working Professional</td>\n      <td>Teacher</td>\n      <td>NaN</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>7-8 hours</td>\n      <td>Moderate</td>\n      <td>B.Arch</td>\n      <td>Yes</td>\n      <td>12.0</td>\n      <td>4.0</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>140703</td>\n      <td>Nalini</td>\n      <td>Female</td>\n      <td>23.0</td>\n      <td>Rajkot</td>\n      <td>Student</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>NaN</td>\n      <td>6.84</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>More than 8 hours</td>\n      <td>Moderate</td>\n      <td>BSc</td>\n      <td>Yes</td>\n      <td>10.0</td>\n      <td>4.0</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>140704</td>\n      <td>Shaurya</td>\n      <td>Male</td>\n      <td>47.0</td>\n      <td>Kalyan</td>\n      <td>Working Professional</td>\n      <td>Teacher</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>7-8 hours</td>\n      <td>Moderate</td>\n      <td>BCA</td>\n      <td>Yes</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>No</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      <td>...</td>\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      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>93795</th>\n      <td>234495</td>\n      <td>Zoya</td>\n      <td>Female</td>\n      <td>49.0</td>\n      <td>Jaipur</td>\n      <td>Working Professional</td>\n      <td>Pilot</td>\n      <td>NaN</td>\n      <td>3.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>Less than 5 hours</td>\n      <td>Moderate</td>\n      <td>BSc</td>\n      <td>Yes</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>93796</th>\n      <td>234496</td>\n      <td>Shlok</td>\n      <td>Male</td>\n      <td>29.0</td>\n      <td>Ahmedabad</td>\n      <td>Working Professional</td>\n      <td>Pilot</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>7-8 hours</td>\n      <td>Moderate</td>\n      <td>BE</td>\n      <td>Yes</td>\n      <td>11.0</td>\n      <td>3.0</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>93797</th>\n      <td>234497</td>\n      <td>Rishi</td>\n      <td>Male</td>\n      <td>24.0</td>\n      <td>Visakhapatnam</td>\n      <td>Student</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>7.51</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>7-8 hours</td>\n      <td>Moderate</td>\n      <td>B.Tech</td>\n      <td>No</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>93798</th>\n      <td>234498</td>\n      <td>Eshita</td>\n      <td>Female</td>\n      <td>23.0</td>\n      <td>Kalyan</td>\n      <td>Working Professional</td>\n      <td>Marketing Manager</td>\n      <td>NaN</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.0</td>\n      <td>5-6 hours</td>\n      <td>Healthy</td>\n      <td>BA</td>\n      <td>Yes</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>93799</th>\n      <td>234499</td>\n      <td>Gauri</td>\n      <td>Female</td>\n      <td>43.0</td>\n      <td>Varanasi</td>\n      <td>Working Professional</td>\n      <td>Educational Consultant</td>\n      <td>NaN</td>\n      <td>5.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.0</td>\n      <td>More than 8 hours</td>\n      <td>Healthy</td>\n      <td>B.Ed</td>\n      <td>No</td>\n      <td>11.0</td>\n      <td>2.0</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>93800 rows × 19 columns</p>\n</div>"},"metadata":{}}],"execution_count":2},{"cell_type":"code","source":"df.info()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:57:21.081320Z","iopub.execute_input":"2025-08-12T06:57:21.082133Z","iopub.status.idle":"2025-08-12T06:57:21.148953Z","shell.execute_reply.started":"2025-08-12T06:57:21.082100Z","shell.execute_reply":"2025-08-12T06:57:21.148398Z"}},"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 93800 entries, 0 to 93799\nData columns (total 19 columns):\n #   Column                                 Non-Null Count  Dtype  \n---  ------                                 --------------  -----  \n 0   id                                     93800 non-null  int64  \n 1   Name                                   93800 non-null  object \n 2   Gender                                 93800 non-null  object \n 3   Age                                    93800 non-null  float64\n 4   City                                   93800 non-null  object \n 5   Working Professional or Student        93800 non-null  object \n 6   Profession                             69168 non-null  object \n 7   Academic Pressure                      18767 non-null  float64\n 8   Work Pressure                          75022 non-null  float64\n 9   CGPA                                   18766 non-null  float64\n 10  Study Satisfaction                     18767 non-null  float64\n 11  Job Satisfaction                       75026 non-null  float64\n 12  Sleep Duration                         93800 non-null  object \n 13  Dietary Habits                         93795 non-null  object \n 14  Degree                                 93798 non-null  object \n 15  Have you ever had suicidal thoughts ?  93800 non-null  object \n 16  Work/Study Hours                       93800 non-null  float64\n 17  Financial Stress                       93800 non-null  float64\n 18  Family History of Mental Illness       93800 non-null  object \ndtypes: float64(8), int64(1), object(10)\nmemory usage: 13.6+ MB\n","output_type":"stream"}],"execution_count":3},{"cell_type":"code","source":"\n\ndf.columns\n\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:57:48.880084Z","iopub.execute_input":"2025-08-12T06:57:48.880977Z","iopub.status.idle":"2025-08-12T06:57:48.885843Z","shell.execute_reply.started":"2025-08-12T06:57:48.880947Z","shell.execute_reply":"2025-08-12T06:57:48.885114Z"}},"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"Index(['id', 'Name', 'Gender', 'Age', 'City',\n       'Working Professional or Student', 'Profession', 'Academic Pressure',\n       'Work Pressure', 'CGPA', 'Study Satisfaction', 'Job Satisfaction',\n       'Sleep Duration', 'Dietary Habits', 'Degree',\n       'Have you ever had suicidal thoughts ?', 'Work/Study Hours',\n       'Financial Stress', 'Family History of Mental Illness'],\n      dtype='object')"},"metadata":{}}],"execution_count":4},{"cell_type":"code","source":"\n\ndf.isnull().sum()\n\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:58:29.982997Z","iopub.execute_input":"2025-08-12T06:58:29.983535Z","iopub.status.idle":"2025-08-12T06:58:30.040118Z","shell.execute_reply.started":"2025-08-12T06:58:29.983511Z","shell.execute_reply":"2025-08-12T06:58:30.039360Z"}},"outputs":[{"execution_count":5,"output_type":"execute_result","data":{"text/plain":"id                                           0\nName                                         0\nGender                                       0\nAge                                          0\nCity                                         0\nWorking Professional or Student              0\nProfession                               24632\nAcademic Pressure                        75033\nWork Pressure                            18778\nCGPA                                     75034\nStudy Satisfaction                       75033\nJob Satisfaction                         18774\nSleep Duration                               0\nDietary Habits                               5\nDegree                                       2\nHave you ever had suicidal thoughts ?        0\nWork/Study Hours                             0\nFinancial Stress                             0\nFamily History of Mental Illness             0\ndtype: int64"},"metadata":{}}],"execution_count":5},{"cell_type":"code","source":"df.describe()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:58:44.611071Z","iopub.execute_input":"2025-08-12T06:58:44.611757Z","iopub.status.idle":"2025-08-12T06:58:44.692282Z","shell.execute_reply.started":"2025-08-12T06:58:44.611729Z","shell.execute_reply":"2025-08-12T06:58:44.691570Z"}},"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"                  id           Age  Academic Pressure  Work Pressure  \\\ncount   93800.000000  93800.000000       18767.000000   75022.000000   \nmean   187599.500000     40.321685           3.158576       3.011797   \nstd     27077.871962     12.393480           1.386666       1.403563   \nmin    140700.000000     18.000000           1.000000       1.000000   \n25%    164149.750000     29.000000           2.000000       2.000000   \n50%    187599.500000     42.000000           3.000000       3.000000   \n75%    211049.250000     51.000000           4.000000       4.000000   \nmax    234499.000000     60.000000           5.000000       5.000000   \n\n               CGPA  Study Satisfaction  Job Satisfaction  Work/Study Hours  \\\ncount  18766.000000        18767.000000       75026.00000      93800.000000   \nmean       7.674016            2.939522           2.96092          6.247335   \nstd        1.465056            1.374242           1.41071          3.858191   \nmin        5.030000            1.000000           1.00000          0.000000   \n25%        6.330000            2.000000           2.00000          3.000000   \n50%        7.800000            3.000000           3.00000          6.000000   \n75%        8.940000            4.000000           4.00000         10.000000   \nmax       10.000000            5.000000           5.00000         12.000000   \n\n       Financial Stress  \ncount      93800.000000  \nmean           2.978763  \nstd            1.414604  \nmin            1.000000  \n25%            2.000000  \n50%            3.000000  \n75%            4.000000  \nmax            5.000000  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>Age</th>\n      <th>Academic Pressure</th>\n      <th>Work Pressure</th>\n      <th>CGPA</th>\n      <th>Study Satisfaction</th>\n      <th>Job Satisfaction</th>\n      <th>Work/Study Hours</th>\n      <th>Financial Stress</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>93800.000000</td>\n      <td>93800.000000</td>\n      <td>18767.000000</td>\n      <td>75022.000000</td>\n      <td>18766.000000</td>\n      <td>18767.000000</td>\n      <td>75026.00000</td>\n      <td>93800.000000</td>\n      <td>93800.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>187599.500000</td>\n      <td>40.321685</td>\n      <td>3.158576</td>\n      <td>3.011797</td>\n      <td>7.674016</td>\n      <td>2.939522</td>\n      <td>2.96092</td>\n      <td>6.247335</td>\n      <td>2.978763</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>27077.871962</td>\n      <td>12.393480</td>\n      <td>1.386666</td>\n      <td>1.403563</td>\n      <td>1.465056</td>\n      <td>1.374242</td>\n      <td>1.41071</td>\n      <td>3.858191</td>\n      <td>1.414604</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>140700.000000</td>\n      <td>18.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>5.030000</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>0.000000</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>164149.750000</td>\n      <td>29.000000</td>\n      <td>2.000000</td>\n      <td>2.000000</td>\n      <td>6.330000</td>\n      <td>2.000000</td>\n      <td>2.00000</td>\n      <td>3.000000</td>\n      <td>2.000000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>187599.500000</td>\n      <td>42.000000</td>\n      <td>3.000000</td>\n      <td>3.000000</td>\n      <td>7.800000</td>\n      <td>3.000000</td>\n      <td>3.00000</td>\n      <td>6.000000</td>\n      <td>3.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>211049.250000</td>\n      <td>51.000000</td>\n      <td>4.000000</td>\n      <td>4.000000</td>\n      <td>8.940000</td>\n      <td>4.000000</td>\n      <td>4.00000</td>\n      <td>10.000000</td>\n      <td>4.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>234499.000000</td>\n      <td>60.000000</td>\n      <td>5.000000</td>\n      <td>5.000000</td>\n      <td>10.000000</td>\n      <td>5.000000</td>\n      <td>5.00000</td>\n      <td>12.000000</td>\n      <td>5.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":6},{"cell_type":"code","source":"import pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\n# Load dataset\ndf = pd.read_csv('/kaggle/input/exploring-mental-health-data/test.csv')\n\n# Select numerical columns\nnumerical_df = df.select_dtypes(include=['int64', 'float64'])\n\n# Compute correlation matrix\ncorr = numerical_df.corr()\n\n# Plot heatmap\nplt.figure(figsize=(10, 8))\nsns.heatmap(corr, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=0.5, square=True)\nplt.title(\"Correlation Heatmap of Numerical Features\", fontsize=16)\nplt.tight_layout()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T06:59:55.191180Z","iopub.execute_input":"2025-08-12T06:59:55.191936Z","iopub.status.idle":"2025-08-12T06:59:56.750378Z","shell.execute_reply.started":"2025-08-12T06:59:55.191910Z","shell.execute_reply":"2025-08-12T06:59:56.749608Z"}},"outputs":[{"name":"stderr","text":"/usr/local/lib/python3.11/dist-packages/matplotlib/colors.py:721: RuntimeWarning: invalid value encountered in less\n  xa[xa < 0] = -1\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 2 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":7},{"cell_type":"code","source":"import pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import LabelEncoder, StandardScaler\nfrom sklearn.impute import SimpleImputer\nfrom sklearn.metrics import classification_report, confusion_matrix, roc_curve, auc, RocCurveDisplay\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestClassifier\nfrom xgboost import XGBClassifier\nfrom sklearn.svm import SVC\nfrom sklearn.neighbors import KNeighborsClassifier\nimport warnings\nwarnings.filterwarnings(\"ignore\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T07:05:49.545396Z","iopub.execute_input":"2025-08-12T07:05:49.545915Z","iopub.status.idle":"2025-08-12T07:05:50.310111Z","shell.execute_reply.started":"2025-08-12T07:05:49.545888Z","shell.execute_reply":"2025-08-12T07:05:50.309375Z"}},"outputs":[],"execution_count":8},{"cell_type":"code","source":"# Load dataset\ndf = pd.read_csv(\"/kaggle/input/exploring-mental-health-data/test.csv\")\n\n# Drop irrelevant columns\ndf = df.drop(columns=[\"id\", \"Name\", \"City\", \"Profession\"])\n\n# Separate numeric and categorical\nnum_cols = df.select_dtypes(include=['int64', 'float64']).columns\ncat_cols = df.select_dtypes(include=['object']).columns\n\n# Impute missing values\ndf[num_cols] = SimpleImputer(strategy=\"median\").fit_transform(df[num_cols])\ndf[cat_cols] = SimpleImputer(strategy=\"most_frequent\").fit_transform(df[cat_cols])\n\n# Label encode categorical columns\nle_dict = {}\nfor col in cat_cols:\n    le = LabelEncoder()\n    df[col] = le.fit_transform(df[col])\n    le_dict[col] = le\n\n# Features and target\nX = df.drop(columns=[\"Working Professional or Student\"])\ny = df[\"Working Professional or Student\"]\n\n# Scale features\nscaler = StandardScaler()\nX_scaled = scaler.fit_transform(X)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T07:05:59.990150Z","iopub.execute_input":"2025-08-12T07:05:59.990519Z","iopub.status.idle":"2025-08-12T07:06:00.543014Z","shell.execute_reply.started":"2025-08-12T07:05:59.990493Z","shell.execute_reply":"2025-08-12T07:06:00.542275Z"}},"outputs":[],"execution_count":9},{"cell_type":"code","source":"# Train-test split\nX_train, X_test, y_train, y_test = train_test_split(X_scaled, y, test_size=0.2, random_state=42)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T07:06:44.683407Z","iopub.execute_input":"2025-08-12T07:06:44.683694Z","iopub.status.idle":"2025-08-12T07:06:44.702279Z","shell.execute_reply.started":"2025-08-12T07:06:44.683673Z","shell.execute_reply":"2025-08-12T07:06:44.701609Z"}},"outputs":[],"execution_count":10},{"cell_type":"code","source":"# Define models\nmodels = {\n    \"Logistic Regression\": LogisticRegression(max_iter=1000),\n    \"Decision Tree\": DecisionTreeClassifier(),\n    \"Random Forest\": RandomForestClassifier(),\n    \"XGBoost\": XGBClassifier(use_label_encoder=False, eval_metric='logloss')\n}\n\n# Plot ROC curves\nplt.figure(figsize=(10, 8))\n\nfor name, model in models.items():\n    model.fit(X_train, y_train)\n    y_proba = model.predict_proba(X_test)[:, 1]\n    fpr, tpr, _ = roc_curve(y_test, y_proba)\n    roc_auc = auc(fpr, tpr)\n\n    # Print classification report\n    print(f\"\\n--- {name} ---\")\n    print(\"Classification Report:\")\n    print(classification_report(y_test, model.predict(X_test)))\n    print(\"Confusion Matrix:\")\n    print(confusion_matrix(y_test, model.predict(X_test)))\n\n    # Plot ROC\n    plt.plot(fpr, tpr, label=f\"{name} (AUC = {roc_auc:.2f})\")\n\n# Plot settings\nplt.plot([0, 1], [0, 1], \"k--\")\nplt.xlabel(\"False Positive Rate\")\nplt.ylabel(\"True Positive Rate\")\nplt.title(\"ROC Curve - Family History of Mental Illness\")\nplt.legend(loc=\"lower right\")\nplt.grid(True)\nplt.tight_layout()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-12T07:07:10.124120Z","iopub.execute_input":"2025-08-12T07:07:10.124429Z","iopub.status.idle":"2025-08-12T07:07:13.900658Z","shell.execute_reply.started":"2025-08-12T07:07:10.124407Z","shell.execute_reply":"2025-08-12T07:07:13.899878Z"}},"outputs":[{"name":"stdout","text":"\n--- Logistic Regression ---\nClassification Report:\n              precision    recall  f1-score   support\n\n           0       0.61      0.55      0.58      3681\n           1       0.89      0.91      0.90     15079\n\n    accuracy                           0.84     18760\n   macro avg       0.75      0.73      0.74     18760\nweighted avg       0.84      0.84      0.84     18760\n\nConfusion Matrix:\n[[ 2016  1665]\n [ 1304 13775]]\n\n--- Decision Tree ---\nClassification Report:\n              precision    recall  f1-score   support\n\n           0       1.00      1.00      1.00      3681\n           1       1.00      1.00      1.00     15079\n\n    accuracy                           1.00     18760\n   macro avg       1.00      1.00      1.00     18760\nweighted avg       1.00      1.00      1.00     18760\n\nConfusion Matrix:\n[[ 3677     4]\n [    3 15076]]\n\n--- Random Forest ---\nClassification Report:\n              precision    recall  f1-score   support\n\n           0       1.00      1.00      1.00      3681\n           1       1.00      1.00      1.00     15079\n\n    accuracy                           1.00     18760\n   macro avg       1.00      1.00      1.00     18760\nweighted avg       1.00      1.00      1.00     18760\n\nConfusion Matrix:\n[[ 3678     3]\n [    2 15077]]\n\n--- XGBoost ---\nClassification Report:\n              precision    recall  f1-score   support\n\n           0       1.00      1.00      1.00      3681\n           1       1.00      1.00      1.00     15079\n\n    accuracy                           1.00     18760\n   macro avg       1.00      1.00      1.00     18760\nweighted avg       1.00      1.00      1.00     18760\n\nConfusion Matrix:\n[[ 3674     7]\n [    2 15077]]\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 1 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":11},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}