medical-insurance-cost-prediction.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":18513,"sourceType":"datasetVersion","datasetId":13720}],"dockerImageVersionId":30786,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"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","execution":{"iopub.status.busy":"2024-10-26T08:55:45.643807Z","iopub.execute_input":"2024-10-26T08:55:45.644340Z","iopub.status.idle":"2024-10-26T08:55:46.297569Z","shell.execute_reply.started":"2024-10-26T08:55:45.644286Z","shell.execute_reply":"2024-10-26T08:55:46.295982Z"},"trusted":true},"execution_count":3,"outputs":[{"name":"stdout","text":"/kaggle/input/insurance/insurance.csv\n","output_type":"stream"}]},{"cell_type":"code","source":"data = pd.read_csv('/kaggle/input/insurance/insurance.csv')","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.300281Z","iopub.execute_input":"2024-10-26T08:55:46.301051Z","iopub.status.idle":"2024-10-26T08:55:46.327027Z","shell.execute_reply.started":"2024-10-26T08:55:46.300971Z","shell.execute_reply":"2024-10-26T08:55:46.325602Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"data.sample(5)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.328518Z","iopub.execute_input":"2024-10-26T08:55:46.328925Z","iopub.status.idle":"2024-10-26T08:55:46.365732Z","shell.execute_reply.started":"2024-10-26T08:55:46.328882Z","shell.execute_reply":"2024-10-26T08:55:46.364462Z"},"trusted":true},"execution_count":5,"outputs":[{"execution_count":5,"output_type":"execute_result","data":{"text/plain":"     age     sex     bmi  children smoker     region      charges\n691   47    male  36.200         1     no  southwest   8068.18500\n658   48  female  35.910         1     no  northeast  26392.26029\n115   60    male  28.595         0     no  northeast  30259.99556\n17    23    male  23.845         0     no  northeast   2395.17155\n775   51    male  33.330         3     no  southeast  10560.49170","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>age</th>\n      <th>sex</th>\n      <th>bmi</th>\n      <th>children</th>\n      <th>smoker</th>\n      <th>region</th>\n      <th>charges</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>691</th>\n      <td>47</td>\n      <td>male</td>\n      <td>36.200</td>\n      <td>1</td>\n      <td>no</td>\n      <td>southwest</td>\n      <td>8068.18500</td>\n    </tr>\n    <tr>\n      <th>658</th>\n      <td>48</td>\n      <td>female</td>\n      <td>35.910</td>\n      <td>1</td>\n      <td>no</td>\n      <td>northeast</td>\n      <td>26392.26029</td>\n    </tr>\n    <tr>\n      <th>115</th>\n      <td>60</td>\n      <td>male</td>\n      <td>28.595</td>\n      <td>0</td>\n      <td>no</td>\n      <td>northeast</td>\n      <td>30259.99556</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>23</td>\n      <td>male</td>\n      <td>23.845</td>\n      <td>0</td>\n      <td>no</td>\n      <td>northeast</td>\n      <td>2395.17155</td>\n    </tr>\n    <tr>\n      <th>775</th>\n      <td>51</td>\n      <td>male</td>\n      <td>33.330</td>\n      <td>3</td>\n      <td>no</td>\n      <td>southeast</td>\n      <td>10560.49170</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# **1.Display Top 5 rows of The Dataset**","metadata":{}},{"cell_type":"code","source":"data.head(5)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.368892Z","iopub.execute_input":"2024-10-26T08:55:46.369296Z","iopub.status.idle":"2024-10-26T08:55:46.385642Z","shell.execute_reply.started":"2024-10-26T08:55:46.369254Z","shell.execute_reply":"2024-10-26T08:55:46.384152Z"},"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"   age     sex     bmi  children smoker     region      charges\n0   19  female  27.900         0    yes  southwest  16884.92400\n1   18    male  33.770         1     no  southeast   1725.55230\n2   28    male  33.000         3     no  southeast   4449.46200\n3   33    male  22.705         0     no  northwest  21984.47061\n4   32    male  28.880         0     no  northwest   3866.85520","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>age</th>\n      <th>sex</th>\n      <th>bmi</th>\n      <th>children</th>\n      <th>smoker</th>\n      <th>region</th>\n      <th>charges</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>19</td>\n      <td>female</td>\n      <td>27.900</td>\n      <td>0</td>\n      <td>yes</td>\n      <td>southwest</td>\n      <td>16884.92400</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>18</td>\n      <td>male</td>\n      <td>33.770</td>\n      <td>1</td>\n      <td>no</td>\n      <td>southeast</td>\n      <td>1725.55230</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>28</td>\n      <td>male</td>\n      <td>33.000</td>\n      <td>3</td>\n      <td>no</td>\n      <td>southeast</td>\n      <td>4449.46200</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>33</td>\n      <td>male</td>\n      <td>22.705</td>\n      <td>0</td>\n      <td>no</td>\n      <td>northwest</td>\n      <td>21984.47061</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>32</td>\n      <td>male</td>\n      <td>28.880</td>\n      <td>0</td>\n      <td>no</td>\n      <td>northwest</td>\n      <td>3866.85520</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# **2. Check Last 5 Rows of the Dataset**","metadata":{}},{"cell_type":"code","source":"data.tail()","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.387688Z","iopub.execute_input":"2024-10-26T08:55:46.388150Z","iopub.status.idle":"2024-10-26T08:55:46.405094Z","shell.execute_reply.started":"2024-10-26T08:55:46.388084Z","shell.execute_reply":"2024-10-26T08:55:46.403606Z"},"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"      age     sex    bmi  children smoker     region     charges\n1333   50    male  30.97         3     no  northwest  10600.5483\n1334   18  female  31.92         0     no  northeast   2205.9808\n1335   18  female  36.85         0     no  southeast   1629.8335\n1336   21  female  25.80         0     no  southwest   2007.9450\n1337   61  female  29.07         0    yes  northwest  29141.3603","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>age</th>\n      <th>sex</th>\n      <th>bmi</th>\n      <th>children</th>\n      <th>smoker</th>\n      <th>region</th>\n      <th>charges</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1333</th>\n      <td>50</td>\n      <td>male</td>\n      <td>30.97</td>\n      <td>3</td>\n      <td>no</td>\n      <td>northwest</td>\n      <td>10600.5483</td>\n    </tr>\n    <tr>\n      <th>1334</th>\n      <td>18</td>\n      <td>female</td>\n      <td>31.92</td>\n      <td>0</td>\n      <td>no</td>\n      <td>northeast</td>\n      <td>2205.9808</td>\n    </tr>\n    <tr>\n      <th>1335</th>\n      <td>18</td>\n      <td>female</td>\n      <td>36.85</td>\n      <td>0</td>\n      <td>no</td>\n      <td>southeast</td>\n      <td>1629.8335</td>\n    </tr>\n    <tr>\n      <th>1336</th>\n      <td>21</td>\n      <td>female</td>\n      <td>25.80</td>\n      <td>0</td>\n      <td>no</td>\n      <td>southwest</td>\n      <td>2007.9450</td>\n    </tr>\n    <tr>\n      <th>1337</th>\n      <td>61</td>\n      <td>female</td>\n      <td>29.07</td>\n      <td>0</td>\n      <td>yes</td>\n      <td>northwest</td>\n      <td>29141.3603</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# **3. Find shape of our Dataset**","metadata":{}},{"cell_type":"code","source":"data.shape","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.407063Z","iopub.execute_input":"2024-10-26T08:55:46.407645Z","iopub.status.idle":"2024-10-26T08:55:46.420921Z","shell.execute_reply.started":"2024-10-26T08:55:46.407584Z","shell.execute_reply":"2024-10-26T08:55:46.419445Z"},"trusted":true},"execution_count":8,"outputs":[{"execution_count":8,"output_type":"execute_result","data":{"text/plain":"(1338, 7)"},"metadata":{}}]},{"cell_type":"markdown","source":"# 4. **Get Information about Dataset**","metadata":{}},{"cell_type":"code","source":"data.info()","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.422840Z","iopub.execute_input":"2024-10-26T08:55:46.423293Z","iopub.status.idle":"2024-10-26T08:55:46.457123Z","shell.execute_reply.started":"2024-10-26T08:55:46.423247Z","shell.execute_reply":"2024-10-26T08:55:46.455728Z"},"trusted":true},"execution_count":9,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 1338 entries, 0 to 1337\nData columns (total 7 columns):\n #   Column    Non-Null Count  Dtype  \n---  ------    --------------  -----  \n 0   age       1338 non-null   int64  \n 1   sex       1338 non-null   object \n 2   bmi       1338 non-null   float64\n 3   children  1338 non-null   int64  \n 4   smoker    1338 non-null   object \n 5   region    1338 non-null   object \n 6   charges   1338 non-null   float64\ndtypes: float64(2), int64(2), object(3)\nmemory usage: 73.3+ KB\n","output_type":"stream"}]},{"cell_type":"markdown","source":"* ### **The dataset does not contain any missing values.**","metadata":{}},{"cell_type":"markdown","source":"# 5. **Check Null Values in The Dataset**","metadata":{}},{"cell_type":"code","source":"  data.isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.458469Z","iopub.execute_input":"2024-10-26T08:55:46.458860Z","iopub.status.idle":"2024-10-26T08:55:46.470651Z","shell.execute_reply.started":"2024-10-26T08:55:46.458820Z","shell.execute_reply":"2024-10-26T08:55:46.469113Z"},"trusted":true},"execution_count":10,"outputs":[{"execution_count":10,"output_type":"execute_result","data":{"text/plain":"age         0\nsex         0\nbmi         0\nchildren    0\nsmoker      0\nregion      0\ncharges     0\ndtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"# 6. **Get overall statistics about the dataset**","metadata":{}},{"cell_type":"code","source":"data.describe(include='all')","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.472271Z","iopub.execute_input":"2024-10-26T08:55:46.472820Z","iopub.status.idle":"2024-10-26T08:55:46.514063Z","shell.execute_reply.started":"2024-10-26T08:55:46.472758Z","shell.execute_reply":"2024-10-26T08:55:46.512866Z"},"trusted":true},"execution_count":11,"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"                age   sex          bmi     children smoker     region  \\\ncount   1338.000000  1338  1338.000000  1338.000000   1338       1338   \nunique          NaN     2          NaN          NaN      2          4   \ntop             NaN  male          NaN          NaN     no  southeast   \nfreq            NaN   676          NaN          NaN   1064        364   \nmean      39.207025   NaN    30.663397     1.094918    NaN        NaN   \nstd       14.049960   NaN     6.098187     1.205493    NaN        NaN   \nmin       18.000000   NaN    15.960000     0.000000    NaN        NaN   \n25%       27.000000   NaN    26.296250     0.000000    NaN        NaN   \n50%       39.000000   NaN    30.400000     1.000000    NaN        NaN   \n75%       51.000000   NaN    34.693750     2.000000    NaN        NaN   \nmax       64.000000   NaN    53.130000     5.000000    NaN        NaN   \n\n             charges  \ncount    1338.000000  \nunique           NaN  \ntop              NaN  \nfreq             NaN  \nmean    13270.422265  \nstd     12110.011237  \nmin      1121.873900  \n25%      4740.287150  \n50%      9382.033000  \n75%     16639.912515  \nmax     63770.428010  ","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>age</th>\n      <th>sex</th>\n      <th>bmi</th>\n      <th>children</th>\n      <th>smoker</th>\n      <th>region</th>\n      <th>charges</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>1338.000000</td>\n      <td>1338</td>\n      <td>1338.000000</td>\n      <td>1338.000000</td>\n      <td>1338</td>\n      <td>1338</td>\n      <td>1338.000000</td>\n    </tr>\n    <tr>\n      <th>unique</th>\n      <td>NaN</td>\n      <td>2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2</td>\n      <td>4</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>top</th>\n      <td>NaN</td>\n      <td>male</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>no</td>\n      <td>southeast</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>freq</th>\n      <td>NaN</td>\n      <td>676</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1064</td>\n      <td>364</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>39.207025</td>\n      <td>NaN</td>\n      <td>30.663397</td>\n      <td>1.094918</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>13270.422265</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>14.049960</td>\n      <td>NaN</td>\n      <td>6.098187</td>\n      <td>1.205493</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>12110.011237</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>18.000000</td>\n      <td>NaN</td>\n      <td>15.960000</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1121.873900</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>27.000000</td>\n      <td>NaN</td>\n      <td>26.296250</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4740.287150</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>39.000000</td>\n      <td>NaN</td>\n      <td>30.400000</td>\n      <td>1.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9382.033000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>51.000000</td>\n      <td>NaN</td>\n      <td>34.693750</td>\n      <td>2.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>16639.912515</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>64.000000</td>\n      <td>NaN</td>\n      <td>53.130000</td>\n      <td>5.000000</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>63770.428010</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# 7. Convert categorical columns to numerical values.","metadata":{}},{"cell_type":"markdown","source":"* ###  **`You can use Label Encoding or One-Hot Encoding, but here I am doing it manually.`**","metadata":{}},{"cell_type":"code","source":"print(data['sex'].unique())\nprint(data['smoker'].unique())\nprint(data['region'].unique())","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.518432Z","iopub.execute_input":"2024-10-26T08:55:46.518901Z","iopub.status.idle":"2024-10-26T08:55:46.528181Z","shell.execute_reply.started":"2024-10-26T08:55:46.518855Z","shell.execute_reply":"2024-10-26T08:55:46.526549Z"},"trusted":true},"execution_count":12,"outputs":[{"name":"stdout","text":"['female' 'male']\n['yes' 'no']\n['southwest' 'southeast' 'northwest' 'northeast']\n","output_type":"stream"}]},{"cell_type":"code","source":"# Columns -> sex, smoker, region\n\ndata['sex'] = data['sex'].map({'female':0,'male':1})\ndata['smoker'] = data['smoker'].map({'yes':1,'no':0})\ndata['region'] = data['region'].map({'southwest':0,'southeast':1,'northwest':2,'northeast':3})","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.529835Z","iopub.execute_input":"2024-10-26T08:55:46.530353Z","iopub.status.idle":"2024-10-26T08:55:46.545821Z","shell.execute_reply.started":"2024-10-26T08:55:46.530292Z","shell.execute_reply":"2024-10-26T08:55:46.544397Z"},"trusted":true},"execution_count":13,"outputs":[]},{"cell_type":"code","source":"data","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.547517Z","iopub.execute_input":"2024-10-26T08:55:46.548026Z","iopub.status.idle":"2024-10-26T08:55:46.572371Z","shell.execute_reply.started":"2024-10-26T08:55:46.547975Z","shell.execute_reply":"2024-10-26T08:55:46.570920Z"},"trusted":true},"execution_count":14,"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":"      age  sex     bmi  children  smoker  region      charges\n0      19    0  27.900         0       1       0  16884.92400\n1      18    1  33.770         1       0       1   1725.55230\n2      28    1  33.000         3       0       1   4449.46200\n3      33    1  22.705         0       0       2  21984.47061\n4      32    1  28.880         0       0       2   3866.85520\n...   ...  ...     ...       ...     ...     ...          ...\n1333   50    1  30.970         3       0       2  10600.54830\n1334   18    0  31.920         0       0       3   2205.98080\n1335   18    0  36.850         0       0       1   1629.83350\n1336   21    0  25.800         0       0       0   2007.94500\n1337   61    0  29.070         0       1       2  29141.36030\n\n[1338 rows x 7 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>age</th>\n      <th>sex</th>\n      <th>bmi</th>\n      <th>children</th>\n      <th>smoker</th>\n      <th>region</th>\n      <th>charges</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>19</td>\n      <td>0</td>\n      <td>27.900</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>16884.92400</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>18</td>\n      <td>1</td>\n      <td>33.770</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1725.55230</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>28</td>\n      <td>1</td>\n      <td>33.000</td>\n      <td>3</td>\n      <td>0</td>\n      <td>1</td>\n      <td>4449.46200</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>33</td>\n      <td>1</td>\n      <td>22.705</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>21984.47061</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>32</td>\n      <td>1</td>\n      <td>28.880</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>3866.85520</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    </tr>\n    <tr>\n      <th>1333</th>\n      <td>50</td>\n      <td>1</td>\n      <td>30.970</td>\n      <td>3</td>\n      <td>0</td>\n      <td>2</td>\n      <td>10600.54830</td>\n    </tr>\n    <tr>\n      <th>1334</th>\n      <td>18</td>\n      <td>0</td>\n      <td>31.920</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>2205.98080</td>\n    </tr>\n    <tr>\n      <th>1335</th>\n      <td>18</td>\n      <td>0</td>\n      <td>36.850</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1629.83350</td>\n    </tr>\n    <tr>\n      <th>1336</th>\n      <td>21</td>\n      <td>0</td>\n      <td>25.800</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2007.94500</td>\n    </tr>\n    <tr>\n      <th>1337</th>\n      <td>61</td>\n      <td>0</td>\n      <td>29.070</td>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n      <td>29141.36030</td>\n    </tr>\n  </tbody>\n</table>\n<p>1338 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# 8. **Store the feature matrix in X and the target vector in y.**","metadata":{}},{"cell_type":"code","source":"X = data.drop('charges', axis=1)\ny = data['charges']","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.574299Z","iopub.execute_input":"2024-10-26T08:55:46.575103Z","iopub.status.idle":"2024-10-26T08:55:46.583520Z","shell.execute_reply.started":"2024-10-26T08:55:46.575055Z","shell.execute_reply":"2024-10-26T08:55:46.582062Z"},"trusted":true},"execution_count":15,"outputs":[]},{"cell_type":"markdown","source":"# **9. Train/Test split**\n1. split data into 2 part \n             * training set\n             * testing set\n2. Train the model on training set\n3. Test the model on testing set","metadata":{}},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.585195Z","iopub.execute_input":"2024-10-26T08:55:46.585665Z","iopub.status.idle":"2024-10-26T08:55:46.599138Z","shell.execute_reply.started":"2024-10-26T08:55:46.585619Z","shell.execute_reply":"2024-10-26T08:55:46.597820Z"},"trusted":true},"execution_count":16,"outputs":[]},{"cell_type":"markdown","source":"* ***As we know, this is a regression problem because the target variable has continuous values, so we will use regression models***","metadata":{}},{"cell_type":"markdown","source":"# **10. Import the models**","metadata":{}},{"cell_type":"code","source":"from sklearn.linear_model import LinearRegression\nfrom sklearn.svm import SVR\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.ensemble import GradientBoostingRegressor\n    ","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.600729Z","iopub.execute_input":"2024-10-26T08:55:46.601139Z","iopub.status.idle":"2024-10-26T08:55:46.614893Z","shell.execute_reply.started":"2024-10-26T08:55:46.601096Z","shell.execute_reply":"2024-10-26T08:55:46.613382Z"},"trusted":true},"execution_count":17,"outputs":[]},{"cell_type":"markdown","source":"# **11. Model Training**","metadata":{}},{"cell_type":"code","source":"lr = LinearRegression()\nlr.fit(X_train, y_train)\n\nsvm = SVR()\nsvm.fit(X_train, y_train)\n\nrf = RandomForestRegressor()\nrf.fit(X_train, y_train)\n\ngr = GradientBoostingRegressor()\ngr.fit(X_train, y_train)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T08:55:46.616959Z","iopub.execute_input":"2024-10-26T08:55:46.617532Z","iopub.status.idle":"2024-10-26T08:55:47.300017Z","shell.execute_reply.started":"2024-10-26T08:55:46.617448Z","shell.execute_reply":"2024-10-26T08:55:47.298514Z"},"trusted":true},"execution_count":18,"outputs":[{"execution_count":18,"output_type":"execute_result","data":{"text/plain":"GradientBoostingRegressor()","text/html":"<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GradientBoostingRegressor()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GradientBoostingRegressor</label><div class=\"sk-toggleable__content\"><pre>GradientBoostingRegressor()</pre></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"markdown","source":"","metadata":{}},{"cell_type":"markdown","source":"# **12. Prediction on Test Data**","metadata":{}},{"cell_type":"code","source":"lr_pred = lr.predict(X_test)\nsvm_pred = svm.predict(X_test)\nrf_pred = rf.predict(X_test)\ngr_pred = gr.predict(X_test)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:00:46.710874Z","iopub.execute_input":"2024-10-26T09:00:46.711384Z","iopub.status.idle":"2024-10-26T09:00:46.757837Z","shell.execute_reply.started":"2024-10-26T09:00:46.711338Z","shell.execute_reply":"2024-10-26T09:00:46.756224Z"},"trusted":true},"execution_count":27,"outputs":[]},{"cell_type":"code","source":"df = pd.DataFrame({'Actual':y_test,'lr_pred':lr_pred,'svm_pred':svm_pred,'rf_pred':rf_pred,'gr_pred':gr_pred})","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:00:47.164162Z","iopub.execute_input":"2024-10-26T09:00:47.164713Z","iopub.status.idle":"2024-10-26T09:00:47.171888Z","shell.execute_reply.started":"2024-10-26T09:00:47.164666Z","shell.execute_reply":"2024-10-26T09:00:47.170312Z"},"trusted":true},"execution_count":28,"outputs":[]},{"cell_type":"code","source":"df","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:00:47.634857Z","iopub.execute_input":"2024-10-26T09:00:47.635341Z","iopub.status.idle":"2024-10-26T09:00:47.654782Z","shell.execute_reply.started":"2024-10-26T09:00:47.635293Z","shell.execute_reply":"2024-10-26T09:00:47.652969Z"},"trusted":true},"execution_count":29,"outputs":[{"execution_count":29,"output_type":"execute_result","data":{"text/plain":"           Actual       lr_pred     svm_pred       rf_pred       gr_pred\n764    9095.06825   8924.407244  9548.501784  11350.144941  11001.128629\n887    5272.17580   7116.295018  9493.253027   4956.626517   5840.174656\n890   29330.98315  36909.013521  9648.297116  28407.858865  28001.980112\n1293   9301.89355   9507.874691  9555.223014  10772.230358   9745.291602\n259   33750.29180  27013.350008  9421.474560  34596.261010  33639.100981\n...           ...           ...          ...           ...           ...\n109   47055.53210  39116.968669  9648.419534  47150.165725  45431.423211\n575   12222.89830  11814.555568  9625.047904  12694.990235  12465.025294\n535    6067.12675   7638.107736  9504.805678   6325.493058   6974.336525\n543   63770.42801  40959.081722  9604.855076  46677.583303  47862.047791\n846    9872.70100  12258.228529  9590.848077   9832.740704  10289.655388\n\n[268 rows x 5 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>Actual</th>\n      <th>lr_pred</th>\n      <th>svm_pred</th>\n      <th>rf_pred</th>\n      <th>gr_pred</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>764</th>\n      <td>9095.06825</td>\n      <td>8924.407244</td>\n      <td>9548.501784</td>\n      <td>11350.144941</td>\n      <td>11001.128629</td>\n    </tr>\n    <tr>\n      <th>887</th>\n      <td>5272.17580</td>\n      <td>7116.295018</td>\n      <td>9493.253027</td>\n      <td>4956.626517</td>\n      <td>5840.174656</td>\n    </tr>\n    <tr>\n      <th>890</th>\n      <td>29330.98315</td>\n      <td>36909.013521</td>\n      <td>9648.297116</td>\n      <td>28407.858865</td>\n      <td>28001.980112</td>\n    </tr>\n    <tr>\n      <th>1293</th>\n      <td>9301.89355</td>\n      <td>9507.874691</td>\n      <td>9555.223014</td>\n      <td>10772.230358</td>\n      <td>9745.291602</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>33750.29180</td>\n      <td>27013.350008</td>\n      <td>9421.474560</td>\n      <td>34596.261010</td>\n      <td>33639.100981</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>109</th>\n      <td>47055.53210</td>\n      <td>39116.968669</td>\n      <td>9648.419534</td>\n      <td>47150.165725</td>\n      <td>45431.423211</td>\n    </tr>\n    <tr>\n      <th>575</th>\n      <td>12222.89830</td>\n      <td>11814.555568</td>\n      <td>9625.047904</td>\n      <td>12694.990235</td>\n      <td>12465.025294</td>\n    </tr>\n    <tr>\n      <th>535</th>\n      <td>6067.12675</td>\n      <td>7638.107736</td>\n      <td>9504.805678</td>\n      <td>6325.493058</td>\n      <td>6974.336525</td>\n    </tr>\n    <tr>\n      <th>543</th>\n      <td>63770.42801</td>\n      <td>40959.081722</td>\n      <td>9604.855076</td>\n      <td>46677.583303</td>\n      <td>47862.047791</td>\n    </tr>\n    <tr>\n      <th>846</th>\n      <td>9872.70100</td>\n      <td>12258.228529</td>\n      <td>9590.848077</td>\n      <td>9832.740704</td>\n      <td>10289.655388</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 5 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# **13. Comapare Performance Visually**","metadata":{}},{"cell_type":"code","source":"import matplotlib.pyplot as plt","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:02:46.322728Z","iopub.execute_input":"2024-10-26T09:02:46.323340Z","iopub.status.idle":"2024-10-26T09:02:46.330053Z","shell.execute_reply.started":"2024-10-26T09:02:46.323270Z","shell.execute_reply":"2024-10-26T09:02:46.328035Z"},"trusted":true},"execution_count":30,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(12, 8))  # Set figure size first\n\nplt.subplot(221)  # Define the first subplot in a 2x2 grid\nplt.plot(df['Actual'].iloc[0:11], label='Actual')\nplt.plot(df['lr_pred'].iloc[0:11], label='Lr')\nplt.legend()\n\n\nplt.subplot(222)  \nplt.plot(df['Actual'].iloc[0:11], label='Actual')\nplt.plot(df['svm_pred'].iloc[0:11], label='svm')\nplt.legend()\n\n\nplt.subplot(223)  \nplt.plot(df['Actual'].iloc[0:11], label='Actual')\nplt.plot(df['rf_pred'].iloc[0:11], label='RF')\nplt.legend()\n\n\nplt.subplot(224)  \nplt.plot(df['Actual'].iloc[0:11], label='Actual')\nplt.plot(df['gr_pred'].iloc[0:11], label='GR')\nplt.legend()\n","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:11:36.831303Z","iopub.execute_input":"2024-10-26T09:11:36.831851Z","iopub.status.idle":"2024-10-26T09:11:37.918574Z","shell.execute_reply.started":"2024-10-26T09:11:36.831798Z","shell.execute_reply":"2024-10-26T09:11:37.917159Z"},"trusted":true},"execution_count":45,"outputs":[{"execution_count":45,"output_type":"execute_result","data":{"text/plain":"<matplotlib.legend.Legend at 0x78edbd10b850>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1200x800 with 4 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"# **14. Evaluating the Algorithm**","metadata":{}},{"cell_type":"code","source":"from sklearn.metrics import r2_score, mean_absolute_error","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:17:46.178395Z","iopub.execute_input":"2024-10-26T09:17:46.178914Z","iopub.status.idle":"2024-10-26T09:17:46.185338Z","shell.execute_reply.started":"2024-10-26T09:17:46.178858Z","shell.execute_reply":"2024-10-26T09:17:46.183835Z"},"trusted":true},"execution_count":50,"outputs":[]},{"cell_type":"code","source":"lr_score = r2_score(y_test, lr_pred)\nsvm_score = r2_score(y_test, svm_pred)\nrf_score = r2_score(y_test, rf_pred)\ngr_score = r2_score(y_test, gr_pred)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:15:22.410049Z","iopub.execute_input":"2024-10-26T09:15:22.411287Z","iopub.status.idle":"2024-10-26T09:15:22.420790Z","shell.execute_reply.started":"2024-10-26T09:15:22.411227Z","shell.execute_reply":"2024-10-26T09:15:22.419395Z"},"trusted":true},"execution_count":47,"outputs":[]},{"cell_type":"code","source":"print(lr_score, svm_score, rf_score, gr_score)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:16:00.167112Z","iopub.execute_input":"2024-10-26T09:16:00.167707Z","iopub.status.idle":"2024-10-26T09:16:00.176453Z","shell.execute_reply.started":"2024-10-26T09:16:00.167654Z","shell.execute_reply":"2024-10-26T09:16:00.174351Z"},"trusted":true},"execution_count":48,"outputs":[{"name":"stdout","text":"0.7833463107364539 -0.07230841842488811 0.8637635256800384 0.8779936181637191\n","output_type":"stream"}]},{"cell_type":"code","source":"lr_score_m = mean_absolute_error(y_test, lr_pred)\nsvm_score_m = mean_absolute_error(y_test, svm_pred)\nrf_score_m = mean_absolute_error(y_test, rf_pred)\ngr_score_m = mean_absolute_error(y_test, gr_pred)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:17:50.367197Z","iopub.execute_input":"2024-10-26T09:17:50.368395Z","iopub.status.idle":"2024-10-26T09:17:50.376990Z","shell.execute_reply.started":"2024-10-26T09:17:50.368319Z","shell.execute_reply":"2024-10-26T09:17:50.375622Z"},"trusted":true},"execution_count":51,"outputs":[]},{"cell_type":"code","source":"print(lr_score_m,svm_score_m,rf_score_m,gr_score_m)","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:18:24.879553Z","iopub.execute_input":"2024-10-26T09:18:24.880144Z","iopub.status.idle":"2024-10-26T09:18:24.888159Z","shell.execute_reply.started":"2024-10-26T09:18:24.880091Z","shell.execute_reply":"2024-10-26T09:18:24.886576Z"},"trusted":true},"execution_count":52,"outputs":[{"name":"stdout","text":"4186.508898366432 8592.79866979489 2501.9867251337064 2447.167158715136\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# **15. Predict Charges for New Customer**","metadata":{}},{"cell_type":"code","source":"data1 = {\n    'age':40,\n    'sex':1,\n    'bmi':40.30,\n    'children':4,\n    'smoker':1,\n    'region':2\n}\ndf_ = pd.DataFrame(data1, index=[0])","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:21:47.779839Z","iopub.execute_input":"2024-10-26T09:21:47.780430Z","iopub.status.idle":"2024-10-26T09:21:47.791937Z","shell.execute_reply.started":"2024-10-26T09:21:47.780376Z","shell.execute_reply":"2024-10-26T09:21:47.790222Z"},"trusted":true},"execution_count":54,"outputs":[]},{"cell_type":"code","source":"df_","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:21:50.867232Z","iopub.execute_input":"2024-10-26T09:21:50.867764Z","iopub.status.idle":"2024-10-26T09:21:50.882596Z","shell.execute_reply.started":"2024-10-26T09:21:50.867716Z","shell.execute_reply":"2024-10-26T09:21:50.881258Z"},"trusted":true},"execution_count":55,"outputs":[{"execution_count":55,"output_type":"execute_result","data":{"text/plain":"   age  sex   bmi  children  smoker  region\n0   40    1  40.3         4       1       2","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>age</th>\n      <th>sex</th>\n      <th>bmi</th>\n      <th>children</th>\n      <th>smoker</th>\n      <th>region</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>40</td>\n      <td>1</td>\n      <td>40.3</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"new_pred = gr.predict(df_)\nnew_pred","metadata":{"execution":{"iopub.status.busy":"2024-10-26T09:22:52.583370Z","iopub.execute_input":"2024-10-26T09:22:52.584042Z","iopub.status.idle":"2024-10-26T09:22:52.598532Z","shell.execute_reply.started":"2024-10-26T09:22:52.583985Z","shell.execute_reply":"2024-10-26T09:22:52.596697Z"},"trusted":true},"execution_count":56,"outputs":[{"execution_count":56,"output_type":"execute_result","data":{"text/plain":"array([44974.84644584])"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}