notebook (2).ipynb

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No         No           No\n1       Inter    SEA    Male  ...       No         No           No\n2       Inter    SEA    Male  ...       No         No           No\n3       Inter     EA  Female  ...       No         No           No\n4       Inter     EA  Female  ...       No         No           No\n..        ...    ...     ...  ...      ...        ...          ...\n281      None   None    None  ...     None       None         None\n282      None   None    None  ...     None       None         None\n283      None   None    None  ...     None       None         None\n284      None   None    None  ...     None       None         None\n285      None   None    None  ...     None       None         None\n\n[286 rows x 50 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>inter_dom</th>\n      <th>region</th>\n      <th>gender</th>\n      <th>academic</th>\n      <th>age</th>\n      <th>age_cate</th>\n      <th>stay</th>\n      <th>stay_cate</th>\n      <th>japanese</th>\n      <th>japanese_cate</th>\n      <th>english</th>\n      <th>english_cate</th>\n      <th>intimate</th>\n      <th>religion</th>\n      <th>suicide</th>\n      <th>dep</th>\n      <th>deptype</th>\n      <th>todep</th>\n      <th>depsev</th>\n      <th>tosc</th>\n      <th>apd</th>\n      <th>ahome</th>\n      <th>aph</th>\n      <th>afear</th>\n      <th>acs</th>\n      <th>aguilt</th>\n      <th>amiscell</th>\n      <th>toas</th>\n      <th>partner</th>\n      <th>friends</th>\n      <th>parents</th>\n      <th>relative</th>\n      <th>profess</th>\n      <th>phone</th>\n      <th>doctor</th>\n      <th>reli</th>\n      <th>alone</th>\n      <th>others</th>\n      <th>internet</th>\n      <th>partner_bi</th>\n      <th>friends_bi</th>\n      <th>parents_bi</th>\n      <th>relative_bi</th>\n      <th>professional_bi</th>\n      <th>phone_bi</th>\n      <th>doctor_bi</th>\n      <th>religion_bi</th>\n      <th>alone_bi</th>\n      <th>others_bi</th>\n      <th>internet_bi</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Grad</td>\n      <td>24.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>Long</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>None</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>0.0</td>\n      <td>Min</td>\n      <td>34.0</td>\n      <td>23.0</td>\n      <td>9.0</td>\n      <td>11.0</td>\n      <td>8.0</td>\n      <td>11.0</td>\n      <td>2.0</td>\n      <td>27.0</td>\n      <td>91.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>6.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Grad</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>None</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>2.0</td>\n      <td>Min</td>\n      <td>48.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>10.0</td>\n      <td>39.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Grad</td>\n      <td>25.0</td>\n      <td>4.0</td>\n      <td>6.0</td>\n      <td>Long</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>2.0</td>\n      <td>Min</td>\n      <td>41.0</td>\n      <td>13.0</td>\n      <td>4.0</td>\n      <td>7.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>14.0</td>\n      <td>51.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Inter</td>\n      <td>EA</td>\n      <td>Female</td>\n      <td>Grad</td>\n      <td>29.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>2.0</td>\n      <td>Low</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>3.0</td>\n      <td>Min</td>\n      <td>37.0</td>\n      <td>16.0</td>\n      <td>10.0</td>\n      <td>10.0</td>\n      <td>8.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>21.0</td>\n      <td>75.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Inter</td>\n      <td>EA</td>\n      <td>Female</td>\n      <td>Grad</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>1.0</td>\n      <td>Low</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>3.0</td>\n      <td>Min</td>\n      <td>37.0</td>\n      <td>15.0</td>\n      <td>12.0</td>\n      <td>5.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>4.0</td>\n      <td>31.0</td>\n      <td>82.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</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      <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      <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>281</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>46</td>\n      <td>222</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>282</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>19</td>\n      <td>249</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>283</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>65</td>\n      <td>203</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>284</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>21</td>\n      <td>247</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>285</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>45</td>\n      <td>223</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n  </tbody>\n</table>\n<p>286 rows × 50 columns</p>\n</div>"},"metadata":{},"execution_count":42}]},{"source":"SELECT COUNT(*) AS total_records\nFROM students","metadata":{"customType":"sql","dataFrameVariableName":"df","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":48,"lastExecutedAt":1702075340950,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT COUNT(*) AS total_records\nFROM students","outputsMetadata":{"0":{"height":98,"type":"dataFrame"}}},"id":"ab01f727-3ae9-491a-bf8b-6d507e7dbf15","cell_type":"code","execution_count":43,"outputs":[{"output_type":"execute_result","data":{"application/com.datacamp.data-table.v2+json":{"table":{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"total_records","type":"integer"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":{"index":[0],"total_records":[286]}},"total_rows":1,"truncation_type":null},"text/plain":"   total_records\n0            286","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>total_records</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>286</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{},"execution_count":43}]},{"source":"SELECT inter_dom, \nCOUNT(*) AS count_inter_dom\nFROM students\nGROUP BY inter_dom","metadata":{"customType":"sql","dataFrameVariableName":"df1","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":56,"lastExecutedAt":1702075341006,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT inter_dom, \nCOUNT(*) AS count_inter_dom\nFROM students\nGROUP BY 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class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>inter_dom</th>\n      <th>count_inter_dom</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Inter</td>\n      <td>201</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Dom</td>\n      <td>67</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>None</td>\n      <td>18</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{},"execution_count":44}]},{"source":"SELECT * \nFROM students\nWHERE inter_dom = 'Inter'","metadata":{"customType":"sql","dataFrameVariableName":"df2","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":109,"lastExecutedAt":1702075341115,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT * \nFROM students\nWHERE inter_dom = 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No         No           No\n1       Inter    SEA    Male  ...       No         No           No\n2       Inter    SEA    Male  ...       No         No           No\n3       Inter     EA  Female  ...       No         No           No\n4       Inter     EA  Female  ...       No         No           No\n..        ...    ...     ...  ...      ...        ...          ...\n196     Inter    SEA    Male  ...      Yes         No           No\n197     Inter    SEA  Female  ...      Yes         No           No\n198     Inter    SEA  Female  ...       No         No           No\n199     Inter    SEA  Female  ...      Yes        Yes          Yes\n200     Inter     EA  Female  ...       No         No           No\n\n[201 rows x 50 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>inter_dom</th>\n      <th>region</th>\n      <th>gender</th>\n      <th>academic</th>\n      <th>age</th>\n      <th>age_cate</th>\n      <th>stay</th>\n      <th>stay_cate</th>\n      <th>japanese</th>\n      <th>japanese_cate</th>\n      <th>english</th>\n      <th>english_cate</th>\n      <th>intimate</th>\n      <th>religion</th>\n      <th>suicide</th>\n      <th>dep</th>\n      <th>deptype</th>\n      <th>todep</th>\n      <th>depsev</th>\n      <th>tosc</th>\n      <th>apd</th>\n      <th>ahome</th>\n      <th>aph</th>\n      <th>afear</th>\n      <th>acs</th>\n      <th>aguilt</th>\n      <th>amiscell</th>\n      <th>toas</th>\n      <th>partner</th>\n      <th>friends</th>\n      <th>parents</th>\n      <th>relative</th>\n      <th>profess</th>\n      <th>phone</th>\n      <th>doctor</th>\n      <th>reli</th>\n      <th>alone</th>\n      <th>others</th>\n      <th>internet</th>\n      <th>partner_bi</th>\n      <th>friends_bi</th>\n      <th>parents_bi</th>\n      <th>relative_bi</th>\n      <th>professional_bi</th>\n      <th>phone_bi</th>\n      <th>doctor_bi</th>\n      <th>religion_bi</th>\n      <th>alone_bi</th>\n      <th>others_bi</th>\n      <th>internet_bi</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Grad</td>\n      <td>24.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>Long</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>None</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>0.0</td>\n      <td>Min</td>\n      <td>34.0</td>\n      <td>23.0</td>\n      <td>9.0</td>\n      <td>11.0</td>\n      <td>8.0</td>\n      <td>11.0</td>\n      <td>2.0</td>\n      <td>27.0</td>\n      <td>91.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>6.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Grad</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>None</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>2.0</td>\n      <td>Min</td>\n      <td>48.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>10.0</td>\n      <td>39.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Grad</td>\n      <td>25.0</td>\n      <td>4.0</td>\n      <td>6.0</td>\n      <td>Long</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>2.0</td>\n      <td>Min</td>\n      <td>41.0</td>\n      <td>13.0</td>\n      <td>4.0</td>\n      <td>7.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>14.0</td>\n      <td>51.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Inter</td>\n      <td>EA</td>\n      <td>Female</td>\n      <td>Grad</td>\n      <td>29.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>2.0</td>\n      <td>Low</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>3.0</td>\n      <td>Min</td>\n      <td>37.0</td>\n      <td>16.0</td>\n      <td>10.0</td>\n      <td>10.0</td>\n      <td>8.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>21.0</td>\n      <td>75.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Inter</td>\n      <td>EA</td>\n      <td>Female</td>\n      <td>Grad</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>1.0</td>\n      <td>Low</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>3.0</td>\n      <td>Min</td>\n      <td>37.0</td>\n      <td>15.0</td>\n      <td>12.0</td>\n      <td>5.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>4.0</td>\n      <td>31.0</td>\n      <td>82.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</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      <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      <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>196</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Male</td>\n      <td>Under</td>\n      <td>21.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>Medium</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>6.0</td>\n      <td>Mild</td>\n      <td>37.0</td>\n      <td>23.0</td>\n      <td>8.0</td>\n      <td>11.0</td>\n      <td>8.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>22.0</td>\n      <td>82.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>4.0</td>\n      <td>2.0</td>\n      <td>4.0</td>\n      <td>2.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>197</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>20.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>2.0</td>\n      <td>Low</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>7.0</td>\n      <td>Mild</td>\n      <td>16.0</td>\n      <td>29.0</td>\n      <td>18.0</td>\n      <td>17.0</td>\n      <td>17.0</td>\n      <td>12.0</td>\n      <td>8.0</td>\n      <td>44.0</td>\n      <td>145.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>198</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>21.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>Medium</td>\n      <td>2.0</td>\n      <td>Low</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Major</td>\n      <td>16.0</td>\n      <td>ModSev</td>\n      <td>25.0</td>\n      <td>24.0</td>\n      <td>11.0</td>\n      <td>17.0</td>\n      <td>4.0</td>\n      <td>11.0</td>\n      <td>6.0</td>\n      <td>37.0</td>\n      <td>110.0</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>6.0</td>\n      <td>1.0</td>\n      <td>6.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>199</th>\n      <td>Inter</td>\n      <td>SEA</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>18.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>1.0</td>\n      <td>Low</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>8.0</td>\n      <td>Mild</td>\n      <td>38.0</td>\n      <td>11.0</td>\n      <td>12.0</td>\n      <td>10.0</td>\n      <td>4.0</td>\n      <td>7.0</td>\n      <td>4.0</td>\n      <td>20.0</td>\n      <td>68.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>200</th>\n      <td>Inter</td>\n      <td>EA</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>20.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>Medium</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>2.0</td>\n      <td>Min</td>\n      <td>47.0</td>\n      <td>9.0</td>\n      <td>8.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>8.0</td>\n      <td>3.0</td>\n      <td>19.0</td>\n      <td>57.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>6.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>201 rows × 50 columns</p>\n</div>"},"metadata":{},"execution_count":45}]},{"source":"SELECT *\nFROM students\nWHERE inter_dom = 'Dom'","metadata":{"customType":"sql","dataFrameVariableName":"df3","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":103,"lastExecutedAt":1702075341218,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT *\nFROM students\nWHERE inter_dom = 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  inter_dom region  gender academic  ...  religion_bi  alone_bi  others_bi internet_bi\n0        Dom    JAP  Female     Grad  ...          Yes        No         No          No\n1        Dom    JAP  Female    Under  ...           No        No         No          No\n2        Dom    JAP  Female    Under  ...           No        No         No          No\n3        Dom    JAP    Male    Under  ...           No        No         No          No\n4        Dom    JAP  Female    Under  ...           No        No         No          No\n..       ...    ...     ...      ...  ...          ...       ...        ...         ...\n62       Dom    JAP  Female    Under  ...           No        No         No         Yes\n63       Dom    JAP  Female    Under  ...           No        No         No          No\n64       Dom    JAP  Female    Under  ...           No        No         No          No\n65       Dom    JAP    Male    Under  ...           No        No         No          No\n66       Dom    JAP    Male    Under  ...           No       Yes         No          No\n\n[67 rows x 50 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>inter_dom</th>\n      <th>region</th>\n      <th>gender</th>\n      <th>academic</th>\n      <th>age</th>\n      <th>age_cate</th>\n      <th>stay</th>\n      <th>stay_cate</th>\n      <th>japanese</th>\n      <th>japanese_cate</th>\n      <th>english</th>\n      <th>english_cate</th>\n      <th>intimate</th>\n      <th>religion</th>\n      <th>suicide</th>\n      <th>dep</th>\n      <th>deptype</th>\n      <th>todep</th>\n      <th>depsev</th>\n      <th>tosc</th>\n      <th>apd</th>\n      <th>ahome</th>\n      <th>aph</th>\n      <th>afear</th>\n  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<td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Major</td>\n      <td>12.0</td>\n      <td>Mod</td>\n      <td>47.0</td>\n      <td>16.0</td>\n      <td>11.0</td>\n      <td>5.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>3.0</td>\n      <td>31.0</td>\n      <td>81.0</td>\n      <td>7.0</td>\n      <td>3.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>6.0</td>\n      <td>6.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>18.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>9.0</td>\n      <td>Mild</td>\n      <td>48.0</td>\n      <td>9.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>10.0</td>\n      <td>37.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>21.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>Medium</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>7.0</td>\n      <td>Mild</td>\n      <td>40.0</td>\n      <td>16.0</td>\n      <td>8.0</td>\n      <td>10.0</td>\n      <td>8.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>20.0</td>\n      <td>72.0</td>\n      <td>6.0</td>\n      <td>6.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Male</td>\n      <td>Under</td>\n      <td>20.0</td>\n      <td>2.0</td>\n      <td>3.0</td>\n      <td>Medium</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>1.0</td>\n      <td>Low</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>3.0</td>\n      <td>Min</td>\n      <td>47.0</td>\n      <td>11.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>12.0</td>\n      <td>43.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>21.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>Medium</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>1.0</td>\n      <td>Low</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Other</td>\n      <td>10.0</td>\n      <td>Mod</td>\n      <td>48.0</td>\n      <td>8.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>10.0</td>\n      <td>36.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</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      <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      <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>62</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>21.0</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>Long</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>8.0</td>\n      <td>Mild</td>\n      <td>27.0</td>\n      <td>16.0</td>\n      <td>9.0</td>\n      <td>10.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>4.0</td>\n      <td>20.0</td>\n      <td>74.0</td>\n      <td>1.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>6.0</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>63</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>22.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>Medium</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>4.0</td>\n      <td>High</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>2.0</td>\n      <td>Min</td>\n      <td>48.0</td>\n      <td>8.0</td>\n      <td>10.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>16.0</td>\n      <td>50.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>64</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Female</td>\n      <td>Under</td>\n      <td>19.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>9.0</td>\n      <td>Mild</td>\n      <td>47.0</td>\n      <td>8.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>13.0</td>\n      <td>43.0</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>6.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>7.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>65</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Male</td>\n      <td>Under</td>\n      <td>19.0</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>Short</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>1.0</td>\n      <td>Min</td>\n      <td>43.0</td>\n      <td>8.0</td>\n      <td>12.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>3.0</td>\n      <td>2.0</td>\n      <td>10.0</td>\n      <td>44.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>2.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>66</th>\n      <td>Dom</td>\n      <td>JAP</td>\n      <td>Male</td>\n      <td>Under</td>\n      <td>20.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>Medium</td>\n      <td>5.0</td>\n      <td>High</td>\n      <td>3.0</td>\n      <td>Average</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>7.0</td>\n      <td>Mild</td>\n      <td>41.0</td>\n      <td>14.0</td>\n      <td>4.0</td>\n      <td>10.0</td>\n      <td>7.0</td>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>19.0</td>\n      <td>61.0</td>\n      <td>5.0</td>\n      <td>6.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>6.0</td>\n      <td>1.0</td>\n      <td>3.0</td>\n      <td>Yes</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>No</td>\n      <td>Yes</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>67 rows × 50 columns</p>\n</div>"},"metadata":{},"execution_count":46}]},{"source":"SELECT *\nFROM students\nWHERE inter_dom IS NULL","metadata":{"customType":"sql","dataFrameVariableName":"df4","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":89,"lastExecutedAt":1702075341307,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT *\nFROM students\nWHERE inter_dom IS NULL","outputsMetadata":{"0":{"height":338,"type":"dataFrame"}}},"cell_type":"code","id":"8b73b2b8-f57d-4ccf-acc1-988c75964498","execution_count":47,"outputs":[{"output_type":"execute_result","data":{"application/com.datacamp.data-table.v2+json":{"table":{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"inter_dom","type":"string"},{"name":"region","type":"string"},{"name":"gender","type":"string"},{"name":"academic","type":"string"},{"name":"age","type":"number"},{"name":"age_cate","type":"number"},{"name":"stay","type":"number"},{"name":"stay_cate","type":"string"},{"name":"japanese","type":"number"},{"name":"japanese_cate","type":"string"},{"name":"english","type":"number"},{"name":"english_cate","type":"string"},{"name":"intimate","type":"string"},{"name":"religion","type":"string"},{"name":"suicide","type":"string"},{"name":"dep","type":"string"},{"name":"deptype","type":"string"},{"name":"todep","type":"number"},{"name":"depsev","type":"string"},{"name":"tosc","type":"number"},{"name":"apd","type":"number"},{"name":"ahome","type":"number"},{"name":"aph","type":"number"},{"name":"afear","type":"number"},{"name":"acs","type":"number"},{"name":"aguilt","type":"number"},{"name":"amiscell","type":"number"},{"name":"toas","type":"number"},{"name":"partner","type":"number"},{"name":"friends","type":"number"},{"name":"parents","type":"number"},{"name":"relative","type":"number"},{"name":"profess","type":"number"},{"name":"phone","type":"number"},{"name":"doctor","type":"number"},{"name":"reli","type":"number"},{"name":"alone","type":"number"},{"name":"others","type":"number"},{"name":"internet","type":"number"},{"name":"partner_bi","type":"string"},{"name":"friends_bi","type":"string"},{"name":"parents_bi","type":"string"},{"name":"relative_bi","type":"string"},{"name":"professional_bi","type":"string"},{"name":"phone_bi","type":"string"},{"name":"doctor_bi","type":"string"},{"name":"religion_bi","type":"string"},{"name":"alone_bi","type":"string"},{"name":"others_bi","type":"string"},{"name":"internet_bi","type":"string"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":{"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17],"inter_dom":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"region":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"gender":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"academic":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"age":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"age_cate":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"stay":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"stay_cate":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"japanese":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"japanese_cate":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"english":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"english_cate":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"intimate":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"religion":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"suicide":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"dep":[null,"96","172",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"deptype":[null,"42","54","172",null,null,null,null,null,null,null,null,null,null,null,null,null,null],"todep":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"depsev":[null,"65","107","73","15","8",null,null,null,null,null,null,null,null,null,null,null,null],"tosc":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"apd":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"ahome":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"aph":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"afear":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"acs":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"aguilt":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"amiscell":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"toas":[null,null,null,null,null,null,null,null,null,null,null,null,null,null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  inter_dom region gender academic  ...  religion_bi  alone_bi  others_bi internet_bi\n0       None   None   None     None  ...         None      None       None        None\n1       None   None   None     None  ...           19        65         21          45\n2       None   None   None     None  ...          249       203        247         223\n3       None   None   None     None  ...         None      None       None        None\n4       None   None   None     None  ...           19        65         21          45\n5       None   None   None     None  ...          249       203        247         223\n6       None   None   None     None  ...         None      None       None        None\n7       None   None   None     None  ...         None      None       None        None\n8       None   None   None     None  ...         None      None       None        None\n9       None   None   None     None  ...         None      None       None        None\n10      None   None   None     None  ...         None      None       None        None\n11      None   None   None     None  ...         None      None       None        None\n12      None   None   None     None  ...         None      None       None        None\n13      None   None   None     None  ...         None      None       None        None\n14      None   None   None     None  ...         None      None       None        None\n15      None   None   None     None  ...         None      None       None        None\n16      None   None   None     None  ...         None      None       None        None\n17      None   None   None     None  ...         None      None       None        None\n\n[18 rows x 50 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>inter_dom</th>\n      <th>region</th>\n      <th>gender</th>\n      <th>academic</th>\n      <th>age</th>\n      <th>age_cate</th>\n      <th>stay</th>\n      <th>stay_cate</th>\n      <th>japanese</th>\n      <th>japanese_cate</th>\n      <th>english</th>\n      <th>english_cate</th>\n      <th>intimate</th>\n      <th>religion</th>\n      <th>suicide</th>\n      <th>dep</th>\n      <th>deptype</th>\n      <th>todep</th>\n      <th>depsev</th>\n      <th>tosc</th>\n      <th>apd</th>\n      <th>ahome</th>\n      <th>aph</th>\n      <th>afear</th>\n      <th>acs</th>\n      <th>aguilt</th>\n      <th>amiscell</th>\n      <th>toas</th>\n      <th>partner</th>\n      <th>friends</th>\n      <th>parents</th>\n      <th>relative</th>\n      <th>profess</th>\n      <th>phone</th>\n      <th>doctor</th>\n      <th>reli</th>\n      <th>alone</th>\n      <th>others</th>\n      <th>internet</th>\n      <th>partner_bi</th>\n      <th>friends_bi</th>\n      <th>parents_bi</th>\n      <th>relative_bi</th>\n      <th>professional_bi</th>\n      <th>phone_bi</th>\n      <th>doctor_bi</th>\n      <th>religion_bi</th>\n      <th>alone_bi</th>\n      <th>others_bi</th>\n      <th>internet_bi</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      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<td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>96</td>\n      <td>42</td>\n      <td>NaN</td>\n      <td>65</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>145</td>\n      <td>128</td>\n      <td>137</td>\n      <td>66</td>\n      <td>61</td>\n      <td>30</td>\n      <td>46</td>\n      <td>19</td>\n      <td>65</td>\n      <td>21</td>\n      <td>45</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>172</td>\n      <td>54</td>\n      <td>NaN</td>\n      <td>107</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>123</td>\n      <td>140</td>\n      <td>131</td>\n      <td>202</td>\n      <td>207</td>\n      <td>238</td>\n      <td>222</td>\n      <td>249</td>\n      <td>203</td>\n      <td>247</td>\n      <td>223</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      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<td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>145</td>\n      <td>123</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>128</td>\n      <td>140</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>137</td>\n      <td>131</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>66</td>\n      <td>202</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>61</td>\n      <td>207</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>30</td>\n      <td>238</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>46</td>\n      <td>222</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>19</td>\n      <td>249</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>65</td>\n      <td>203</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>21</td>\n      <td>247</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>45</td>\n      <td>223</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n      <td>None</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{},"execution_count":47}]},{"source":"SELECT inter_dom,\n\t   ROUND(MIN(todep), 2) AS min_phq,\n\t   ROUND(MAX(todep), 2) AS max_phq,\n\t   ROUND(AVG(todep), 2) AS avg_phq,\n\t   ROUND(MIN(tosc), 2) AS min_scs,\n\t   ROUND(MAX(tosc), 2) AS max_scs,\n\t   ROUND(AVG(tosc), 2) AS avg_scs,\n\t   ROUND(MIN(toas), 2) AS min_as,\n\t   ROUND(MAX(toas), 2) AS max_as,\n\t   ROUND(AVG(toas), 2) AS avg_as\nFROM students\nGROUP BY inter_dom","metadata":{"customType":"sql","dataFrameVariableName":"df5","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":63,"lastExecutedAt":1702075341370,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT inter_dom,\n\t   ROUND(MIN(todep), 2) AS min_phq,\n\t   ROUND(MAX(todep), 2) AS max_phq,\n\t   ROUND(AVG(todep), 2) AS avg_phq,\n\t   ROUND(MIN(tosc), 2) AS min_scs,\n\t   ROUND(MAX(tosc), 2) AS max_scs,\n\t   ROUND(AVG(tosc), 2) AS avg_scs,\n\t   ROUND(MIN(toas), 2) AS min_as,\n\t   ROUND(MAX(toas), 2) AS max_as,\n\t   ROUND(AVG(toas), 2) AS avg_as\nFROM students\nGROUP BY inter_dom","outputsMetadata":{"0":{"height":163,"type":"dataFrame"}}},"cell_type":"code","id":"9fad2355-c57b-4225-8387-ef21933e846f","execution_count":48,"outputs":[{"output_type":"execute_result","data":{"application/com.datacamp.data-table.v2+json":{"table":{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"inter_dom","type":"string"},{"name":"min_phq","type":"number"},{"name":"max_phq","type":"number"},{"name":"avg_phq","type":"number"},{"name":"min_scs","type":"number"},{"name":"max_scs","type":"number"},{"name":"avg_scs","type":"number"},{"name":"min_as","type":"number"},{"name":"max_as","type":"number"},{"name":"avg_as","type":"number"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":{"index":[0,1,2],"inter_dom":["Inter","Dom",null],"min_phq":[0,0,null],"max_phq":[25,23,null],"avg_phq":[8.04,8.61,null],"min_scs":[11,8,null],"max_scs":[48,48,null],"avg_scs":[37.42,37.64,null],"min_as":[36,36,null],"max_as":[145,112,null],"avg_as":[75.56,62.84,null]}},"total_rows":3,"truncation_type":null},"text/plain":"  inter_dom  min_phq  max_phq  avg_phq  ...  avg_scs  min_as  max_as  avg_as\n0     Inter      0.0     25.0     8.04  ...    37.42    36.0   145.0   75.56\n1       Dom      0.0     23.0     8.61  ...    37.64    36.0   112.0   62.84\n2      None      NaN      NaN      NaN  ...      NaN     NaN     NaN     NaN\n\n[3 rows x 10 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>inter_dom</th>\n      <th>min_phq</th>\n      <th>max_phq</th>\n      <th>avg_phq</th>\n      <th>min_scs</th>\n      <th>max_scs</th>\n      <th>avg_scs</th>\n      <th>min_as</th>\n      <th>max_as</th>\n      <th>avg_as</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Inter</td>\n      <td>0.0</td>\n      <td>25.0</td>\n      <td>8.04</td>\n      <td>11.0</td>\n      <td>48.0</td>\n      <td>37.42</td>\n      <td>36.0</td>\n      <td>145.0</td>\n      <td>75.56</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Dom</td>\n      <td>0.0</td>\n      <td>23.0</td>\n      <td>8.61</td>\n      <td>8.0</td>\n      <td>48.0</td>\n      <td>37.64</td>\n      <td>36.0</td>\n      <td>112.0</td>\n      <td>62.84</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>None</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{},"execution_count":48}]},{"source":"SELECT *\nFROM df5\nWHERE inter_dom = 'Inter'","metadata":{"customType":"sql","dataFrameVariableName":"df6","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":52,"lastExecutedAt":1702075341422,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT *\nFROM df5\nWHERE inter_dom = 'Inter'","outputsMetadata":{"0":{"height":113,"type":"dataFrame"}}},"cell_type":"code","id":"05358338-7d69-402d-8972-d05bb488571c","execution_count":49,"outputs":[{"output_type":"execute_result","data":{"application/com.datacamp.data-table.v2+json":{"table":{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"inter_dom","type":"string"},{"name":"min_phq","type":"number"},{"name":"max_phq","type":"number"},{"name":"avg_phq","type":"number"},{"name":"min_scs","type":"number"},{"name":"max_scs","type":"number"},{"name":"avg_scs","type":"number"},{"name":"min_as","type":"number"},{"name":"max_as","type":"number"},{"name":"avg_as","type":"number"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":{"index":[0],"inter_dom":["Inter"],"min_phq":[0],"max_phq":[25],"avg_phq":[8.04],"min_scs":[11],"max_scs":[48],"avg_scs":[37.42],"min_as":[36],"max_as":[145],"avg_as":[75.56]}},"total_rows":1,"truncation_type":null},"text/plain":"  inter_dom  min_phq  max_phq  avg_phq  ...  avg_scs  min_as  max_as  avg_as\n0     Inter      0.0     25.0     8.04  ...    37.42    36.0   145.0   75.56\n\n[1 rows x 10 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>inter_dom</th>\n      <th>min_phq</th>\n      <th>max_phq</th>\n      <th>avg_phq</th>\n      <th>min_scs</th>\n      <th>max_scs</th>\n      <th>avg_scs</th>\n      <th>min_as</th>\n      <th>max_as</th>\n      <th>avg_as</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Inter</td>\n      <td>0.0</td>\n      <td>25.0</td>\n      <td>8.04</td>\n      <td>11.0</td>\n      <td>48.0</td>\n      <td>37.42</td>\n      <td>36.0</td>\n      <td>145.0</td>\n      <td>75.56</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{},"execution_count":49}]},{"source":"SELECT stay, \n       ROUND(AVG(todep), 2) AS average_phq, \n       ROUND(AVG(tosc), 2) AS average_scs, \n       ROUND(AVG(toas), 2) AS average_as\nFROM students\nWHERE inter_dom = 'Inter'\nGROUP BY stay\nORDER BY stay DESC;","metadata":{"customType":"sql","dataFrameVariableName":"df","sqlCellMode":"dataFrame","sqlSource":{"type":"dataframesAndCsvs"},"executionCancelledAt":null,"executionTime":56,"lastExecutedAt":1702075341478,"lastScheduledRunId":null,"lastSuccessfullyExecutedCode":"SELECT stay, \n       ROUND(AVG(todep), 2) AS average_phq, \n       ROUND(AVG(tosc), 2) AS average_scs, \n       ROUND(AVG(toas), 2) AS average_as\nFROM students\nWHERE inter_dom = 'Inter'\nGROUP BY stay\nORDER BY stay DESC;","outputsMetadata":{"0":{"height":298,"type":"dataFrame"}}},"cell_type":"code","id":"0ddb17c2-1f5a-4c7e-ac78-3b1047517ecf","execution_count":50,"outputs":[{"output_type":"execute_result","data":{"application/com.datacamp.data-table.v2+json":{"table":{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"stay","type":"number"},{"name":"average_phq","type":"number"},{"name":"average_scs","type":"number"},{"name":"average_as","type":"number"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":{"index":[0,1,2,3,4,5,6,7,8],"stay":[10,8,7,6,5,4,3,2,1],"average_phq":[13,10,4,6,0,8.57,9.09,8.28,7.48],"average_scs":[32,44,48,38,34,33.93,37.13,37.08,38.11],"average_as":[50,65,45,58.67,91,87.71,78,77.67,72.8]}},"total_rows":9,"truncation_type":null},"text/plain":"   stay  average_phq  average_scs  average_as\n0  10.0        13.00        32.00       50.00\n1   8.0        10.00        44.00       65.00\n2   7.0         4.00        48.00       45.00\n3   6.0         6.00        38.00       58.67\n4   5.0         0.00        34.00       91.00\n5   4.0         8.57        33.93       87.71\n6   3.0         9.09        37.13       78.00\n7   2.0         8.28        37.08       77.67\n8   1.0         7.48        38.11       72.80","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>stay</th>\n      <th>average_phq</th>\n      <th>average_scs</th>\n      <th>average_as</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>10.0</td>\n      <td>13.00</td>\n      <td>32.00</td>\n      <td>50.00</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>8.0</td>\n      <td>10.00</td>\n      <td>44.00</td>\n      <td>65.00</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>7.0</td>\n      <td>4.00</td>\n      <td>48.00</td>\n      <td>45.00</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>6.0</td>\n      <td>6.00</td>\n      <td>38.00</td>\n      <td>58.67</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5.0</td>\n      <td>0.00</td>\n      <td>34.00</td>\n      <td>91.00</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>4.0</td>\n      <td>8.57</td>\n      <td>33.93</td>\n      <td>87.71</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>3.0</td>\n      <td>9.09</td>\n      <td>37.13</td>\n      <td>78.00</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2.0</td>\n      <td>8.28</td>\n      <td>37.08</td>\n      <td>77.67</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1.0</td>\n      <td>7.48</td>\n      <td>38.11</td>\n      <td>72.80</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{},"execution_count":50}]}],"metadata":{"colab":{"name":"Welcome to DataCamp Workspaces.ipynb","provenance":[]},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.8.10"}},"nbformat":4,"nbformat_minor":5}