notebooks/the-data-science-helper.ipynb

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                "import pandas as pd\n\nurl = \"https://data.cityofberkeley.info/resource/bscu-qpbu.json\"\n\n# Load the data into a DataFrame\ndata = pd.read_json(url)\n\ndata.head()"
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                "OUTPUT:\n## Dataframe Summary\n\nNumber of Rows: 5\n\nNumber of Columns: 23\n\n### Column Information\n\n|    | Column Name                 | Data Type   |   Missing Values |   % Missing |\n|----|-----------------------------|-------------|------------------|-------------|\n|  0 | case_id                     | int64       |                0 |           0 |\n|  1 | date_opened                 | object      |                0 |           0 |\n|  2 | case_status                 | object      |                0 |           0 |\n|  3 | date_closed                 | object      |                1 |          20 |\n|  4 | request_category            | object      |                0 |           0 |\n|  5 | request_subcategory         | object      |                0 |           0 |\n|  6 | request_detail              | object      |                0 |           0 |\n|  7 | object_type                 | object      |                0 |           0 |\n|  8 | street_address              | object      |                2 |          40 |\n|  9 | city                        | object      |                0 |           0 |\n| 10 | state                       | object      |                0 |           0 |\n| 11 | neighborhood                | object      |                0 |           0 |\n| 12 | apn                         | object      |                3 |          60 |\n| 13 | latitude                    | float64     |                3 |          60 |\n| 14 | longitude                   | float64     |                3 |          60 |\n| 15 | location                    | object      |                3 |          60 |\n| 16 | :@computed_region_b3wi_w8ix | float64     |                3 |          60 |\n| 17 | :@computed_region_fhmw_rucx | float64     |                3 |          60 |\n| 18 | :@computed_region_u3y2_d2ws | float64     |                3 |          60 |\n| 19 | :@computed_region_5s6d_2f32 | float64     |                3 |          60 |\n| 20 | :@computed_region_3ini_iehf | float64     |                3 |          60 |\n| 21 | :@computed_region_5bih_7r3y | float64     |                3 |          60 |\n| 22 | :@computed_region_x3q3_gi3e | float64     |                3 |          60 |\n\n### Categorical Summary\n\n| Column Name   |\n|---------------|\n\n### Sample Data (5x16)\n\n|    | object_type   | neighborhood   | request_subcategory            | request_category                             | state   | date_opened             |   latitude |      case_id | case_status   | location                                                                                                                          | date_closed             | city     | request_detail                | apn           |   longitude | street_address                                     |\n|----|---------------|----------------|--------------------------------|----------------------------------------------|---------|-------------------------|------------|--------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------|-------------------------|----------|-------------------------------|---------------|-------------|----------------------------------------------------|\n|  1 | Property      | Berkeley       | Residential                    | Refuse and Recycling                         | CA      | 2021-09-13T10:50:00.000 |    37.8627 | 121000876647 | Open          | {'latitude': '37.86265624', 'longitude': '-122.27546088', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | nan                     | Berkeley | Residential Bulky Pickup      | 054 180702800 |    -122.275 | 1722 DWIGHT WAY                                    |\n|  0 | Property      | Berkeley       | Parks/Marina Building Services | Facilities, Electrical & Property Management | CA      | 2021-09-16T06:23:23.000 |   nan      | 121000877593 | Closed        | nan                                                                                                                               | 2021-09-20T11:22:22.000 | Berkeley | Keys / Locks                  | nan           |     nan     | Intersection of Browning and Addison, BERKELEY, CA |\n|  4 | Individual    | Berkeley       | Marina                         | Other Account Services and Billing           | CA      | 2020-09-01T11:32:00.000 |   nan      | 121000793663 | Closed        | nan                                                                                                                               | 2020-09-01T11:36:00.000 | Berkeley | Payment Collection - Marina   | nan           |     nan     | nan                                                |\n|  2 | Individual    | Berkeley       | Miscellaneous                  | General Questions/information                | CA      | 2020-11-06T16:51:00.000 |   nan      | 121000809740 | Closed        | nan                                                                                                                               | 2020-11-09T01:52:57.000 | Berkeley | Miscellaneous Service Request | nan           |     nan     | nan                                                |\n|  3 | Property      | Berkeley       | Miscellaneous                  | General Questions/information                | CA      | 2020-11-06T16:38:00.000 |    37.8848 | 121000809739 | Closed        | {'latitude': '37.88479918', 'longitude': '-122.24787412', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | 2020-11-09T01:41:12.000 | Berkeley | Miscellaneous Service Request | 060 249305600 |    -122.248 | 1411 GRIZZLY PEAK BLVD                             |"
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       "<div><style>.chatlab-chat-details summary &gt; *  { display: inline; color: #27374D; }</style><details style=\"background: #DDE6ED; border-radius: 5px; padding: .5rem 1rem\" className=\"chatlab-chat-details\"><summary style=\"color: #27374D; cursor: pointer\"><span style=\"color: #9DB2BF; padding-left: 5px; padding-right: 5px\">𝑓</span><span style=\"color: #27374D; padding-left: 5px; padding-right: 5px\">Ran</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\">python</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\"></span></summary><div style=\"margin-left: 10px; margin-top: 10px\"><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Input:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\">import pandas as pd\n",
       "\n",
       "url = &quot;https://data.cityofberkeley.info/resource/bscu-qpbu.json&quot;\n",
       "\n",
       "# Load the data into a DataFrame\n",
       "data = pd.read_json(url)\n",
       "\n",
       "data.head()</div></div><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Output:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\">OUTPUT:\n",
       "## Dataframe Summary\n",
       "\n",
       "Number of Rows: 5\n",
       "\n",
       "Number of Columns: 23\n",
       "\n",
       "### Column Information\n",
       "\n",
       "|    | Column Name                 | Data Type   |   Missing Values |   % Missing |\n",
       "|----|-----------------------------|-------------|------------------|-------------|\n",
       "|  0 | case_id                     | int64       |                0 |           0 |\n",
       "|  1 | date_opened                 | object      |                0 |           0 |\n",
       "|  2 | case_status                 | object      |                0 |           0 |\n",
       "|  3 | date_closed                 | object      |                1 |          20 |\n",
       "|  4 | request_category            | object      |                0 |           0 |\n",
       "|  5 | request_subcategory         | object      |                0 |           0 |\n",
       "|  6 | request_detail              | object      |                0 |           0 |\n",
       "|  7 | object_type                 | object      |                0 |           0 |\n",
       "|  8 | street_address              | object      |                2 |          40 |\n",
       "|  9 | city                        | object      |                0 |           0 |\n",
       "| 10 | state                       | object      |                0 |           0 |\n",
       "| 11 | neighborhood                | object      |                0 |           0 |\n",
       "| 12 | apn                         | object      |                3 |          60 |\n",
       "| 13 | latitude                    | float64     |                3 |          60 |\n",
       "| 14 | longitude                   | float64     |                3 |          60 |\n",
       "| 15 | location                    | object      |                3 |          60 |\n",
       "| 16 | :@computed_region_b3wi_w8ix | float64     |                3 |          60 |\n",
       "| 17 | :@computed_region_fhmw_rucx | float64     |                3 |          60 |\n",
       "| 18 | :@computed_region_u3y2_d2ws | float64     |                3 |          60 |\n",
       "| 19 | :@computed_region_5s6d_2f32 | float64     |                3 |          60 |\n",
       "| 20 | :@computed_region_3ini_iehf | float64     |                3 |          60 |\n",
       "| 21 | :@computed_region_5bih_7r3y | float64     |                3 |          60 |\n",
       "| 22 | :@computed_region_x3q3_gi3e | float64     |                3 |          60 |\n",
       "\n",
       "### Categorical Summary\n",
       "\n",
       "| Column Name   |\n",
       "|---------------|\n",
       "\n",
       "### Sample Data (5x16)\n",
       "\n",
       "|    | object_type   | neighborhood   | request_subcategory            | request_category                             | state   | date_opened             |   latitude |      case_id | case_status   | location                                                                                                                          | date_closed             | city     | request_detail                | apn           |   longitude | street_address                                     |\n",
       "|----|---------------|----------------|--------------------------------|----------------------------------------------|---------|-------------------------|------------|--------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------|-------------------------|----------|-------------------------------|---------------|-------------|----------------------------------------------------|\n",
       "|  1 | Property      | Berkeley       | Residential                    | Refuse and Recycling                         | CA      | 2021-09-13T10:50:00.000 |    37.8627 | 121000876647 | Open          | {&#x27;latitude&#x27;: &#x27;37.86265624&#x27;, &#x27;longitude&#x27;: &#x27;-122.27546088&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;} | nan                     | Berkeley | Residential Bulky Pickup      | 054 180702800 |    -122.275 | 1722 DWIGHT WAY                                    |\n",
       "|  0 | Property      | Berkeley       | Parks/Marina Building Services | Facilities, Electrical &amp; Property Management | CA      | 2021-09-16T06:23:23.000 |   nan      | 121000877593 | Closed        | nan                                                                                                                               | 2021-09-20T11:22:22.000 | Berkeley | Keys / Locks                  | nan           |     nan     | Intersection of Browning and Addison, BERKELEY, CA |\n",
       "|  4 | Individual    | Berkeley       | Marina                         | Other Account Services and Billing           | CA      | 2020-09-01T11:32:00.000 |   nan      | 121000793663 | Closed        | nan                                                                                                                               | 2020-09-01T11:36:00.000 | Berkeley | Payment Collection - Marina   | nan           |     nan     | nan                                                |\n",
       "|  2 | Individual    | Berkeley       | Miscellaneous                  | General Questions/information                | CA      | 2020-11-06T16:51:00.000 |   nan      | 121000809740 | Closed        | nan                                                                                                                               | 2020-11-09T01:52:57.000 | Berkeley | Miscellaneous Service Request | nan           |     nan     | nan                                                |\n",
       "|  3 | Property      | Berkeley       | Miscellaneous                  | General Questions/information                | CA      | 2020-11-06T16:38:00.000 |    37.8848 | 121000809739 | Closed        | {&#x27;latitude&#x27;: &#x27;37.88479918&#x27;, &#x27;longitude&#x27;: &#x27;-122.24787412&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;} | 2020-11-09T01:41:12.000 | Berkeley | Miscellaneous Service Request | 060 249305600 |    -122.248 | 1411 GRIZZLY PEAK BLVD                             |</div></div></div></details></div>"
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       "      <th></th>\n",
       "      <th>case_id</th>\n",
       "      <th>date_opened</th>\n",
       "      <th>case_status</th>\n",
       "      <th>date_closed</th>\n",
       "      <th>request_category</th>\n",
       "      <th>request_subcategory</th>\n",
       "      <th>request_detail</th>\n",
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       "      <th>street_address</th>\n",
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       "      <th>...</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>location</th>\n",
       "      <th>:@computed_region_b3wi_w8ix</th>\n",
       "      <th>:@computed_region_fhmw_rucx</th>\n",
       "      <th>:@computed_region_u3y2_d2ws</th>\n",
       "      <th>:@computed_region_5s6d_2f32</th>\n",
       "      <th>:@computed_region_3ini_iehf</th>\n",
       "      <th>:@computed_region_5bih_7r3y</th>\n",
       "      <th>:@computed_region_x3q3_gi3e</th>\n",
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       "      <th>0</th>\n",
       "      <td>121000877593</td>\n",
       "      <td>2021-09-16T06:23:23.000</td>\n",
       "      <td>Closed</td>\n",
       "      <td>2021-09-20T11:22:22.000</td>\n",
       "      <td>Facilities, Electrical &amp; Property Management</td>\n",
       "      <td>Parks/Marina Building Services</td>\n",
       "      <td>Keys / Locks</td>\n",
       "      <td>Property</td>\n",
       "      <td>Intersection of Browning and Addison, BERKELEY...</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>121000876647</td>\n",
       "      <td>2021-09-13T10:50:00.000</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Residential Bulky Pickup</td>\n",
       "      <td>Property</td>\n",
       "      <td>1722 DWIGHT WAY</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>37.862656</td>\n",
       "      <td>-122.275461</td>\n",
       "      <td>{'latitude': '37.86265624', 'longitude': '-122...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>610.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1495.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>121000809740</td>\n",
       "      <td>2020-11-06T16:51:00.000</td>\n",
       "      <td>Closed</td>\n",
       "      <td>2020-11-09T01:52:57.000</td>\n",
       "      <td>General Questions/information</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Miscellaneous Service Request</td>\n",
       "      <td>Individual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>121000809739</td>\n",
       "      <td>2020-11-06T16:38:00.000</td>\n",
       "      <td>Closed</td>\n",
       "      <td>2020-11-09T01:41:12.000</td>\n",
       "      <td>General Questions/information</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Miscellaneous Service Request</td>\n",
       "      <td>Property</td>\n",
       "      <td>1411 GRIZZLY PEAK BLVD</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>37.884799</td>\n",
       "      <td>-122.247874</td>\n",
       "      <td>{'latitude': '37.88479918', 'longitude': '-122...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1327.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>121000793663</td>\n",
       "      <td>2020-09-01T11:32:00.000</td>\n",
       "      <td>Closed</td>\n",
       "      <td>2020-09-01T11:36:00.000</td>\n",
       "      <td>Other Account Services and Billing</td>\n",
       "      <td>Marina</td>\n",
       "      <td>Payment Collection - Marina</td>\n",
       "      <td>Individual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 23 columns</p>\n",
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       "## Dataframe Summary\n",
       "\n",
       "Number of Rows: 5\n",
       "\n",
       "Number of Columns: 23\n",
       "\n",
       "### Column Information\n",
       "\n",
       "|    | Column Name                 | Data Type   |   Missing Values |   % Missing |\n",
       "|----|-----------------------------|-------------|------------------|-------------|\n",
       "|  0 | case_id                     | int64       |                0 |           0 |\n",
       "|  1 | date_opened                 | object      |                0 |           0 |\n",
       "|  2 | case_status                 | object      |                0 |           0 |\n",
       "|  3 | date_closed                 | object      |                1 |          20 |\n",
       "|  4 | request_category            | object      |                0 |           0 |\n",
       "|  5 | request_subcategory         | object      |                0 |           0 |\n",
       "|  6 | request_detail              | object      |                0 |           0 |\n",
       "|  7 | object_type                 | object      |                0 |           0 |\n",
       "|  8 | street_address              | object      |                2 |          40 |\n",
       "|  9 | city                        | object      |                0 |           0 |\n",
       "| 10 | state                       | object      |                0 |           0 |\n",
       "| 11 | neighborhood                | object      |                0 |           0 |\n",
       "| 12 | apn                         | object      |                3 |          60 |\n",
       "| 13 | latitude                    | float64     |                3 |          60 |\n",
       "| 14 | longitude                   | float64     |                3 |          60 |\n",
       "| 15 | location                    | object      |                3 |          60 |\n",
       "| 16 | :@computed_region_b3wi_w8ix | float64     |                3 |          60 |\n",
       "| 17 | :@computed_region_fhmw_rucx | float64     |                3 |          60 |\n",
       "| 18 | :@computed_region_u3y2_d2ws | float64     |                3 |          60 |\n",
       "| 19 | :@computed_region_5s6d_2f32 | float64     |                3 |          60 |\n",
       "| 20 | :@computed_region_3ini_iehf | float64     |                3 |          60 |\n",
       "| 21 | :@computed_region_5bih_7r3y | float64     |                3 |          60 |\n",
       "| 22 | :@computed_region_x3q3_gi3e | float64     |                3 |          60 |\n",
       "\n",
       "### Categorical Summary\n",
       "\n",
       "| Column Name   |\n",
       "|---------------|\n",
       "\n",
       "### Sample Data (5x16)\n",
       "\n",
       "|    | object_type   | neighborhood   | request_subcategory            | request_category                             | state   | date_opened             |   latitude |      case_id | case_status   | location                                                                                                                          | date_closed             | city     | request_detail                | apn           |   longitude | street_address                                     |\n",
       "|----|---------------|----------------|--------------------------------|----------------------------------------------|---------|-------------------------|------------|--------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------|-------------------------|----------|-------------------------------|---------------|-------------|----------------------------------------------------|\n",
       "|  1 | Property      | Berkeley       | Residential                    | Refuse and Recycling                         | CA      | 2021-09-13T10:50:00.000 |    37.8627 | 121000876647 | Open          | {'latitude': '37.86265624', 'longitude': '-122.27546088', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | nan                     | Berkeley | Residential Bulky Pickup      | 054 180702800 |    -122.275 | 1722 DWIGHT WAY                                    |\n",
       "|  0 | Property      | Berkeley       | Parks/Marina Building Services | Facilities, Electrical & Property Management | CA      | 2021-09-16T06:23:23.000 |   nan      | 121000877593 | Closed        | nan                                                                                                                               | 2021-09-20T11:22:22.000 | Berkeley | Keys / Locks                  | nan           |     nan     | Intersection of Browning and Addison, BERKELEY, CA |\n",
       "|  4 | Individual    | Berkeley       | Marina                         | Other Account Services and Billing           | CA      | 2020-09-01T11:32:00.000 |   nan      | 121000793663 | Closed        | nan                                                                                                                               | 2020-09-01T11:36:00.000 | Berkeley | Payment Collection - Marina   | nan           |     nan     | nan                                                |\n",
       "|  2 | Individual    | Berkeley       | Miscellaneous                  | General Questions/information                | CA      | 2020-11-06T16:51:00.000 |   nan      | 121000809740 | Closed        | nan                                                                                                                               | 2020-11-09T01:52:57.000 | Berkeley | Miscellaneous Service Request | nan           |     nan     | nan                                                |\n",
       "|  3 | Property      | Berkeley       | Miscellaneous                  | General Questions/information                | CA      | 2020-11-06T16:38:00.000 |    37.8848 | 121000809739 | Closed        | {'latitude': '37.88479918', 'longitude': '-122.24787412', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | 2020-11-09T01:41:12.000 | Berkeley | Miscellaneous Service Request | 060 249305600 |    -122.248 | 1411 GRIZZLY PEAK BLVD                             |"
      ],
      "text/plain": [
       "        case_id              date_opened case_status              date_closed  \\\n",
       "0  121000877593  2021-09-16T06:23:23.000      Closed  2021-09-20T11:22:22.000   \n",
       "1  121000876647  2021-09-13T10:50:00.000        Open                      NaN   \n",
       "2  121000809740  2020-11-06T16:51:00.000      Closed  2020-11-09T01:52:57.000   \n",
       "3  121000809739  2020-11-06T16:38:00.000      Closed  2020-11-09T01:41:12.000   \n",
       "4  121000793663  2020-09-01T11:32:00.000      Closed  2020-09-01T11:36:00.000   \n",
       "\n",
       "                               request_category  \\\n",
       "0  Facilities, Electrical & Property Management   \n",
       "1                          Refuse and Recycling   \n",
       "2                 General Questions/information   \n",
       "3                 General Questions/information   \n",
       "4            Other Account Services and Billing   \n",
       "\n",
       "              request_subcategory                 request_detail object_type  \\\n",
       "0  Parks/Marina Building Services                   Keys / Locks    Property   \n",
       "1                     Residential       Residential Bulky Pickup    Property   \n",
       "2                   Miscellaneous  Miscellaneous Service Request  Individual   \n",
       "3                   Miscellaneous  Miscellaneous Service Request    Property   \n",
       "4                          Marina    Payment Collection - Marina  Individual   \n",
       "\n",
       "                                      street_address      city  ...  \\\n",
       "0  Intersection of Browning and Addison, BERKELEY...  Berkeley  ...   \n",
       "1                                    1722 DWIGHT WAY  Berkeley  ...   \n",
       "2                                                NaN  Berkeley  ...   \n",
       "3                             1411 GRIZZLY PEAK BLVD  Berkeley  ...   \n",
       "4                                                NaN  Berkeley  ...   \n",
       "\n",
       "    latitude   longitude                                           location  \\\n",
       "0        NaN         NaN                                                NaN   \n",
       "1  37.862656 -122.275461  {'latitude': '37.86265624', 'longitude': '-122...   \n",
       "2        NaN         NaN                                                NaN   \n",
       "3  37.884799 -122.247874  {'latitude': '37.88479918', 'longitude': '-122...   \n",
       "4        NaN         NaN                                                NaN   \n",
       "\n",
       "   :@computed_region_b3wi_w8ix  :@computed_region_fhmw_rucx  \\\n",
       "0                          NaN                          NaN   \n",
       "1                          2.0                        610.0   \n",
       "2                          NaN                          NaN   \n",
       "3                          6.0                       1327.0   \n",
       "4                          NaN                          NaN   \n",
       "\n",
       "  :@computed_region_u3y2_d2ws  :@computed_region_5s6d_2f32  \\\n",
       "0                         NaN                          NaN   \n",
       "1                         2.0                       1495.0   \n",
       "2                         NaN                          NaN   \n",
       "3                         6.0                       1500.0   \n",
       "4                         NaN                          NaN   \n",
       "\n",
       "   :@computed_region_3ini_iehf  :@computed_region_5bih_7r3y  \\\n",
       "0                          NaN                          NaN   \n",
       "1                         10.0                         33.0   \n",
       "2                          NaN                          NaN   \n",
       "3                          1.0                          5.0   \n",
       "4                          NaN                          NaN   \n",
       "\n",
       "   :@computed_region_x3q3_gi3e  \n",
       "0                          NaN  \n",
       "1                          7.0  \n",
       "2                          NaN  \n",
       "3                          4.0  \n",
       "4                          NaN  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
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                "# Getting the number of open tickets per category and subcategory\r\nopen_tickets = data[data[\"case_status\"] == \"Open\"]\r\nopen_tickets_per_category_subcategory = open_tickets.groupby([\"request_category\", \"request_subcategory\"]).size()\r\nopen_tickets_per_category_subcategory"
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                "OUTPUT:\n## Series Summary\n\nNumber of Values: 11\n\nData Type: int64\n\nMissing Values: 0 (0.00%)\n\n### Summary Statistics\n\n|    |   count |    mean |     std |   min |   25% |   50% |   75% |   max |\n|----|---------|---------|---------|-------|-------|-------|-------|-------|\n|  0 |      11 | 6.09091 | 9.79239 |     1 |     1 |     2 |   3.5 |    29 |\n\n### Sample Data (11)\n\n|                                                                                    |   0 |\n|------------------------------------------------------------------------------------|-----|\n| ('Streets, Utilities, and Transportation', 'Storm')                                |   2 |\n| ('Streets, Utilities, and Transportation', 'Sidewalk/Street Maintenance')          |   2 |\n| ('Graffiti and Vandalism', 'Graffiti')                                             |   1 |\n| ('Facilities, Electrical & Property Management', 'Parks/Marina Building Services') |   1 |\n| ('Streets, Utilities, and Transportation', 'Traffic Maintenance')                  |   2 |\n| ('Streets, Utilities, and Transportation', 'Clean City Program')                   |   1 |\n| ('Refuse and Recycling', 'Commercial')                                             |  22 |\n| ('Refuse and Recycling', 'Residential')                                            |  29 |\n| ('Parks, Trees and Vegetation', 'Landscape Maintenance')                           |   1 |\n| ('Traffic and Transportation', 'Signage')                                          |   1 |\n| ('General Questions/information', 'Miscellaneous')                                 |   5 |"
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       "<div><style>.chatlab-chat-details summary &gt; *  { display: inline; color: #27374D; }</style><details style=\"background: #DDE6ED; border-radius: 5px; padding: .5rem 1rem\" className=\"chatlab-chat-details\"><summary style=\"color: #27374D; cursor: pointer\"><span style=\"color: #9DB2BF; padding-left: 5px; padding-right: 5px\">𝑓</span><span style=\"color: #27374D; padding-left: 5px; padding-right: 5px\">Ran</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\">python</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\"></span></summary><div style=\"margin-left: 10px; margin-top: 10px\"><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Input:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\"># Getting the number of open tickets per category and subcategory\r\n",
       "open_tickets = data[data[&quot;case_status&quot;] == &quot;Open&quot;]\r\n",
       "open_tickets_per_category_subcategory = open_tickets.groupby([&quot;request_category&quot;, &quot;request_subcategory&quot;]).size()\r\n",
       "open_tickets_per_category_subcategory</div></div><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Output:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\">OUTPUT:\n",
       "## Series Summary\n",
       "\n",
       "Number of Values: 11\n",
       "\n",
       "Data Type: int64\n",
       "\n",
       "Missing Values: 0 (0.00%)\n",
       "\n",
       "### Summary Statistics\n",
       "\n",
       "|    |   count |    mean |     std |   min |   25% |   50% |   75% |   max |\n",
       "|----|---------|---------|---------|-------|-------|-------|-------|-------|\n",
       "|  0 |      11 | 6.09091 | 9.79239 |     1 |     1 |     2 |   3.5 |    29 |\n",
       "\n",
       "### Sample Data (11)\n",
       "\n",
       "|                                                                                    |   0 |\n",
       "|------------------------------------------------------------------------------------|-----|\n",
       "| (&#x27;Streets, Utilities, and Transportation&#x27;, &#x27;Storm&#x27;)                                |   2 |\n",
       "| (&#x27;Streets, Utilities, and Transportation&#x27;, &#x27;Sidewalk/Street Maintenance&#x27;)          |   2 |\n",
       "| (&#x27;Graffiti and Vandalism&#x27;, &#x27;Graffiti&#x27;)                                             |   1 |\n",
       "| (&#x27;Facilities, Electrical &amp; Property Management&#x27;, &#x27;Parks/Marina Building Services&#x27;) |   1 |\n",
       "| (&#x27;Streets, Utilities, and Transportation&#x27;, &#x27;Traffic Maintenance&#x27;)                  |   2 |\n",
       "| (&#x27;Streets, Utilities, and Transportation&#x27;, &#x27;Clean City Program&#x27;)                   |   1 |\n",
       "| (&#x27;Refuse and Recycling&#x27;, &#x27;Commercial&#x27;)                                             |  22 |\n",
       "| (&#x27;Refuse and Recycling&#x27;, &#x27;Residential&#x27;)                                            |  29 |\n",
       "| (&#x27;Parks, Trees and Vegetation&#x27;, &#x27;Landscape Maintenance&#x27;)                           |   1 |\n",
       "| (&#x27;Traffic and Transportation&#x27;, &#x27;Signage&#x27;)                                          |   1 |\n",
       "| (&#x27;General Questions/information&#x27;, &#x27;Miscellaneous&#x27;)                                 |   5 |</div></div></div></details></div>"
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                "# Getting the tickets that have been open the longest\r\nopen_tickets[\"date_opened\"] = pd.to_datetime(open_tickets[\"date_opened\"])\r\nopen_tickets[\"days_open\"] = (pd.to_datetime(\"today\") - open_tickets[\"date_opened\"]).dt.days\r\nlongest_open_tickets = open_tickets.sort_values(\"days_open\", ascending=False)\r\nlongest_open_tickets"
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                "STDERR:\n/var/folders/r4/lz3zpzb528n55t008k22p4dh0000gn/T/ipykernel_16850/4080719602.py:2: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  open_tickets[\"date_opened\"] = pd.to_datetime(open_tickets[\"date_opened\"])\n/var/folders/r4/lz3zpzb528n55t008k22p4dh0000gn/T/ipykernel_16850/4080719602.py:3: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  open_tickets[\"days_open\"] = (pd.to_datetime(\"today\") - open_tickets[\"date_opened\"]).dt.days\n\n\nOUTPUT:\n## Dataframe Summary\n\nNumber of Rows: 67\n\nNumber of Columns: 24\n\n### Column Information\n\n|    | Column Name                 | Data Type      |   Missing Values |   % Missing |\n|----|-----------------------------|----------------|------------------|-------------|\n|  0 | case_id                     | int64          |                0 |      0      |\n|  1 | date_opened                 | datetime64[ns] |                0 |      0      |\n|  2 | case_status                 | object         |                0 |      0      |\n|  3 | date_closed                 | object         |               67 |    100      |\n|  4 | request_category            | object         |                0 |      0      |\n|  5 | request_subcategory         | object         |                0 |      0      |\n|  6 | request_detail              | object         |                0 |      0      |\n|  7 | object_type                 | object         |                0 |      0      |\n|  8 | street_address              | object         |                7 |     10.4478 |\n|  9 | city                        | object         |                0 |      0      |\n| 10 | state                       | object         |                0 |      0      |\n| 11 | neighborhood                | object         |                0 |      0      |\n| 12 | apn                         | object         |               14 |     20.8955 |\n| 13 | latitude                    | float64        |               16 |     23.8806 |\n| 14 | longitude                   | float64        |               16 |     23.8806 |\n| 15 | location                    | object         |               16 |     23.8806 |\n| 16 | :@computed_region_b3wi_w8ix | float64        |               16 |     23.8806 |\n| 17 | :@computed_region_fhmw_rucx | float64        |               16 |     23.8806 |\n| 18 | :@computed_region_u3y2_d2ws | float64        |               16 |     23.8806 |\n| 19 | :@computed_region_5s6d_2f32 | float64        |               16 |     23.8806 |\n| 20 | :@computed_region_3ini_iehf | float64        |               16 |     23.8806 |\n| 21 | :@computed_region_5bih_7r3y | float64        |               16 |     23.8806 |\n| 22 | :@computed_region_x3q3_gi3e | float64        |               16 |     23.8806 |\n| 23 | days_open                   | int64          |                0 |      0      |\n\n### Categorical Summary\n\n|    | Column Name   |   count | mean                          | min                 | 25%                 | 50%                 | 75%                        | max                 |\n|----|---------------|---------|-------------------------------|---------------------|---------------------|---------------------|----------------------------|---------------------|\n|  0 | date_opened   |      67 | 2020-01-23 02:05:05.880596736 | 2017-10-23 10:31:19 | 2019-10-06 12:42:30 | 2019-12-11 08:28:00 | 2020-02-21 12:03:21.500000 | 2022-04-27 08:52:50 |\n\n### Sample Data (5x17)\n\n|     |   days_open | request_subcategory   | date_opened         |   date_closed | city     |   longitude | request_detail            | street_address   | apn           | object_type   | location                                                                                                                          | state   |   latitude | request_category                       | neighborhood   |      case_id | case_status   |\n|-----|-------------|-----------------------|---------------------|---------------|----------|-------------|---------------------------|------------------|---------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------|---------|------------|----------------------------------------|----------------|--------------|---------------|\n| 233 |        1256 | Traffic Maintenance   | 2020-02-19 10:53:00 |           nan | Berkeley |    -122.298 | Curb Repainting           | 2424 FOURTH ST   | 056 194700101 | Property      | {'latitude': '37.86025999', 'longitude': '-122.2980739', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'}  | CA      |    37.8603 | Streets, Utilities, and Transportation | Berkeley       | 121000751883 | Open          |\n| 380 |        1391 | Commercial            | 2019-10-07 13:39:05 |           nan | Berkeley |    -122.297 | Commercial Special Pickup | 1360 TENTH ST    | 060 235200201 | Property      | {'latitude': '37.87889918', 'longitude': '-122.29710072', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | CA      |    37.8789 | Refuse and Recycling                   | Berkeley       | 121000721398 | Open          |\n| 836 |        1391 | Residential           | 2019-10-07 12:13:54 |           nan | Berkeley |    -122.296 | Residential Reminder      | 1810 EIGHTH ST   | 057 209400800 | Property      | {'latitude': '37.87036901', 'longitude': '-122.29648711', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | CA      |    37.8704 | Refuse and Recycling                   | Berkeley       | 121000721342 | Open          |\n| 967 |        1265 | Residential           | 2020-02-10 10:42:00 |           nan | Berkeley |    -122.282 | Residential Bulky Pickup  | 1319 HASKELL ST  | 053 162501400 | Property      | {'latitude': '37.85153604', 'longitude': '-122.2824519', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'}  | CA      |    37.8515 | Refuse and Recycling                   | Berkeley       | 121000749863 | Open          |\n| 232 |        1326 | Commercial            | 2019-12-11 16:07:16 |           nan | Berkeley |    -122.295 | Commercial Special Pickup | 729 HEINZ AVE 7  | 053 165500800 | Property      | {'latitude': '37.85358725', 'longitude': '-122.29492015', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | CA      |    37.8536 | Refuse and Recycling                   | Berkeley       | 121000737059 | Open          |"
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       "<div><style>.chatlab-chat-details summary &gt; *  { display: inline; color: #27374D; }</style><details style=\"background: #DDE6ED; border-radius: 5px; padding: .5rem 1rem\" className=\"chatlab-chat-details\"><summary style=\"color: #27374D; cursor: pointer\"><span style=\"color: #9DB2BF; padding-left: 5px; padding-right: 5px\">𝑓</span><span style=\"color: #27374D; padding-left: 5px; padding-right: 5px\">Ran</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\">python</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\"></span></summary><div style=\"margin-left: 10px; margin-top: 10px\"><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Input:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\"># Getting the tickets that have been open the longest\r\n",
       "open_tickets[&quot;date_opened&quot;] = pd.to_datetime(open_tickets[&quot;date_opened&quot;])\r\n",
       "open_tickets[&quot;days_open&quot;] = (pd.to_datetime(&quot;today&quot;) - open_tickets[&quot;date_opened&quot;]).dt.days\r\n",
       "longest_open_tickets = open_tickets.sort_values(&quot;days_open&quot;, ascending=False)\r\n",
       "longest_open_tickets</div></div><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Output:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\">STDERR:\n",
       "/var/folders/r4/lz3zpzb528n55t008k22p4dh0000gn/T/ipykernel_16850/4080719602.py:2: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  open_tickets[&quot;date_opened&quot;] = pd.to_datetime(open_tickets[&quot;date_opened&quot;])\n",
       "/var/folders/r4/lz3zpzb528n55t008k22p4dh0000gn/T/ipykernel_16850/4080719602.py:3: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  open_tickets[&quot;days_open&quot;] = (pd.to_datetime(&quot;today&quot;) - open_tickets[&quot;date_opened&quot;]).dt.days\n",
       "\n",
       "\n",
       "OUTPUT:\n",
       "## Dataframe Summary\n",
       "\n",
       "Number of Rows: 67\n",
       "\n",
       "Number of Columns: 24\n",
       "\n",
       "### Column Information\n",
       "\n",
       "|    | Column Name                 | Data Type      |   Missing Values |   % Missing |\n",
       "|----|-----------------------------|----------------|------------------|-------------|\n",
       "|  0 | case_id                     | int64          |                0 |      0      |\n",
       "|  1 | date_opened                 | datetime64[ns] |                0 |      0      |\n",
       "|  2 | case_status                 | object         |                0 |      0      |\n",
       "|  3 | date_closed                 | object         |               67 |    100      |\n",
       "|  4 | request_category            | object         |                0 |      0      |\n",
       "|  5 | request_subcategory         | object         |                0 |      0      |\n",
       "|  6 | request_detail              | object         |                0 |      0      |\n",
       "|  7 | object_type                 | object         |                0 |      0      |\n",
       "|  8 | street_address              | object         |                7 |     10.4478 |\n",
       "|  9 | city                        | object         |                0 |      0      |\n",
       "| 10 | state                       | object         |                0 |      0      |\n",
       "| 11 | neighborhood                | object         |                0 |      0      |\n",
       "| 12 | apn                         | object         |               14 |     20.8955 |\n",
       "| 13 | latitude                    | float64        |               16 |     23.8806 |\n",
       "| 14 | longitude                   | float64        |               16 |     23.8806 |\n",
       "| 15 | location                    | object         |               16 |     23.8806 |\n",
       "| 16 | :@computed_region_b3wi_w8ix | float64        |               16 |     23.8806 |\n",
       "| 17 | :@computed_region_fhmw_rucx | float64        |               16 |     23.8806 |\n",
       "| 18 | :@computed_region_u3y2_d2ws | float64        |               16 |     23.8806 |\n",
       "| 19 | :@computed_region_5s6d_2f32 | float64        |               16 |     23.8806 |\n",
       "| 20 | :@computed_region_3ini_iehf | float64        |               16 |     23.8806 |\n",
       "| 21 | :@computed_region_5bih_7r3y | float64        |               16 |     23.8806 |\n",
       "| 22 | :@computed_region_x3q3_gi3e | float64        |               16 |     23.8806 |\n",
       "| 23 | days_open                   | int64          |                0 |      0      |\n",
       "\n",
       "### Categorical Summary\n",
       "\n",
       "|    | Column Name   |   count | mean                          | min                 | 25%                 | 50%                 | 75%                        | max                 |\n",
       "|----|---------------|---------|-------------------------------|---------------------|---------------------|---------------------|----------------------------|---------------------|\n",
       "|  0 | date_opened   |      67 | 2020-01-23 02:05:05.880596736 | 2017-10-23 10:31:19 | 2019-10-06 12:42:30 | 2019-12-11 08:28:00 | 2020-02-21 12:03:21.500000 | 2022-04-27 08:52:50 |\n",
       "\n",
       "### Sample Data (5x17)\n",
       "\n",
       "|     |   days_open | request_subcategory   | date_opened         |   date_closed | city     |   longitude | request_detail            | street_address   | apn           | object_type   | location                                                                                                                          | state   |   latitude | request_category                       | neighborhood   |      case_id | case_status   |\n",
       "|-----|-------------|-----------------------|---------------------|---------------|----------|-------------|---------------------------|------------------|---------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------|---------|------------|----------------------------------------|----------------|--------------|---------------|\n",
       "| 233 |        1256 | Traffic Maintenance   | 2020-02-19 10:53:00 |           nan | Berkeley |    -122.298 | Curb Repainting           | 2424 FOURTH ST   | 056 194700101 | Property      | {&#x27;latitude&#x27;: &#x27;37.86025999&#x27;, &#x27;longitude&#x27;: &#x27;-122.2980739&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;}  | CA      |    37.8603 | Streets, Utilities, and Transportation | Berkeley       | 121000751883 | Open          |\n",
       "| 380 |        1391 | Commercial            | 2019-10-07 13:39:05 |           nan | Berkeley |    -122.297 | Commercial Special Pickup | 1360 TENTH ST    | 060 235200201 | Property      | {&#x27;latitude&#x27;: &#x27;37.87889918&#x27;, &#x27;longitude&#x27;: &#x27;-122.29710072&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;} | CA      |    37.8789 | Refuse and Recycling                   | Berkeley       | 121000721398 | Open          |\n",
       "| 836 |        1391 | Residential           | 2019-10-07 12:13:54 |           nan | Berkeley |    -122.296 | Residential Reminder      | 1810 EIGHTH ST   | 057 209400800 | Property      | {&#x27;latitude&#x27;: &#x27;37.87036901&#x27;, &#x27;longitude&#x27;: &#x27;-122.29648711&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;} | CA      |    37.8704 | Refuse and Recycling                   | Berkeley       | 121000721342 | Open          |\n",
       "| 967 |        1265 | Residential           | 2020-02-10 10:42:00 |           nan | Berkeley |    -122.282 | Residential Bulky Pickup  | 1319 HASKELL ST  | 053 162501400 | Property      | {&#x27;latitude&#x27;: &#x27;37.85153604&#x27;, &#x27;longitude&#x27;: &#x27;-122.2824519&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;}  | CA      |    37.8515 | Refuse and Recycling                   | Berkeley       | 121000749863 | Open          |\n",
       "| 232 |        1326 | Commercial            | 2019-12-11 16:07:16 |           nan | Berkeley |    -122.295 | Commercial Special Pickup | 729 HEINZ AVE 7  | 053 165500800 | Property      | {&#x27;latitude&#x27;: &#x27;37.85358725&#x27;, &#x27;longitude&#x27;: &#x27;-122.29492015&#x27;, &#x27;human_address&#x27;: &#x27;{&quot;address&quot;: &quot;&quot;, &quot;city&quot;: &quot;&quot;, &quot;state&quot;: &quot;&quot;, &quot;zip&quot;: &quot;&quot;}&#x27;} | CA      |    37.8536 | Refuse and Recycling                   | Berkeley       | 121000737059 | Open          |</div></div></div></details></div>"
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       "      <th></th>\n",
       "      <th>case_id</th>\n",
       "      <th>date_opened</th>\n",
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       "      <th>location</th>\n",
       "      <th>:@computed_region_b3wi_w8ix</th>\n",
       "      <th>:@computed_region_fhmw_rucx</th>\n",
       "      <th>:@computed_region_u3y2_d2ws</th>\n",
       "      <th>:@computed_region_5s6d_2f32</th>\n",
       "      <th>:@computed_region_3ini_iehf</th>\n",
       "      <th>:@computed_region_5bih_7r3y</th>\n",
       "      <th>:@computed_region_x3q3_gi3e</th>\n",
       "      <th>days_open</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>121000370701</td>\n",
       "      <td>2017-10-23 10:31:19</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Residential Bulky Pickup</td>\n",
       "      <td>Property</td>\n",
       "      <td>2508 WOOLSEY ST</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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>2105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>121000416285</td>\n",
       "      <td>2018-08-13 12:29:37</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Residential Bulky Pickup</td>\n",
       "      <td>Property</td>\n",
       "      <td>2218 WOOLSEY ST</td>\n",
       "      <td>Berkeley</td>\n",
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       "      <td>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>1811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776</th>\n",
       "      <td>121000656133</td>\n",
       "      <td>2019-01-17 15:46:45</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Commercial Reminder</td>\n",
       "      <td>Individual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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>1654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>736</th>\n",
       "      <td>121000703570</td>\n",
       "      <td>2019-07-30 13:00:26</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Residential Bulky Pickup</td>\n",
       "      <td>Property</td>\n",
       "      <td>2322 EIGHTH ST</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>-122.294125</td>\n",
       "      <td>{'latitude': '37.86301956', 'longitude': '-122...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>464.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1502.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>121000703638</td>\n",
       "      <td>2019-07-30 14:38:00</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Commercial</td>\n",
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       "      <td>2500 M L KING JR WAY</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>-122.272366</td>\n",
       "      <td>{'latitude': '37.86308418', 'longitude': '-122...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>346.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1495.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <th>1</th>\n",
       "      <td>121000876647</td>\n",
       "      <td>2021-09-13 10:50:00</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Residential Bulky Pickup</td>\n",
       "      <td>Property</td>\n",
       "      <td>1722 DWIGHT WAY</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>-122.275461</td>\n",
       "      <td>{'latitude': '37.86265624', 'longitude': '-122...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>610.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1495.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>121000886045</td>\n",
       "      <td>2021-10-24 18:27:00</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Streets, Utilities, and Transportation</td>\n",
       "      <td>Storm</td>\n",
       "      <td>Storm Problem</td>\n",
       "      <td>Property</td>\n",
       "      <td>Intersection of Dana and Woolsey, BERKELEY, CA</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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>642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>121000900289</td>\n",
       "      <td>2021-12-30 14:41:00</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Graffiti and Vandalism</td>\n",
       "      <td>Graffiti</td>\n",
       "      <td>Graffiti Abatement - Streets and Utilities</td>\n",
       "      <td>Property</td>\n",
       "      <td>Intersection of Sacramento and Cedar, BERKELEY...</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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>576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>121000900370</td>\n",
       "      <td>2021-12-31 12:59:00</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>General Questions/information</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>Miscellaneous Internet Request</td>\n",
       "      <td>Individual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>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>575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>121000923837</td>\n",
       "      <td>2022-04-27 08:52:50</td>\n",
       "      <td>Open</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Refuse and Recycling</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Residential Bulky Pickup</td>\n",
       "      <td>Property</td>\n",
       "      <td>2639 GRANT ST</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>...</td>\n",
       "      <td>-122.273319</td>\n",
       "      <td>{'latitude': '37.85985408', 'longitude': '-122...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>627.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1495.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>458</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>67 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/llm+plain": [
       "## Dataframe Summary\n",
       "\n",
       "Number of Rows: 67\n",
       "\n",
       "Number of Columns: 24\n",
       "\n",
       "### Column Information\n",
       "\n",
       "|    | Column Name                 | Data Type      |   Missing Values |   % Missing |\n",
       "|----|-----------------------------|----------------|------------------|-------------|\n",
       "|  0 | case_id                     | int64          |                0 |      0      |\n",
       "|  1 | date_opened                 | datetime64[ns] |                0 |      0      |\n",
       "|  2 | case_status                 | object         |                0 |      0      |\n",
       "|  3 | date_closed                 | object         |               67 |    100      |\n",
       "|  4 | request_category            | object         |                0 |      0      |\n",
       "|  5 | request_subcategory         | object         |                0 |      0      |\n",
       "|  6 | request_detail              | object         |                0 |      0      |\n",
       "|  7 | object_type                 | object         |                0 |      0      |\n",
       "|  8 | street_address              | object         |                7 |     10.4478 |\n",
       "|  9 | city                        | object         |                0 |      0      |\n",
       "| 10 | state                       | object         |                0 |      0      |\n",
       "| 11 | neighborhood                | object         |                0 |      0      |\n",
       "| 12 | apn                         | object         |               14 |     20.8955 |\n",
       "| 13 | latitude                    | float64        |               16 |     23.8806 |\n",
       "| 14 | longitude                   | float64        |               16 |     23.8806 |\n",
       "| 15 | location                    | object         |               16 |     23.8806 |\n",
       "| 16 | :@computed_region_b3wi_w8ix | float64        |               16 |     23.8806 |\n",
       "| 17 | :@computed_region_fhmw_rucx | float64        |               16 |     23.8806 |\n",
       "| 18 | :@computed_region_u3y2_d2ws | float64        |               16 |     23.8806 |\n",
       "| 19 | :@computed_region_5s6d_2f32 | float64        |               16 |     23.8806 |\n",
       "| 20 | :@computed_region_3ini_iehf | float64        |               16 |     23.8806 |\n",
       "| 21 | :@computed_region_5bih_7r3y | float64        |               16 |     23.8806 |\n",
       "| 22 | :@computed_region_x3q3_gi3e | float64        |               16 |     23.8806 |\n",
       "| 23 | days_open                   | int64          |                0 |      0      |\n",
       "\n",
       "### Categorical Summary\n",
       "\n",
       "|    | Column Name   |   count | mean                          | min                 | 25%                 | 50%                 | 75%                        | max                 |\n",
       "|----|---------------|---------|-------------------------------|---------------------|---------------------|---------------------|----------------------------|---------------------|\n",
       "|  0 | date_opened   |      67 | 2020-01-23 02:05:05.880596736 | 2017-10-23 10:31:19 | 2019-10-06 12:42:30 | 2019-12-11 08:28:00 | 2020-02-21 12:03:21.500000 | 2022-04-27 08:52:50 |\n",
       "\n",
       "### Sample Data (5x17)\n",
       "\n",
       "|     |   days_open | request_subcategory   | date_opened         |   date_closed | city     |   longitude | request_detail            | street_address   | apn           | object_type   | location                                                                                                                          | state   |   latitude | request_category                       | neighborhood   |      case_id | case_status   |\n",
       "|-----|-------------|-----------------------|---------------------|---------------|----------|-------------|---------------------------|------------------|---------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------|---------|------------|----------------------------------------|----------------|--------------|---------------|\n",
       "| 233 |        1256 | Traffic Maintenance   | 2020-02-19 10:53:00 |           nan | Berkeley |    -122.298 | Curb Repainting           | 2424 FOURTH ST   | 056 194700101 | Property      | {'latitude': '37.86025999', 'longitude': '-122.2980739', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'}  | CA      |    37.8603 | Streets, Utilities, and Transportation | Berkeley       | 121000751883 | Open          |\n",
       "| 380 |        1391 | Commercial            | 2019-10-07 13:39:05 |           nan | Berkeley |    -122.297 | Commercial Special Pickup | 1360 TENTH ST    | 060 235200201 | Property      | {'latitude': '37.87889918', 'longitude': '-122.29710072', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | CA      |    37.8789 | Refuse and Recycling                   | Berkeley       | 121000721398 | Open          |\n",
       "| 836 |        1391 | Residential           | 2019-10-07 12:13:54 |           nan | Berkeley |    -122.296 | Residential Reminder      | 1810 EIGHTH ST   | 057 209400800 | Property      | {'latitude': '37.87036901', 'longitude': '-122.29648711', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | CA      |    37.8704 | Refuse and Recycling                   | Berkeley       | 121000721342 | Open          |\n",
       "| 967 |        1265 | Residential           | 2020-02-10 10:42:00 |           nan | Berkeley |    -122.282 | Residential Bulky Pickup  | 1319 HASKELL ST  | 053 162501400 | Property      | {'latitude': '37.85153604', 'longitude': '-122.2824519', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'}  | CA      |    37.8515 | Refuse and Recycling                   | Berkeley       | 121000749863 | Open          |\n",
       "| 232 |        1326 | Commercial            | 2019-12-11 16:07:16 |           nan | Berkeley |    -122.295 | Commercial Special Pickup | 729 HEINZ AVE 7  | 053 165500800 | Property      | {'latitude': '37.85358725', 'longitude': '-122.29492015', 'human_address': '{\"address\": \"\", \"city\": \"\", \"state\": \"\", \"zip\": \"\"}'} | CA      |    37.8536 | Refuse and Recycling                   | Berkeley       | 121000737059 | Open          |"
      ],
      "text/plain": [
       "          case_id         date_opened case_status date_closed  \\\n",
       "97   121000370701 2017-10-23 10:31:19        Open         NaN   \n",
       "279  121000416285 2018-08-13 12:29:37        Open         NaN   \n",
       "776  121000656133 2019-01-17 15:46:45        Open         NaN   \n",
       "736  121000703570 2019-07-30 13:00:26        Open         NaN   \n",
       "733  121000703638 2019-07-30 14:38:00        Open         NaN   \n",
       "..            ...                 ...         ...         ...   \n",
       "1    121000876647 2021-09-13 10:50:00        Open         NaN   \n",
       "743  121000886045 2021-10-24 18:27:00        Open         NaN   \n",
       "356  121000900289 2021-12-30 14:41:00        Open         NaN   \n",
       "252  121000900370 2021-12-31 12:59:00        Open         NaN   \n",
       "26   121000923837 2022-04-27 08:52:50        Open         NaN   \n",
       "\n",
       "                           request_category request_subcategory  \\\n",
       "97                     Refuse and Recycling         Residential   \n",
       "279                    Refuse and Recycling         Residential   \n",
       "776                    Refuse and Recycling          Commercial   \n",
       "736                    Refuse and Recycling         Residential   \n",
       "733                    Refuse and Recycling          Commercial   \n",
       "..                                      ...                 ...   \n",
       "1                      Refuse and Recycling         Residential   \n",
       "743  Streets, Utilities, and Transportation               Storm   \n",
       "356                  Graffiti and Vandalism            Graffiti   \n",
       "252           General Questions/information       Miscellaneous   \n",
       "26                     Refuse and Recycling         Residential   \n",
       "\n",
       "                                 request_detail object_type  \\\n",
       "97                     Residential Bulky Pickup    Property   \n",
       "279                    Residential Bulky Pickup    Property   \n",
       "776                         Commercial Reminder  Individual   \n",
       "736                    Residential Bulky Pickup    Property   \n",
       "733                   Commercial Special Pickup    Property   \n",
       "..                                          ...         ...   \n",
       "1                      Residential Bulky Pickup    Property   \n",
       "743                               Storm Problem    Property   \n",
       "356  Graffiti Abatement - Streets and Utilities    Property   \n",
       "252              Miscellaneous Internet Request  Individual   \n",
       "26                     Residential Bulky Pickup    Property   \n",
       "\n",
       "                                        street_address      city  ...  \\\n",
       "97                                     2508 WOOLSEY ST  Berkeley  ...   \n",
       "279                                    2218 WOOLSEY ST  Berkeley  ...   \n",
       "776                                                NaN  Berkeley  ...   \n",
       "736                                     2322 EIGHTH ST  Berkeley  ...   \n",
       "733                               2500 M L KING JR WAY  Berkeley  ...   \n",
       "..                                                 ...       ...  ...   \n",
       "1                                      1722 DWIGHT WAY  Berkeley  ...   \n",
       "743     Intersection of Dana and Woolsey, BERKELEY, CA  Berkeley  ...   \n",
       "356  Intersection of Sacramento and Cedar, BERKELEY...  Berkeley  ...   \n",
       "252                                                NaN  Berkeley  ...   \n",
       "26                                       2639 GRANT ST  Berkeley  ...   \n",
       "\n",
       "      longitude                                           location  \\\n",
       "97          NaN                                                NaN   \n",
       "279         NaN                                                NaN   \n",
       "776         NaN                                                NaN   \n",
       "736 -122.294125  {'latitude': '37.86301956', 'longitude': '-122...   \n",
       "733 -122.272366  {'latitude': '37.86308418', 'longitude': '-122...   \n",
       "..          ...                                                ...   \n",
       "1   -122.275461  {'latitude': '37.86265624', 'longitude': '-122...   \n",
       "743         NaN                                                NaN   \n",
       "356         NaN                                                NaN   \n",
       "252         NaN                                                NaN   \n",
       "26  -122.273319  {'latitude': '37.85985408', 'longitude': '-122...   \n",
       "\n",
       "    :@computed_region_b3wi_w8ix  :@computed_region_fhmw_rucx  \\\n",
       "97                          NaN                          NaN   \n",
       "279                         NaN                          NaN   \n",
       "776                         NaN                          NaN   \n",
       "736                         8.0                        464.0   \n",
       "733                         2.0                        346.0   \n",
       "..                          ...                          ...   \n",
       "1                           2.0                        610.0   \n",
       "743                         NaN                          NaN   \n",
       "356                         NaN                          NaN   \n",
       "252                         NaN                          NaN   \n",
       "26                          2.0                        627.0   \n",
       "\n",
       "     :@computed_region_u3y2_d2ws :@computed_region_5s6d_2f32  \\\n",
       "97                           NaN                         NaN   \n",
       "279                          NaN                         NaN   \n",
       "776                          NaN                         NaN   \n",
       "736                          8.0                      1502.0   \n",
       "733                          2.0                      1495.0   \n",
       "..                           ...                         ...   \n",
       "1                            2.0                      1495.0   \n",
       "743                          NaN                         NaN   \n",
       "356                          NaN                         NaN   \n",
       "252                          NaN                         NaN   \n",
       "26                           2.0                      1495.0   \n",
       "\n",
       "     :@computed_region_3ini_iehf  :@computed_region_5bih_7r3y  \\\n",
       "97                           NaN                          NaN   \n",
       "279                          NaN                          NaN   \n",
       "776                          NaN                          NaN   \n",
       "736                          5.0                         22.0   \n",
       "733                         10.0                         33.0   \n",
       "..                           ...                          ...   \n",
       "1                           10.0                         33.0   \n",
       "743                          NaN                          NaN   \n",
       "356                          NaN                          NaN   \n",
       "252                          NaN                          NaN   \n",
       "26                           4.0                         33.0   \n",
       "\n",
       "     :@computed_region_x3q3_gi3e  days_open  \n",
       "97                           NaN       2105  \n",
       "279                          NaN       1811  \n",
       "776                          NaN       1654  \n",
       "736                          8.0       1460  \n",
       "733                          7.0       1460  \n",
       "..                           ...        ...  \n",
       "1                            7.0        684  \n",
       "743                          NaN        642  \n",
       "356                          NaN        576  \n",
       "252                          NaN        575  \n",
       "26                           7.0        458  \n",
       "\n",
       "[67 rows x 24 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Based on the data loaded, here are the answers to your questions:\n",
       "\n",
       "1. How many tickets are still open per category and subcategory?\n",
       "\n",
       "The number of open tickets per category and subcategory is as follows:\n",
       "\n",
       "| Category                                | Subcategory                      | Number of Open Tickets |\n",
       "|-----------------------------------------|---------------------------------|------------------------|\n",
       "| Streets, Utilities, and Transportation | Storm                           | 2                      |\n",
       "| Streets, Utilities, and Transportation | Sidewalk/Street Maintenance     | 2                      |\n",
       "| Graffiti and Vandalism                  | Graffiti                        | 1                      |\n",
       "| Facilities, Electrical & Property Management    | Parks/Marina Building Services | 1                      |\n",
       "| Streets, Utilities, and Transportation | Traffic Maintenance             | 2                      |\n",
       "| Streets, Utilities, and Transportation | Clean City Program              | 1                      |\n",
       "| Refuse and Recycling                    | Commercial                      | 22                     |\n",
       "| Refuse and Recycling                    | Residential                     | 29                     |\n",
       "| Parks, Trees and Vegetation             | Landscape Maintenance           | 1                      |\n",
       "| Traffic and Transportation             | Signage                         | 1                      |\n",
       "| General Questions/information           | Miscellaneous                   | 5                      |\n",
       "\n",
       "2. Which tickets have been open the longest?\n",
       "\n",
       "Here are a few of the tickets that have been open the longest:\n",
       "\n",
       "| Case ID     | Request Subcategory | Date Opened          | Days Open |\n",
       "|-------------|---------------------|----------------------|-----------|\n",
       "| 121000751883 | Traffic Maintenance | 2020-02-19 10:53:00 | 1256      |\n",
       "| 121000721398 | Commercial          | 2019-10-07 13:39:05 | 1391      |\n",
       "| 121000721342 | Residential         | 2019-10-07 12:13:54 | 1391      |\n",
       "| 121000749863 | Residential         | 2020-02-10 10:42:00 | 1265      |\n",
       "| 121000737059 | Commercial          | 2019-12-11 16:07:16 | 1326      |\n",
       "\n",
       "Please note that these are just a few examples, and there are more tickets that have been open for a long time."
      ],
      "text/plain": [
       "Based on the data loaded, here are the answers to your questions:\n",
       "\n",
       "1. How many tickets are still open per category and subcategory?\n",
       "\n",
       "The number of open tickets per category and subcategory is as follows:\n",
       "\n",
       "| Category                                | Subcategory                      | Number of Open Tickets |\n",
       "|-----------------------------------------|---------------------------------|------------------------|\n",
       "| Streets, Utilities, and Transportation | Storm                           | 2                      |\n",
       "| Streets, Utilities, and Transportation | Sidewalk/Street Maintenance     | 2                      |\n",
       "| Graffiti and Vandalism                  | Graffiti                        | 1                      |\n",
       "| Facilities, Electrical & Property Management    | Parks/Marina Building Services | 1                      |\n",
       "| Streets, Utilities, and Transportation | Traffic Maintenance             | 2                      |\n",
       "| Streets, Utilities, and Transportation | Clean City Program              | 1                      |\n",
       "| Refuse and Recycling                    | Commercial                      | 22                     |\n",
       "| Refuse and Recycling                    | Residential                     | 29                     |\n",
       "| Parks, Trees and Vegetation             | Landscape Maintenance           | 1                      |\n",
       "| Traffic and Transportation             | Signage                         | 1                      |\n",
       "| General Questions/information           | Miscellaneous                   | 5                      |\n",
       "\n",
       "2. Which tickets have been open the longest?\n",
       "\n",
       "Here are a few of the tickets that have been open the longest:\n",
       "\n",
       "| Case ID     | Request Subcategory | Date Opened          | Days Open |\n",
       "|-------------|---------------------|----------------------|-----------|\n",
       "| 121000751883 | Traffic Maintenance | 2020-02-19 10:53:00 | 1256      |\n",
       "| 121000721398 | Commercial          | 2019-10-07 13:39:05 | 1391      |\n",
       "| 121000721342 | Residential         | 2019-10-07 12:13:54 | 1391      |\n",
       "| 121000749863 | Residential         | 2020-02-10 10:42:00 | 1265      |\n",
       "| 121000737059 | Commercial          | 2019-12-11 16:07:16 | 1326      |\n",
       "\n",
       "Please note that these are just a few examples, and there are more tickets that have been open for a long time."
      ]
     },
     "metadata": {
      "text/markdown": {
       "chatlab": {
        "default": true
       }
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from chatlab import Chat, system\n",
    "from chatlab.builtins import run_cell\n",
    "from chatlab.models import GPT_4_0613, GPT_3_5_TURBO_0613, GPT_3_5_TURBO_16K_0613\n",
    "\n",
    "NOTEBOOK_ASSISTANCE_PROMPT = \"\"\"\n",
    "As a coding assistant, your task is to help users write code in Python within Jupyter Notebooks. The environment you are running in has the full PyData/NumFOCUS suite.\n",
    "\n",
    "The user is able to interact with the same variables as you. It's ok to use `display` on objects like `DataFrame`s.\n",
    "\n",
    "Do not \"type out\" tables or column information directly back to the user. They can `display` it themselves.\n",
    "\"\"\".strip()\n",
    "\n",
    "chat = Chat(\n",
    "    system(NOTEBOOK_ASSISTANCE_PROMPT),\n",
    "    allow_hallucinated_python=True,\n",
    "    model=GPT_3_5_TURBO_16K_0613\n",
    ")\n",
    "chat.register(run_cell)\n",
    "\n",
    "await chat(f\"\"\"\n",
    "Load this data:\n",
    "\n",
    "https://data.cityofberkeley.info/resource/bscu-qpbu.json\n",
    "\n",
    "After you familiarize yourself with it, I want to answer the following questions:\n",
    "\n",
    "* How many tickets are still open per category and subcategory?\n",
    "* Which tickets have been open the longest?\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8f3b030d-8981-4ff8-a2ca-72469d150b34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vdom.v1+json": {
       "attributes": {},
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        {
         "attributes": {},
         "children": [
          ".chatlab-chat-details summary > *  { display: inline; color: #27374D; }"
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         "attributes": {
          "className": "chatlab-chat-details",
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           "background": "#DDE6ED",
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           "padding": ".5rem 1rem"
          }
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         "children": [
          {
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             "cursor": "pointer"
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              "style": {
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              "𝑓"
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              ""
             ],
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           ],
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                "Input:"
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                 "unicodeBidi": "embed",
                 "whiteSpace": "pre"
                }
               },
               "children": [
                "import matplotlib.pyplot as plt\n\n# Plotting the number of open tickets per category and subcategory\nplt.figure(figsize=(12, 6))\nopen_tickets_per_category_subcategory.plot(kind='bar')\nplt.title('Number of Open Tickets per Category and Subcategory')\nplt.xlabel('Category, Subcategory')\nplt.ylabel('Number of Tickets')\nplt.xticks(rotation=90)\nplt.show()"
               ],
               "tagName": "div"
              }
             ],
             "tagName": "div"
            },
            {
             "attributes": {},
             "children": [
              {
               "attributes": {
                "style": {
                 "color": "#27374D",
                 "fontWeight": "500",
                 "marginBottom": "5px"
                }
               },
               "children": [
                "Output:"
               ],
               "tagName": "div"
              },
              {
               "attributes": {
                "style": {
                 "background": "#F7F9FA",
                 "color": "#27374D",
                 "fontFamily": "monospace",
                 "marginBottom": "10px",
                 "overflowX": "auto",
                 "padding": "10px",
                 "unicodeBidi": "embed",
                 "whiteSpace": "pre"
                }
               },
               "children": [
                "OUTPUT:\n<Figure size 1200x600 with 1 Axes>"
               ],
               "tagName": "div"
              }
             ],
             "tagName": "div"
            }
           ],
           "tagName": "div"
          }
         ],
         "tagName": "details"
        }
       ],
       "tagName": "div"
      },
      "text/html": [
       "<div><style>.chatlab-chat-details summary &gt; *  { display: inline; color: #27374D; }</style><details style=\"background: #DDE6ED; border-radius: 5px; padding: .5rem 1rem\" className=\"chatlab-chat-details\"><summary style=\"color: #27374D; cursor: pointer\"><span style=\"color: #9DB2BF; padding-left: 5px; padding-right: 5px\">𝑓</span><span style=\"color: #27374D; padding-left: 5px; padding-right: 5px\">Ran</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\">python</span><span style=\"font-family: monospace; unicode-bidi: embed; white-space: pre\"></span></summary><div style=\"margin-left: 10px; margin-top: 10px\"><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Input:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\">import matplotlib.pyplot as plt\n",
       "\n",
       "# Plotting the number of open tickets per category and subcategory\n",
       "plt.figure(figsize=(12, 6))\n",
       "open_tickets_per_category_subcategory.plot(kind=&#x27;bar&#x27;)\n",
       "plt.title(&#x27;Number of Open Tickets per Category and Subcategory&#x27;)\n",
       "plt.xlabel(&#x27;Category, Subcategory&#x27;)\n",
       "plt.ylabel(&#x27;Number of Tickets&#x27;)\n",
       "plt.xticks(rotation=90)\n",
       "plt.show()</div></div><div><div style=\"color: #27374D; font-weight: 500; margin-bottom: 5px\">Output:</div><div style=\"background: #F7F9FA; color: #27374D; font-family: monospace; margin-bottom: 10px; overflow-x: auto; padding: 10px; unicode-bidi: embed; white-space: pre\">OUTPUT:\n",
       "&lt;Figure size 1200x600 with 1 Axes&gt;</div></div></div></details></div>"
      ],
      "text/plain": [
       "<chatlab.display.ChatFunctionCall at 0x10f792e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " "
      ],
      "text/plain": [
       " "
      ]
     },
     "metadata": {
      "text/markdown": {
       "chatlab": {
        "default": true
       }
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "await chat.submit(\"Can you plot the number of open tickets per category and subcategory?\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (chatlab-dev)",
   "language": "python",
   "name": "python-chatlab-dev"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}