{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Styling Bokeh plots\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " Loading BokehJS ...\n", "
\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " const force = true;\n", "\n", " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", " root._bokeh_onload_callbacks = [];\n", " root._bokeh_is_loading = undefined;\n", " }\n", "\n", "const JS_MIME_TYPE = 'application/javascript';\n", " const HTML_MIME_TYPE = 'text/html';\n", " const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", " const CLASS_NAME = 'output_bokeh rendered_html';\n", "\n", " /**\n", " * Render data to the DOM node\n", " */\n", " function render(props, node) {\n", " const script = document.createElement(\"script\");\n", " node.appendChild(script);\n", " }\n", "\n", " /**\n", " * Handle when an output is cleared or removed\n", " */\n", " function handleClearOutput(event, handle) {\n", " const cell = handle.cell;\n", "\n", " const id = cell.output_area._bokeh_element_id;\n", " const server_id = cell.output_area._bokeh_server_id;\n", " // Clean up Bokeh references\n", " if (id != null && id in Bokeh.index) {\n", " Bokeh.index[id].model.document.clear();\n", " delete Bokeh.index[id];\n", " }\n", "\n", " if (server_id !== undefined) {\n", " // Clean up Bokeh references\n", " const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", " cell.notebook.kernel.execute(cmd_clean, {\n", " iopub: {\n", " output: function(msg) {\n", " const id = msg.content.text.trim();\n", " if (id in Bokeh.index) {\n", " Bokeh.index[id].model.document.clear();\n", " delete Bokeh.index[id];\n", " }\n", " }\n", " }\n", " });\n", " // Destroy server and session\n", " const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", " cell.notebook.kernel.execute(cmd_destroy);\n", " }\n", " }\n", "\n", " /**\n", " * Handle when a new output is added\n", " */\n", " function handleAddOutput(event, handle) {\n", " const output_area = handle.output_area;\n", " const output = handle.output;\n", "\n", " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n", " return\n", " }\n", "\n", " const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", "\n", " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", " // store reference to embed id on output_area\n", " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", " }\n", " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", " const bk_div = document.createElement(\"div\");\n", " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", " const script_attrs = bk_div.children[0].attributes;\n", " for (let i = 0; i < script_attrs.length; i++) {\n", " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", " }\n", " // store reference to server id on output_area\n", " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", " }\n", " }\n", "\n", " function register_renderer(events, OutputArea) {\n", "\n", " function append_mime(data, metadata, element) {\n", " // create a DOM node to render to\n", " const toinsert = this.create_output_subarea(\n", " metadata,\n", " CLASS_NAME,\n", " EXEC_MIME_TYPE\n", " );\n", " this.keyboard_manager.register_events(toinsert);\n", " // Render to node\n", " const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", " render(props, toinsert[toinsert.length - 1]);\n", " element.append(toinsert);\n", " return toinsert\n", " }\n", "\n", " /* Handle when an output is cleared or removed */\n", " events.on('clear_output.CodeCell', handleClearOutput);\n", " events.on('delete.Cell', handleClearOutput);\n", "\n", " /* Handle when a new output is added */\n", " events.on('output_added.OutputArea', handleAddOutput);\n", "\n", " /**\n", " * Register the mime type and append_mime function with output_area\n", " */\n", " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", " /* Is output safe? */\n", " safe: true,\n", " /* Index of renderer in `output_area.display_order` */\n", " index: 0\n", " });\n", " }\n", "\n", " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", " if (root.Jupyter !== undefined) {\n", " const events = require('base/js/events');\n", " const OutputArea = require('notebook/js/outputarea').OutputArea;\n", "\n", " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", " register_renderer(events, OutputArea);\n", " }\n", " }\n", " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", "\n", " const NB_LOAD_WARNING = {'data': {'text/html':\n", " \"
\\n\"+\n", " \"

\\n\"+\n", " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", " \"

\\n\"+\n", " \"\\n\"+\n", " \"\\n\"+\n", " \"from bokeh.resources import INLINE\\n\"+\n", " \"output_notebook(resources=INLINE)\\n\"+\n", " \"\\n\"+\n", " \"
\"}};\n", "\n", " function display_loaded() {\n", " const el = document.getElementById(\"fbd3eca6-de7f-4dfd-aa44-bd0f10dec108\");\n", " if (el != null) {\n", " el.textContent = \"BokehJS is loading...\";\n", " }\n", " if (root.Bokeh !== undefined) {\n", " if (el != null) {\n", " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", " }\n", " } else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(display_loaded, 100)\n", " }\n", " }\n", "\n", " function run_callbacks() {\n", " try {\n", " root._bokeh_onload_callbacks.forEach(function(callback) {\n", " if (callback != null)\n", " callback();\n", " });\n", " } finally {\n", " delete root._bokeh_onload_callbacks\n", " }\n", " console.debug(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(css_urls, js_urls, callback) {\n", " if (css_urls == null) css_urls = [];\n", " if (js_urls == null) js_urls = [];\n", "\n", " root._bokeh_onload_callbacks.push(callback);\n", " if (root._bokeh_is_loading > 0) {\n", " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", " if (js_urls == null || js_urls.length === 0) {\n", " run_callbacks();\n", " return null;\n", " }\n", " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", "\n", " function on_load() {\n", " root._bokeh_is_loading--;\n", " if (root._bokeh_is_loading === 0) {\n", " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", " run_callbacks()\n", " }\n", " }\n", "\n", " function on_error(url) {\n", " console.error(\"failed to load \" + url);\n", " }\n", "\n", " for (let i = 0; i < css_urls.length; i++) {\n", " const url = css_urls[i];\n", " const element = document.createElement(\"link\");\n", " element.onload = on_load;\n", " element.onerror = on_error.bind(null, url);\n", " element.rel = \"stylesheet\";\n", " element.type = \"text/css\";\n", " element.href = url;\n", " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", " document.body.appendChild(element);\n", " }\n", "\n", " for (let i = 0; i < js_urls.length; i++) {\n", " const url = js_urls[i];\n", " const element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error.bind(null, url);\n", " element.async = false;\n", " element.src = url;\n", " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", " };\n", "\n", " function inject_raw_css(css) {\n", " const element = document.createElement(\"style\");\n", " element.appendChild(document.createTextNode(css));\n", " document.body.appendChild(element);\n", " }\n", "\n", " const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.2.1.min.js\"];\n", " const css_urls = [];\n", "\n", " const inline_js = [ function(Bokeh) {\n", " Bokeh.set_log_level(\"info\");\n", " },\n", "function(Bokeh) {\n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " if (root.Bokeh !== undefined || force === true) {\n", " for (let i = 0; i < inline_js.length; i++) {\n", " inline_js[i].call(root, root.Bokeh);\n", " }\n", "if (force === true) {\n", " display_loaded();\n", " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", " root._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", " const cell = $(document.getElementById(\"fbd3eca6-de7f-4dfd-aa44-bd0f10dec108\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", " }\n", "\n", " if (root._bokeh_is_loading === 0) {\n", " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", " run_inline_js();\n", " } else {\n", " load_libs(css_urls, js_urls, function() {\n", " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", " run_inline_js();\n", " });\n", " }\n", "}(window));" ], "application/vnd.bokehjs_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n const NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n const el = document.getElementById(\"fbd3eca6-de7f-4dfd-aa44-bd0f10dec108\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.2.1.min.js\"];\n const css_urls = [];\n\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {\n }\n ];\n\n function run_inline_js() {\n if (root.Bokeh !== undefined || force === true) {\n for (let i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\nif (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n const cell = $(document.getElementById(\"fbd3eca6-de7f-4dfd-aa44-bd0f10dec108\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "\n", "import iqplot\n", "\n", "import colorcet\n", "\n", "import bokeh.io\n", "import bokeh.plotting\n", "import bokeh.models\n", "import bokeh.themes\n", "\n", "bokeh.io.output_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "We have seen how to use Bokeh (and the higher-level plotting package iqplot) to make interactive plots. We have seen how to adjust plot size, axis labels, glyph color, etc., but we have just started to touch the surface of how we might customize plots. In this lesson, we investigate ways to stylize Bokeh plots to our visual preferences.\n", "\n", "Before we get into the lower-level styling, we will first go over some of the styling available in iqplot. We will again use the frog strike data set, so let's load it in." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv('../data/frog_tongue_adhesion.csv', comment='#')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Customization with iqplot\n", "\n", "All of `iqplot`'s high-level plotting functions take `data`, `q`, and `cats` arguments. Additionally, each of the plotting functions also has the following additional optional keyword arguments, as described above.\n", "\n", "- `q_axis`: Along which axis, x or y that the quantitative variable varies. The default is `'x'`.\n", "- `palette`: A list of hex colors to use for coloring the markers for each category. By default, it uses the Glasbey Category 10 color palette from [colorcet](https://colorcet.holoviz.org/).\n", "- `order`: If specified, the ordering of the categories to use on the categorical axis and legend (if applicable). Otherwise, the order of the inputted data frame is used.\n", "- `p`: If specified, the `bokeh.plotting.Figure` object to use for the plot. If not specified, a new figure is created.\n", "\n", "The respective plotting functions also have kwargs that are specific to each (such as `style` for `iqplot.ecdf()`. Examples highlighting some, but not all, customizations follow. You can find out what kwargs are available for each function by reading their doc strings, e.g., with\n", "\n", "```python\n", "iqplot.box?\n", "```\n", "\n", "Any kwargs not in the function call signature are passed to `bokeh.plotting.figure()` when the figure is instantiated." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Customizing box plots\n", "\n", "We can also have vertical box plots." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " 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);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1002" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.box(\n", " data=df,\n", " q=\"impact force (mN)\",\n", " cats=\"ID\",\n", " q_axis='y',\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can independently specify properties of the glyphs using `box_kwargs`, `whisker_kwargs`, `median_kwargs`, 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console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1085" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.box(\n", " data=df,\n", " q=\"impact force (mN)\",\n", " cats=\"ID\",\n", " whisker_caps=True,\n", " outlier_marker='diamond',\n", " box_kwargs=dict(fill_color='#7C0000'),\n", " whisker_kwargs=dict(line_color='#7C0000', line_width=2),\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Custominzing strip plots\n", "\n", "To help alleviate the overlap problem, we can make a strip plot with dash markers and add some transparency." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1183" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.strip(\n", " data=df,\n", " q=\"impact force (mN)\",\n", " cats=\"ID\",\n", " marker='dash',\n", " marker_kwargs=dict(alpha=0.5)\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The problem with strip plots is that they can have trouble with overlapping data points. 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force (mN)\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1329\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1330\",\"attributes\":{\"axis\":{\"id\":\"p1326\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1335\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1331\"},\"grid_line_color\":null}}],\"frame_height\":275}}]}};\n", " const render_items = [{\"docid\":\"def817bb-9d28-489b-8538-48c6647386f3\",\"roots\":{\"p1315\":\"b2d3ab4c-dc0a-42a9-a466-db50badfce4c\"},\"root_ids\":[\"p1315\"]}];\n", " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " 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);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1315" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.strip(\n", " data=df,\n", " q=\"impact force (mN)\",\n", " cats=['ID', 'trial number'],\n", " color_column='trial number',\n", " width=550,\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Customizing histograms\n", "\n", "We could plot normalized histograms using the density kwarg. To generate data to plot, we will draw random numbers, which we will learn how to do in a future lesson." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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" const render_items = [{\"docid\":\"b0054cee-a8d1-4f08-a097-61b04810e215\",\"roots\":{\"p1420\":\"a44b02e7-0980-4389-8541-0fef4a0f5bf1\"},\"root_ids\":[\"p1420\"]}];\n", " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " 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);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1420" } }, "output_type": "display_data" } ], "source": [ "# Generate normally distributed data\n", "x = np.random.standard_normal(size=100000)\n", "\n", "# Plot the histogram\n", "p = iqplot.histogram(x, bins=50, density=True, rug=False)\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Customizing ECDFs\n", "\n", "Instead of plotting a separate ECDF for each category, we can put all of the categories together on one ECDF and color the points by the categorical variable by using the `kind='colored'` kwarg. 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Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1459" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.ecdf(\n", " data=df,\n", " q=\"impact force (mN)\",\n", " cats=\"ID\",\n", " kind='colored',\n", " tooltips=[\n", " ('trial', '@{trial number}'),\n", " ('adh force', '@{adhesive force (mN)}')\n", " ], \n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Styling Bokeh plots as they are built\n", "\n", "We now move into lower-level styling of Bokeh plots in general. Bokeh figures and renderers (which are essentially the glyphs) have a plethora of attributes pertaining to visual appearance that may be adjusted at instantiation and after making a plot. As an example, let us again make a plot from the face-matching data set. We'll naturally start by loading the data set." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"../data/gfmt_sleep.csv\", na_values=\"*\")\n", "df[\"insomnia\"] = df[\"sci\"] <= 16" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A **color palette** an ordering of colors that are used for glyphs, usually corresponding to categorical data. [Colorcet's Glasbey Category 10](https://colorcet.holoviz.org/user_guide/Categorical.html#starting-colors) provides a good palette for categorical data, and we store this as our categorical colors for plotting." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "cat_colors = colorcet.b_glasbey_category10" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can build the plot. Since the data are percentages, we will set the axes to go from zero to 100 and enforce that the figure is square. We will also include a title as well so we can style that." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "p = bokeh.plotting.figure(\n", " frame_width=300,\n", " frame_height=300,\n", " x_axis_label=\"confidence when correct\",\n", " y_axis_label=\"condifence when incorrect\",\n", " title=\"GMFT with sleep conditions\",\n", " x_range=[0, 100],\n", " y_range=[0, 100],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In styling this plot, we will also put the legend outside of the plot area. This is a bit trickier than what we have been doing using the `legend_label` kwarg in `p.circle()`. To get a legend outside of the plot area, we need to:\n", "\n", "1. Assign each glyph to a variable.\n", "2. Instantiate a `bokeh.models.Legend` object using the stored variables containing the glyphs. This is instantiated as `bokeh.models.Legend(items=legend_items)`, where `legend_items` is a list of 2-tuples. In each 2-tuple, the first entry is a string with the text used to label the glyph. The second entry is a list of glyphs that have the label.\n", "3. Add the legend to the figure using the `add_layout()` method.\n", "\n", "Now, we add the glyphs, storing them as variables `normal_glyph` and `insom_glyph`." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# Set up sources\n", "source_insomnia = bokeh.models.ColumnDataSource(df.loc[df['insomnia'], :])\n", "source_normal = bokeh.models.ColumnDataSource(df.loc[~df['insomnia'], :])\n", "\n", "normal_glyph = p.circle(\n", " source=source_normal,\n", " x=\"confidence when correct\",\n", " y=\"confidence when incorrect\",\n", " color=cat_colors[0],\n", ")\n", "\n", "insom_glyph = p.circle(\n", " source=source_insomnia,\n", " x=\"confidence when correct\",\n", " y=\"confidence when incorrect\",\n", " color=cat_colors[1],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can construct and add the legend." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# Construct legend items\n", "legend_items = [('normal', [normal_glyph]), ('insomnia', [insom_glyph])]\n", "\n", "# Instantiate legend\n", "legend = bokeh.models.Legend(items=legend_items, click_policy='hide')\n", "\n", "# Add the legend to the right of the plot\n", "p.add_layout(legend, 'right')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let's take a look at this beauty!" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1561" } }, "output_type": "display_data" } ], "source": [ "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Styling Bokeh plots after they are built\n", "\n", "After building a plot, we sometimes want to adjust styling. To do so, we need to change attributes of the object `p`. For example, let's look at the font of the x-axis label." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'helvetica'" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "p.xaxis.axis_label_text_font" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also look at the style and size of the font." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "('italic', '13px')" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "p.xaxis.axis_label_text_font_style, p.xaxis.axis_label_text_font_size" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, the default axis labels for Bokeh are italicized 13 pt Helvetica. I personally think this choice if fine, but we may have other preferences.\n", "\n", "To find out all of the available options to tweak, I usually type something like `p.` and hit tab to see what the options are. Finding `p.xaxis` is an option, then type `p.xaxis.` and hit tab again to see the styling option there.\n", "\n", "Using this technique, we can set some obnoxious styling for this plot. I will make all of the fonts non-italicized, large [papyrus](https://www.youtube.com/watch?v=jVhlJNJopOQ). I can also set the background and grid colors. Note that in Bokeh, any [named CSS color](https://css-tricks.com/snippets/css/named-colors-and-hex-equivalents/) or any valid [HEX code](https://en.wikipedia.org/wiki/Web_colors#Hex_triplet), entered as a string, is a valid color.\n", "\n", "Before we do the obnoxious styling, we will do one adjustment that is useful. Note in the above plot that the glyphs at the end of the plot are cropped. We would like the whole glyph to show. To do that, we set the **level** of the glyphs to be `'overlay'`. To do that, we extract the first two elements of the list of renderers, which contains the glyphs, and set the `level` attribute." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "p.renderers[0].level = 'overlay'\n", "p.renderers[1].level = 'overlay'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can proceed to make our obnoxious styling." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " 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);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1561" } }, "output_type": "display_data" } ], "source": [ "# Obnoxious fonts\n", "p.xaxis.major_label_text_font = 'papyrus'\n", "p.xaxis.major_label_text_font_size = '14pt'\n", "p.xaxis.axis_label_text_font = 'papyrus'\n", "p.xaxis.axis_label_text_font_style = 'normal'\n", "p.xaxis.axis_label_text_font_size = '20pt'\n", "p.yaxis.major_label_text_font = 'papyrus'\n", "p.yaxis.major_label_text_font_size = '14pt'\n", "p.yaxis.axis_label_text_font = 'papyrus'\n", "p.yaxis.axis_label_text_font_style = 'normal'\n", "p.yaxis.axis_label_text_font_size = '20pt'\n", "p.title.text_font = 'papyrus'\n", "p.title.text_font_size = '18pt'\n", "p.legend.label_text_font = 'papyrus'\n", "\n", "# Align the title center\n", "p.title.align = 'center'\n", "\n", "# Set background and grid color\n", "p.background_fill_color = 'blanchedalmond'\n", "p.legend.background_fill_color = 'chartreuse'\n", "p.xgrid.grid_line_color = 'azure'\n", "p.ygrid.grid_line_color = 'azure'\n", "\n", "# Make the ticks point inward (I *hate* this!)\n", "# Units are pixels that the ticks extend in and out of plot\n", "p.xaxis.major_tick_out = 0\n", "p.xaxis.major_tick_in = 10\n", "p.xaxis.minor_tick_out = 0\n", "p.xaxis.minor_tick_in = 5\n", "p.yaxis.major_tick_out = 0\n", "p.yaxis.major_tick_in = 10\n", "p.yaxis.minor_tick_out = 0\n", "p.yaxis.minor_tick_in = 5\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is truly hideous, but it demonstrates how we can go about styling plots after they are made." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Bokeh themes\n", "\n", "Bokeh has several built-in [themes](https://docs.bokeh.org/en/latest/docs/reference/themes.html) which you can apply to all plots in a given document (e.g., in a notebook). Please see the [documentation](https://docs.bokeh.org/en/latest/docs/reference/themes.html) for details about the built-in themes. I personally prefer the default styling to all of their themes, but your opinion may differ.\n", "\n", "You may also specify custom themes using [JSON](https://www.json.org/json-en.html) or [YAML](https://yaml.org). As an example, we can specify a theme such that plots are styled like the default style of the excellent plotting packages [Vega-Altair](https://altair-viz.github.io/)/[Vega-Lite](http://vega.github.io/vega-lite)/[Vega](http://vega.github.io/vega). If we use JSON formatting, we can specify a theme as a dictionary of dictionaries, as below." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "altair_theme_dict = {\n", " \"attrs\": {\n", " \"Axis\": {\n", " \"axis_line_color\": \"dimgray\",\n", " \"minor_tick_out\": 0,\n", " \"major_tick_in\": 0,\n", " \"major_tick_line_color\": \"dimgray\",\n", " \"major_label_text_font_size\": \"7.5pt\",\n", " \"axis_label_text_font_size\": \"8pt\",\n", " \"axis_label_text_font_style\": \"bold\",\n", " },\n", " \"Circle\": {\n", " \"fill_alpha\": 0, \n", " \"line_width\": 2, \n", " \"size\": 5, \n", " \"line_alpha\": 0.7,\n", " },\n", " \"ContinuousTicker\": {\n", " \"desired_num_ticks\": 10\n", " },\n", " \"figure\": {\n", " \"frame_width\": 350, \n", " \"frame_height\": 300,\n", " },\n", " \"Grid\": {\n", " \"grid_line_color\": \"lightgray\",\n", " \"level\": \"underlay\",\n", " },\n", " \"Legend\": {\n", " \"border_line_color\": None,\n", " \"background_fill_color\": None,\n", " \"label_text_font_size\": \"7.5pt\",\n", " \"title_text_font_size\": \"8pt\",\n", " \"title_text_font_style\": \"bold\",\n", " },\n", " \"Renderer\": {\n", " \"level\": \"overlay\"\n", " },\n", " \"Title\": {\n", " \"align\": \"center\",\n", " },\n", " }\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To activate the theme, we convert it to a Bokeh theme and then add it to the `curdoc()`, or the current document." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "altair_theme = bokeh.themes.Theme(json=altair_theme_dict)\n", "\n", "bokeh.io.curdoc().theme = altair_theme" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now the theme is activated, and future plots will have this theme by default. Let's remake our plot using this theme. For convenience later on, I will write a function to generate this scatter plot that we will use to test various styles." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " 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);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1683" } }, "output_type": "display_data" } ], "source": [ "def gfmt_plot():\n", " \"\"\"Make a plot for testing out styles in this notebook.\"\"\"\n", " p = bokeh.plotting.figure(\n", " frame_width=300,\n", " frame_height=300,\n", " x_axis_label=\"confidence when correct\",\n", " y_axis_label=\"condifence when incorrect\",\n", " title=\"GMFT with sleep conditions\",\n", " x_range=[0, 100],\n", " y_range=[0, 100],\n", " )\n", "\n", " normal_glyph = p.circle(\n", " source=source_normal,\n", " x=\"confidence when correct\",\n", " y=\"confidence when incorrect\",\n", " color=cat_colors[0],\n", " )\n", "\n", " insom_glyph = p.circle(\n", " source=source_insomnia,\n", " x=\"confidence when correct\",\n", " y=\"confidence when incorrect\",\n", " color=cat_colors[1],\n", " )\n", "\n", " # Construct legend items\n", " legend_items = [('normal', [normal_glyph]), ('insomnia', [insom_glyph])]\n", "\n", " # Instantiate legend\n", " legend = bokeh.models.Legend(items=legend_items, click_policy='hide')\n", "\n", " # Add the legend to the right of the plot\n", " p.add_layout(legend, 'right')\n", " \n", " return p\n", "\n", "bokeh.io.show(gfmt_plot())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We could also style our plots to resemble the default \"dark\" styling of [Seaborn](https://seaborn.pydata.org)." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "seaborn_theme_dict = {\n", " \"attrs\": {\n", " \"figure\": {\n", " \"background_fill_color\": \"#eaeaf2\",\n", " \"frame_height\": 300,\n", " \"frame_width\": 350,\n", " },\n", " \"Axis\": {\n", " \"axis_line_color\": None,\n", " \"minor_tick_out\": 0,\n", " \"major_tick_in\": 0,\n", " \"major_tick_out\": 0,\n", " \"major_label_text_font_size\": \"7.5pt\",\n", " \"axis_label_text_font_size\": \"7.5pt\",\n", " \"axis_label_text_font_style\": \"normal\",\n", " },\n", " \"Legend\": {\n", " \"border_line_color\": \"darkgray\",\n", " \"background_fill_color\": \"#eaeaf2\",\n", " \"border_line_width\": 0.75,\n", " \"label_text_font_size\": \"7.5pt\",\n", " },\n", " \"Grid\": {\n", " \"grid_line_color\": \"#FFFFFF\", \n", " \"grid_line_width\": 0.75,\n", " },\n", " \"Title\": {\n", " \"align\": \"center\",\n", " 'text_font_style': 'normal',\n", " 'text_font_size': \"8pt\",\n", " },\n", " }\n", "}\n", "\n", "seaborn_theme = bokeh.themes.Theme(json=seaborn_theme_dict)\n", "bokeh.io.curdoc().theme = seaborn_theme" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's make the plot, yet again, with this new styling." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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when correct\",\"axis_label_text_font_size\":\"9pt\",\"axis_label_text_font_style\":\"bold\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1951\"},\"major_label_text_font_size\":\"7.5pt\",\"axis_line_color\":\"dimgray\",\"major_tick_line_color\":\"dimgray\"}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1952\",\"attributes\":{\"level\":\"underlay\",\"axis\":{\"id\":\"p1948\"},\"grid_line_color\":\"lightgray\"}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1957\",\"attributes\":{\"level\":\"underlay\",\"dimension\":1,\"axis\":{\"id\":\"p1953\"},\"grid_line_color\":\"lightgray\"}}],\"frame_width\":300,\"frame_height\":300}}]}};\n", " const render_items = [{\"docid\":\"c087b104-988f-413f-98f9-a19b5b156c5d\",\"roots\":{\"p1935\":\"e5f7931f-ed16-4d6f-a291-e048ea73c5b1\"},\"root_ids\":[\"p1935\"]}];\n", " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " 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);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1935" } }, "output_type": "display_data" } ], "source": [ "p = bokeh.plotting.figure(\n", " frame_width=300,\n", " frame_height=300,\n", " x_axis_label=\"confidence when correct\",\n", " y_axis_label=\"condifence when incorrect\",\n", " x_range=[-2.5, 102.5],\n", " y_range=[-2.5, 102.5],\n", ")\n", "\n", "normal_glyph = p.circle(\n", " source=source_normal,\n", " x=\"confidence when correct\",\n", " y=\"confidence when incorrect\",\n", " color=cat_colors[0],\n", ")\n", "\n", "insom_glyph = p.circle(\n", " source=source_insomnia,\n", " x=\"confidence when correct\",\n", " y=\"confidence when incorrect\",\n", " color=cat_colors[1],\n", ")\n", "\n", "# Construct legend items\n", "legend_items = [('normal', [normal_glyph]), ('insomnia', [insom_glyph])]\n", "\n", "# Instantiate legend\n", "legend = bokeh.models.Legend(items=legend_items, click_policy='hide')\n", "\n", "# Add the legend to the right of the plot\n", "p.add_layout(legend, 'right')\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can play with these themes and develop your own style as you see fit. As you can see, Bokeh is highly configurable, and you can really make the plots your own!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python implementation: CPython\n", "Python version : 3.11.4\n", "IPython version : 8.12.2\n", "\n", "numpy : 1.24.3\n", "pandas : 2.0.3\n", "bokeh : 3.2.1\n", "iqplot : 0.3.4\n", "jupyterlab: 4.0.5\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,pandas,bokeh,iqplot,jupyterlab" ] } ], "metadata": { "anaconda-cloud": {}, "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": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 4 }