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"# Exploring Recent Shootings in Philadelphia with Altair, Folium, and Panel\n",
"\n",
"In this notebook, we create an example dashboard visualizing recent shootings in Philadelphia. The dashboard includes:\n",
"\n",
"- a Folium heatmap of the shootings from the past *X* days, where *X* is specified by the user\n",
"- an Altair histogram of victim ages\n",
"- an hvplot bar chart showing the number of shootings per day\n",
"- a slider for selecting the number of days to query shootings for\n",
"\n",
"#### References\n",
"\n",
"For more information, see the documentation:\n",
"\n",
"- [Documentation homepage](https://panel.holoviz.org)\n",
"- [App Gallery](https://panel.holoviz.org/gallery/index.html)\n",
" - Examples of end-to-end web apps using Panel\n",
"- [Component Gallery](https://panel.holoviz.org/reference/index.html)\n",
" - Examples (code snippets) for the types of panes, widgets, and layouts possible in Panel dashboards\n",
"- [Folium documentation](https://python-visualization.github.io/folium/)\n",
"\n",
"\n",
"For this dashboard, check out the following reference examples:\n",
"\n",
"1. See the **Altair/Vega** [reference gallery page](https://panel.holoviz.org/reference/panes/Vega.html) for more information about embedding Altair in Panel dashboards.\n",
"\n",
"2. See the **Folium** [reference gallery page](https://panel.holoviz.org/reference/panes/Folium.html) for more information about embedding Folium in Panel dashboards."
]
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"output_type": "display_data"
}
],
"source": [
"import panel as pn\n",
"\n",
"pn.extension(\"vega\") # Enables support for vega/altair"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import geopandas as gpd\n",
"import requests\n",
"\n",
"import holoviews as hv\n",
"import hvplot.pandas\n",
"import param as pm\n",
"\n",
"import altair as alt\n",
"import folium\n",
"from folium.plugins import HeatMap"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the full data set\n",
"\n",
"We'll load the full data set before initializing the app, and then the user will be able to filter and display subsets of the entire data set. \n",
"\n",
"The maximum of our slider will be 365 days, so we only need to query data from the past year. When the user slides the slider, we can select the subset of this full dataset to apply."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# The maximum number of days into past to query\n",
"# NOTE: this will be the maximum number of days the user will be allowed to select\n",
"MAX_DAYS = 365\n",
"MIN_DAYS = 30"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Query the CARTO API\n",
"\n",
"Get shooting victim data from Open Data Philly for all data within the last 365 days.\n",
"\n",
"[API Documentation](https://cityofphiladelphia.github.io/carto-api-explorer/#shootings)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# The CARTO API endpoint\n",
"CARTO_URL = \"https://phl.carto.com/api/v2/sql\"\n",
"\n",
"# Select everything within the last year\n",
"# NOTE: \"current_date\" is a SQL variable built in to the database\n",
"WHERE = f\"date_ >= current_date - {MAX_DAYS}\"\n",
"\n",
"# The query parameters\n",
"params = {\"q\": \"SELECT * FROM shootings\", \"format\": \"geojson\", \"where\": WHERE}\n",
"\n",
"# The request\n",
"response = requests.get(CARTO_URL, params=params)\n",
"\n",
"# Make the GeoDataFrame\n",
"DATA = gpd.GeoDataFrame.from_features(response.json(), crs=\"EPSG:4326\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Preprocess the data\n",
"\n",
"Do some preprocessing to clean up the data and format some columns."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Remove entries with missing values\n",
"DATA = DATA.dropna(subset=[\"point_x\", \"point_y\"])\n",
"\n",
"# Re-map the fatal column to Yes/No\n",
"DATA[\"fatal\"] = DATA[\"fatal\"].map({0: \"No\", 1: \"Yes\"})\n",
"\n",
"# Remove entries where fatal is NaN\n",
"DATA = DATA.dropna(subset=[\"fatal\"])\n",
"\n",
"# Parse the date_ column into a valid Datetime object\n",
"DATA[\"date_\"] = pd.to_datetime(DATA[\"date_\"].str.slice(0, 10), format=\"%Y-%m-%d\")\n",
"\n",
"# Add longitude and latitude columns\n",
"DATA[\"lat\"] = DATA.geometry.y\n",
"DATA[\"lng\"] = DATA.geometry.x"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Build the app\n",
"\n",
"We'll define our app as a custom Python class that defines the various components of our dashboard, which include:\n",
"\n",
"- The parameters we want the user to be able to change.\n",
"- Functions to generate the various charts/maps in our dashboard, based on those input parameters.\n",
"- The dependencies between our chart functions and parameters."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
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" async function embed_document(root) {\n",
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"\t const root_el = id_el.children[0]\n",
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" // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
"\t child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
"\t }\n",
"\t}\n",
" }\n",
" }\n",
" }\n",
" function get_bokeh(root) {\n",
" if (root.Bokeh === undefined) {\n",
" return null\n",
" } else if (root.Bokeh.version !== py_version) {\n",
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"\treturn null\n",
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" } else if (root.Bokeh.version === py_version) {\n",
" return root.Bokeh\n",
" }\n",
" return null\n",
" }\n",
" function is_loaded(root) {\n",
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" }\n",
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"\t var Bokeh = get_bokeh(root)\n",
"\t if (Bokeh == null || Bokeh.Panel == null) {\n",
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"\t } else {\n",
"\t console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
"\t embed_document(root)\n",
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" }, 25, root)\n",
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"})(window);</script>"
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"text/plain": [
"Row\n",
" [0] Param(ParameterizedMetaclass, name='PhiladelphiaShootingsApp'..., widgets={'start_date': {'type': <c...})"
]
},
"execution_count": 6,
"metadata": {
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"id": "5d6f37c1-01c0-4533-ade8-1c669f3cd3d6"
}
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}
],
"source": [
"from datetime import date, timedelta\n",
"\n",
"\n",
"class PhiladelphiaShootingsApp(pm.Parameterized):\n",
" \"\"\"\n",
" An example app visualizing recent shootings in Philadelphia.\n",
"\n",
" It includes:\n",
" - a date range widget for selecting the date range to query shootings for\n",
" - a Folium heatmap\n",
" - an Altair histogram\n",
" - an hvplot line chart\n",
"\n",
" Parameters:\n",
" - start_date: Start date of the range.\n",
" - end_date: End date of the range.\n",
" \"\"\"\n",
"\n",
" # Start and end date for the data range\n",
" start_date = pm.CalendarDate(default=(date.today() - timedelta(days=180)))\n",
" end_date = pm.CalendarDate(default=date.today())\n",
"\n",
" def filter_by_date_range(self):\n",
" \"\"\"\n",
" Return the subset of the full data set ('DATA') that\n",
" occurred within the selected date range.\n",
" \"\"\"\n",
" # Ensure DATA[\"date_\"] is converted to datetime.date for comparison\n",
" data_date = DATA[\"date_\"].dt.date\n",
" \n",
" # Filter the data based on the selected date range\n",
" mask = (data_date >= self.start_date) & (data_date <= self.end_date)\n",
" \n",
" # Subset and select necessary columns\n",
" subset = DATA.loc[mask]\n",
" COLS = [\"age\", \"fatal\", \"lat\", \"lng\", \"date_\"]\n",
" subset = subset[COLS]\n",
" \n",
" return subset\n",
" \n",
"\n",
" def get_daily_shootings(self):\n",
" \"\"\"\n",
" Return a DataFrame with two columns ('date_', 'count')\n",
" that gives the total number of shootings per day.\n",
" \"\"\"\n",
" # Filter by the selected date range\n",
" df = self.filter_by_date_range()\n",
"\n",
" # Group by date\n",
" grouper = pd.Grouper(freq=\"d\")\n",
" return df.set_index(\"date_\").groupby(grouper).size().reset_index(name=\"count\")\n",
"\n",
" @pm.depends(\"start_date\", \"end_date\")\n",
" def pane_daily_shootings_chart(self):\n",
" \"\"\"\n",
" Return an hvplot chart of daily shootings.\n",
" \"\"\"\n",
" # Get the daily shootings data\n",
" N = self.get_daily_shootings()\n",
"\n",
" # Plot the line chart\n",
" return N.hvplot.line(\n",
" x=\"date_\",\n",
" y=\"count\",\n",
" color=\"#cfcfcf\",\n",
" width=1200,\n",
" height=300,\n",
" )\n",
"\n",
" @pm.depends(\"start_date\", \"end_date\")\n",
" def pane_heatmap(self):\n",
" \"\"\"\n",
" Return a Folium map with a heatmap showing the data within the selected date range.\n",
" \"\"\"\n",
" m = folium.Map(location=[39.99, -75.13], tiles=\"Cartodb Positron\", zoom_start=12)\n",
" data = self.filter_by_date_range()\n",
" coordinates = data[[\"lat\", \"lng\"]].values\n",
" HeatMap(coordinates).add_to(m)\n",
" return pn.pane.plot.Folium(m, height=600)\n",
"\n",
" @pm.depends(\"start_date\", \"end_date\")\n",
" def pane_summary_text(self):\n",
" \"\"\"\n",
" Get a summary of the number of shootings and homicides.\n",
" \"\"\"\n",
" data = self.filter_by_date_range()\n",
" shootings = len(data)\n",
" homicides = (data.fatal == \"Yes\").sum()\n",
" t = f\"<p style='font-size: 20px'>There have been {shootings:,} shootings and {homicides:,} homicides between {self.start_date:%Y-%m-%d} and {self.end_date:%Y-%m-%d}.</p>\"\n",
" return pn.pane.HTML(t, width=550)\n",
"\n",
" @pm.depends(\"start_date\", \"end_date\")\n",
" def pane_altair_hist(self):\n",
" \"\"\"\n",
" Return an Altair histogram of shootings by age.\n",
" \"\"\"\n",
" data = self.filter_by_date_range()\n",
" chart = (\n",
" alt.Chart(data)\n",
" .mark_bar()\n",
" .encode(\n",
" x=alt.X(\"age:Q\", bin=True, scale=alt.Scale(domain=(0, 100))),\n",
" y=\"count()\",\n",
" color=\"fatal:N\",\n",
" tooltip=[\"count()\", \"age\", \"fatal\"],\n",
" )\n",
" .properties(\n",
" width=400, height=400, title=\"Number of Shootings by Victim's Age\"\n",
" )\n",
" )\n",
" return pn.pane.Vega(chart, width=600)\n",
"\n",
"# Replace `days` slider with date range picker in your dashboard layout\n",
"pn.Row(\n",
" pn.Param(\n",
" PhiladelphiaShootingsApp.param,\n",
" widgets={\n",
" \"start_date\": {\"type\": pn.widgets.DatePicker},\n",
" \"end_date\": {\"type\": pn.widgets.DatePicker},\n",
" },\n",
" )\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"app = PhiladelphiaShootingsApp(name=\"\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>fatal</th>\n",
" <th>lat</th>\n",
" <th>lng</th>\n",
" <th>date_</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>26</td>\n",
" <td>No</td>\n",
" <td>40.025375</td>\n",
" <td>-75.137133</td>\n",
" <td>2024-11-09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>35</td>\n",
" <td>No</td>\n",
" <td>40.023584</td>\n",
" <td>-75.153075</td>\n",
" <td>2024-11-27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>20</td>\n",
" <td>No</td>\n",
" <td>40.054625</td>\n",
" <td>-75.151251</td>\n",
" <td>2024-06-09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>15</td>\n",
" <td>No</td>\n",
" <td>40.028639</td>\n",
" <td>-75.143136</td>\n",
" <td>2024-06-14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td>15</td>\n",
" <td>No</td>\n",
" <td>40.028639</td>\n",
" <td>-75.143136</td>\n",
" <td>2024-06-14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16349</th>\n",
" <td>23</td>\n",
" <td>No</td>\n",
" <td>39.952611</td>\n",
" <td>-75.166064</td>\n",
" <td>2024-09-10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16350</th>\n",
" <td>39</td>\n",
" <td>Yes</td>\n",
" <td>40.042000</td>\n",
" <td>-75.061806</td>\n",
" <td>2024-11-06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16352</th>\n",
" <td>42</td>\n",
" <td>No</td>\n",
" <td>39.951111</td>\n",
" <td>-75.152784</td>\n",
" <td>2024-10-04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16359</th>\n",
" <td>34</td>\n",
" <td>No</td>\n",
" <td>40.029046</td>\n",
" <td>-75.210674</td>\n",
" <td>2024-08-30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16362</th>\n",
" <td>34</td>\n",
" <td>No</td>\n",
" <td>40.079412</td>\n",
" <td>-75.069179</td>\n",
" <td>2024-06-26</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>548 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" age fatal lat lng date_\n",
"30 26 No 40.025375 -75.137133 2024-11-09\n",
"32 35 No 40.023584 -75.153075 2024-11-27\n",
"36 20 No 40.054625 -75.151251 2024-06-09\n",
"47 15 No 40.028639 -75.143136 2024-06-14\n",
"48 15 No 40.028639 -75.143136 2024-06-14\n",
"... .. ... ... ... ...\n",
"16349 23 No 39.952611 -75.166064 2024-09-10\n",
"16350 39 Yes 40.042000 -75.061806 2024-11-06\n",
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"\n",
"[548 rows x 5 columns]"
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}
],
"source": [
"app.filter_by_date_range()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Layout our Panel object: Bootstrap template\n",
"\n",
"We can use a combination of the `Column()` and `Row()` objects in Panel to create the layout in the main component.\n",
"\n",
"We'll also use the [Bootstrap template](https://panel.holoviz.org/reference/templates/Bootstrap.html) to improve the aesthetics of the user interface.\n",
"\n",
"\n",
"- The `app.param` is an automatically generated set of widgets that corresponds to our `param` parameters\n",
"- The charts are specified as the functions of our main application, e.g., app.bar_chart is the function that will return our bar chart.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Create a text HTML element to show instructions below the daily shootings chart and the title of the app:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"panel = pn.template.BootstrapTemplate(\n",
" title=\"Recent Shootings in Philadelphia\",\n",
" sidebar_width=0, # No sidebar needed for this app\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n",
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n"
]
}
],
"source": [
"# Append the content to the main part of the dashboard\n",
"panel.main.append(\n",
" pn.Column(\n",
" pn.Row(app.pane_summary_text, app.param),\n",
" pn.Row(app.pane_altair_hist, app.pane_heatmap),\n",
" pn.Row(app.pane_daily_shootings_chart, align=\"center\"),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Call servable() and render our Panel object\n",
"\n",
"- The final step is to call the `.servable()` function\n",
"- This will render the dashboard directly in the notebook\n",
"- It also enables the notebook to be served from `localhost`.\n",
"\n",
"<div style=\"color: red; font-weight: bold;\">\n",
"Since we're using a template, the dashboard won't render properly in the notebook! You'll need to run it from the command line (Miniforge Prompt or Terminal).\n",
"</div>\n",
"\n",
"\n",
"From the command line, we will run:\n",
"\n",
"```\n",
"panel serve --show shootingApp.ipynb\n",
"```\n",
"\n",
"And see the app live at: `http://localhost:5006/app2`"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n",
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n",
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n",
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n",
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n",
"/Users/delmelle/miniforge3/lib/python3.10/site-packages/altair/utils/core.py:384: FutureWarning: the convert_dtype parameter is deprecated and will be removed in a future version. Do ``ser.astype(object).apply()`` instead if you want ``convert_dtype=False``.\n",
" col = df[col_name].apply(to_list_if_array, convert_dtype=False)\n"
]
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" <link rel=\"stylesheet\" href=\"static/extensions/panel/css/loadingspinner.css?v=1.5.4\">\n",
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" const timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
" })(window);\n",
" });\n",
" };\n",
" if (document.readyState != \"loading\") fn();\n",
" else document.addEventListener(\"DOMContentLoaded\", fn, {once: true});\n",
" })();\n",
" </script>\n",
" </body>\n",
"</html>"
],
"text/plain": [
"BootstrapTemplate\n",
" [js_area] HTML(None, height=0, margin=0, sizing_mode='fixed', width=0)\n",
" [actions] BootstrapTemplateActions()\n",
" [browser_info] BrowserInfo(dark_mode=False, device_pixel_ratio=2.2222222222222223, language='en-US', timezone='America/New_York', timezone_offset=300, webdriver=False, webgl=True)\n",
" [busy_indicator] LoadingSpinner(height=20, width=20)\n",
" [main-5118059248] Column\n",
" [0] Row\n",
" [0] ParamMethod(method, _pane=HTML, defer_load=False)\n",
" [1] Column(margin=(5, 10))\n",
" [0] StaticText(value='<b></b>')\n",
" [1] DatePicker(name='Start date', value=datetime.date(2024, 6, 8))\n",
" [2] DatePicker(name='End date', value=datetime.date(2024, ...)\n",
" [1] Row\n",
" [0] ParamMethod(method, _pane=Vega, defer_load=False)\n",
" [1] ParamMethod(method, _pane=Folium, defer_load=False)\n",
" [2] Row(align='center')\n",
" [0] ParamMethod(method, _pane=HoloViews, defer_load=False)"
]
},
"execution_count": 12,
"metadata": {
"application/vnd.holoviews_exec.v0+json": {
"id": "9b5211ef-f8c9-477b-9d3e-86a1de443650"
}
},
"output_type": "execute_result"
}
],
"source": [
"panel.servable()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"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": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
|