{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "fiscal-holly",
"metadata": {},
"outputs": [
{
"data": {
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" var script = document.createElement(\"script\");\n",
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"})];\n",
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" --header-text-color: #474747;\n",
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" --background: #303030;\n",
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" --background-hover: #464646;\n",
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"p.dataframe_description {\n",
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" background-color: var(--background);\n",
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"\n",
"table.dataframe tbody > tr:nth-child(odd) {\n",
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"}\n",
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"}\n",
"\n",
"table.dataframe a:hover {\n",
" color: var(--link-hover);\n",
" text-decoration: underline;\n",
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"\n",
"table.dataframe img {\n",
" max-width: fit-content;\n",
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"\n",
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" background-color: var(--background);\n",
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"\n",
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" height: 8px;\n",
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"\n",
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" display: flex;\n",
" align-items: center;\n",
"}\n",
"\n",
"/* formatting */\n",
"\n",
"table.dataframe .null {\n",
" color: var(--text-color-pale);\n",
"}\n",
"\n",
"table.dataframe .structural {\n",
" color: var(--text-color-medium);\n",
" font-weight: bold;\n",
"}\n",
"\n",
"table.dataframe .dataFrameCaption {\n",
" font-weight: bold;\n",
"}\n",
"\n",
"table.dataframe .numbers {\n",
" color: var(--text-color-dark);\n",
"}\n",
"\n",
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"\n",
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%useLatestDescriptors\n",
"%use lets-plot\n",
"%use dataframe"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "worthy-cedar",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Lets-Plot Kotlin API v.4.4.2. Frontend: Notebook with dynamically loaded JS. Lets-Plot JS v.4.0.0."
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LetsPlot.getInfo()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "weird-republican",
"metadata": {},
"outputs": [
{
"data": {
"application/kotlindataframe+json": "{\"nrow\":3,\"ncol\":12,\"columns\":[\"untitled\",\"manufacturer\",\"model\",\"displ\",\"year\",\"cyl\",\"trans\",\"drv\",\"cty\",\"hwy\",\"fl\",\"class\"],\"kotlin_dataframe\":[{\"untitled\":1,\"manufacturer\":\"audi\",\"model\":\"a4\",\"displ\":1.8,\"year\":1999,\"cyl\":4,\"trans\":\"auto(l5)\",\"drv\":\"f\",\"cty\":18,\"hwy\":29,\"fl\":\"p\",\"class\":\"compact\"},{\"untitled\":2,\"manufacturer\":\"audi\",\"model\":\"a4\",\"displ\":1.8,\"year\":1999,\"cyl\":4,\"trans\":\"manual(m5)\",\"drv\":\"f\",\"cty\":21,\"hwy\":29,\"fl\":\"p\",\"class\":\"compact\"},{\"untitled\":3,\"manufacturer\":\"audi\",\"model\":\"a4\",\"displ\":2.0,\"year\":2008,\"cyl\":4,\"trans\":\"manual(m6)\",\"drv\":\"f\",\"cty\":20,\"hwy\":31,\"fl\":\"p\",\"class\":\"compact\"}]}",
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" :root {\n",
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" --link-hover: #1a466c;\n",
"}\n",
"\n",
":root[theme=\"dark\"], :root [data-jp-theme-light=\"false\"], .dataframe_dark{\n",
" --background: #303030;\n",
" --background-odd: #3c3c3c;\n",
" --background-hover: #464646;\n",
" --header-text-color: #dddddd;\n",
" --text-color: #b3b3b3;\n",
" --text-color-dark: #dddddd;\n",
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" color: var(--text-color-dark);\n",
" border: none;\n",
" border-collapse: collapse;\n",
"}\n",
"\n",
"table.dataframe th, td {\n",
" padding: 6px;\n",
" border: 1px solid transparent;\n",
" text-align: left;\n",
"}\n",
"\n",
"table.dataframe th {\n",
" background-color: var(--background);\n",
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"\n",
"table.dataframe td {\n",
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"\n",
"table.dataframe th.bottomBorder {\n",
" border-bottom-color: var(--bold-border-color);\n",
"}\n",
"\n",
"table.dataframe tbody > tr:nth-child(odd) {\n",
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" text-decoration: none;\n",
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"\n",
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" max-width: fit-content;\n",
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"\n",
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" width: 8px;\n",
" height: 8px;\n",
" margin-right: 3px;\n",
"}\n",
"\n",
"table.dataframe .expander {\n",
" display: flex;\n",
" align-items: center;\n",
"}\n",
"\n",
"/* formatting */\n",
"\n",
"table.dataframe .null {\n",
" color: var(--text-color-pale);\n",
"}\n",
"\n",
"table.dataframe .structural {\n",
" color: var(--text-color-medium);\n",
" font-weight: bold;\n",
"}\n",
"\n",
"table.dataframe .dataFrameCaption {\n",
" font-weight: bold;\n",
"}\n",
"\n",
"table.dataframe .numbers {\n",
" color: var(--text-color-dark);\n",
"}\n",
"\n",
"table.dataframe td:hover .formatted .structural, .null {\n",
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" </head>\n",
" <body>\n",
" \n",
"<table class=\"dataframe\" id=\"df_-1426063360\"></table>\n",
"\n",
"<p class=\"dataframe_description\">DataFrame: rowsCount = 3, columnsCount = 12</p>\n",
" </body>\n",
" <script>\n",
" \n",
"/*<!--*/\n",
"call_DataFrame(function() { DataFrame.addTable({ cols: [{ name: \"<span title=\\\"untitled: Int\\\">untitled</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">3</span></span>\"] }, \n",
"{ name: \"<span title=\\\"manufacturer: String\\\">manufacturer</span>\", children: [], rightAlign: false, values: [\"audi\",\"audi\",\"audi\"] }, \n",
"{ name: \"<span title=\\\"model: String\\\">model</span>\", children: [], rightAlign: false, values: [\"a4\",\"a4\",\"a4\"] }, \n",
"{ name: \"<span title=\\\"displ: Double\\\">displ</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1.8</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1.8</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2.0</span></span>\"] }, \n",
"{ name: \"<span title=\\\"year: Int\\\">year</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1999</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1999</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2008</span></span>\"] }, \n",
"{ name: \"<span title=\\\"cyl: Int\\\">cyl</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\"] }, \n",
"{ name: \"<span title=\\\"trans: String\\\">trans</span>\", children: [], rightAlign: false, values: [\"auto(l5)\",\"manual(m5)\",\"manual(m6)\"] }, \n",
"{ name: \"<span title=\\\"drv: String\\\">drv</span>\", children: [], rightAlign: false, values: [\"f\",\"f\",\"f\"] }, \n",
"{ name: \"<span title=\\\"cty: Int\\\">cty</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">18</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">21</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">20</span></span>\"] }, \n",
"{ name: \"<span title=\\\"hwy: Int\\\">hwy</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">29</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">29</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">31</span></span>\"] }, \n",
"{ name: \"<span title=\\\"fl: String\\\">fl</span>\", children: [], rightAlign: false, values: [\"p\",\"p\",\"p\"] }, \n",
"{ name: \"<span title=\\\"class: String\\\">class</span>\", children: [], rightAlign: false, values: [\"compact\",\"compact\",\"compact\"] }, \n",
"], id: -1426063360, rootId: -1426063360, totalRows: 3 } ) });\n",
"/*-->*/\n",
"\n",
"call_DataFrame(function() { DataFrame.renderTable(-1426063360) });\n",
"\n",
"\n",
" </script>\n",
" </html>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"val df = DataFrame.readCSV(\"https://raw.githubusercontent.com/JetBrains/lets-plot-kotlin/master/docs/examples/data/mpg.csv\")\n",
"df.head(3)\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "accepted-afternoon",
"metadata": {},
"outputs": [
{
"data": {
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" <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
" (function() {\n",
" var plotSpec={\n",
"\"ggtitle\":{\n",
"\"text\":\"Fuel efficiency\\nfor most popular models of car\",\n",
"\"subtitle\":\"Period 1999-2008\"\n",
"},\n",
"\"mapping\":{\n",
"\"x\":\"displ\",\n",
"\"y\":\"hwy\"\n",
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"\"data\":{\n",
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"\"hwy\":[29.0,29.0,31.0,30.0,26.0,26.0,27.0,26.0,25.0,28.0,27.0,25.0,25.0,25.0,25.0,24.0,25.0,23.0,20.0,15.0,20.0,17.0,17.0,26.0,23.0,26.0,25.0,24.0,19.0,14.0,15.0,17.0,27.0,30.0,26.0,29.0,26.0,24.0,24.0,22.0,22.0,24.0,24.0,17.0,22.0,21.0,23.0,23.0,19.0,18.0,17.0,17.0,19.0,19.0,12.0,17.0,15.0,17.0,17.0,12.0,17.0,16.0,18.0,15.0,16.0,12.0,17.0,17.0,16.0,12.0,15.0,16.0,17.0,15.0,17.0,17.0,18.0,17.0,19.0,17.0,19.0,19.0,17.0,17.0,17.0,16.0,16.0,17.0,15.0,17.0,26.0,25.0,26.0,24.0,21.0,22.0,23.0,22.0,20.0,33.0,32.0,32.0,29.0,32.0,34.0,36.0,36.0,29.0,26.0,27.0,30.0,31.0,26.0,26.0,28.0,26.0,29.0,28.0,27.0,24.0,24.0,24.0,22.0,19.0,20.0,17.0,12.0,19.0,18.0,14.0,15.0,18.0,18.0,15.0,17.0,16.0,18.0,17.0,19.0,19.0,17.0,29.0,27.0,31.0,32.0,27.0,26.0,26.0,25.0,25.0,17.0,17.0,20.0,18.0,26.0,26.0,27.0,28.0,25.0,25.0,24.0,27.0,25.0,26.0,23.0,26.0,26.0,26.0,26.0,25.0,27.0,25.0,27.0,20.0,20.0,19.0,17.0,20.0,17.0,29.0,27.0,31.0,31.0,26.0,26.0,28.0,27.0,29.0,31.0,31.0,26.0,26.0,27.0,30.0,33.0,35.0,37.0,35.0,15.0,18.0,20.0,20.0,22.0,17.0,19.0,18.0,20.0,29.0,26.0,29.0,29.0,24.0,44.0,29.0,26.0,29.0,29.0,29.0,29.0,23.0,24.0,44.0,41.0,29.0,26.0,28.0,29.0,29.0,29.0,28.0,29.0,26.0,26.0,26.0]\n",
"},\n",
"\"kind\":\"plot\",\n",
"\"scales\":[{\n",
"\"aesthetic\":\"x\",\n",
"\"name\":\"Engine displacement\\n(litres)\"\n",
"},{\n",
"\"aesthetic\":\"y\",\n",
"\"name\":\"Highway\\nmiles per gallon\"\n",
"}],\n",
"\"layers\":[{\n",
"\"mapping\":{\n",
"},\n",
"\"stat\":\"identity\",\n",
"\"position\":\"identity\",\n",
"\"geom\":\"point\",\n",
"\"data\":{\n",
"}\n",
"}],\n",
"\"caption\":{\n",
"\"text\":\"MPG Dataset\"\n",
"},\n",
"\"theme\":{\n",
"\"name\":\"classic\",\n",
"\"plot_background\":{\n",
"\"size\":1.0,\n",
"\"blank\":false\n",
"}\n",
"}\n",
"};\n",
" var plotContainer = document.getElementById(\"jQBxFC\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"val p = letsPlot(df.toMap()) { x = \"displ\"; y = \"hwy\" } + geomPoint() +\n",
" labs(\n",
" title = \"Fuel efficiency\\nfor most popular models of car\",\n",
" subtitle = \"Period 1999-2008\",\n",
" caption = \"MPG Dataset\",\n",
" x = \"Engine displacement\\n(litres)\", \n",
" y = \"Highway\\nmiles per gallon\"\n",
" ) + themeClassic() + theme(plotBackground = elementRect(size=1))\n",
"p"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "posted-newsletter",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" <div id=\"FA1eXe\"></div>\n",
" <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
" (function() {\n",
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"\"ggtitle\":{\n",
"\"text\":\"Fuel efficiency\\nfor most popular models of car\",\n",
"\"subtitle\":\"Period 1999-2008\"\n",
"},\n",
"\"mapping\":{\n",
"\"x\":\"displ\",\n",
"\"y\":\"hwy\"\n",
"},\n",
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"\"hwy\":[29.0,29.0,31.0,30.0,26.0,26.0,27.0,26.0,25.0,28.0,27.0,25.0,25.0,25.0,25.0,24.0,25.0,23.0,20.0,15.0,20.0,17.0,17.0,26.0,23.0,26.0,25.0,24.0,19.0,14.0,15.0,17.0,27.0,30.0,26.0,29.0,26.0,24.0,24.0,22.0,22.0,24.0,24.0,17.0,22.0,21.0,23.0,23.0,19.0,18.0,17.0,17.0,19.0,19.0,12.0,17.0,15.0,17.0,17.0,12.0,17.0,16.0,18.0,15.0,16.0,12.0,17.0,17.0,16.0,12.0,15.0,16.0,17.0,15.0,17.0,17.0,18.0,17.0,19.0,17.0,19.0,19.0,17.0,17.0,17.0,16.0,16.0,17.0,15.0,17.0,26.0,25.0,26.0,24.0,21.0,22.0,23.0,22.0,20.0,33.0,32.0,32.0,29.0,32.0,34.0,36.0,36.0,29.0,26.0,27.0,30.0,31.0,26.0,26.0,28.0,26.0,29.0,28.0,27.0,24.0,24.0,24.0,22.0,19.0,20.0,17.0,12.0,19.0,18.0,14.0,15.0,18.0,18.0,15.0,17.0,16.0,18.0,17.0,19.0,19.0,17.0,29.0,27.0,31.0,32.0,27.0,26.0,26.0,25.0,25.0,17.0,17.0,20.0,18.0,26.0,26.0,27.0,28.0,25.0,25.0,24.0,27.0,25.0,26.0,23.0,26.0,26.0,26.0,26.0,25.0,27.0,25.0,27.0,20.0,20.0,19.0,17.0,20.0,17.0,29.0,27.0,31.0,31.0,26.0,26.0,28.0,27.0,29.0,31.0,31.0,26.0,26.0,27.0,30.0,33.0,35.0,37.0,35.0,15.0,18.0,20.0,20.0,22.0,17.0,19.0,18.0,20.0,29.0,26.0,29.0,29.0,24.0,44.0,29.0,26.0,29.0,29.0,29.0,29.0,23.0,24.0,44.0,41.0,29.0,26.0,28.0,29.0,29.0,29.0,28.0,29.0,26.0,26.0,26.0]\n",
"},\n",
"\"kind\":\"plot\",\n",
"\"scales\":[{\n",
"\"aesthetic\":\"x\",\n",
"\"name\":\"Engine displacement\\n(litres)\"\n",
"},{\n",
"\"aesthetic\":\"y\",\n",
"\"name\":\"Highway\\nmiles per gallon\"\n",
"}],\n",
"\"layers\":[{\n",
"\"mapping\":{\n",
"},\n",
"\"stat\":\"identity\",\n",
"\"position\":\"identity\",\n",
"\"geom\":\"point\",\n",
"\"data\":{\n",
"}\n",
"}],\n",
"\"caption\":{\n",
"\"text\":\"MPG Dataset\"\n",
"},\n",
"\"theme\":{\n",
"\"name\":\"classic\",\n",
"\"plot_background\":{\n",
"\"size\":1.0,\n",
"\"blank\":false\n",
"},\n",
"\"axis_title_y\":{\n",
"\"margin\":{\n",
"\"r\":10.0,\n",
"\"l\":15.0\n",
"},\n",
"\"blank\":false\n",
"},\n",
"\"plot_title\":{\n",
"\"margin\":{\n",
"\"t\":15.0\n",
"},\n",
"\"blank\":false\n",
"},\n",
"\"plot_caption\":{\n",
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"\"b\":15.0\n",
"},\n",
"\"blank\":false\n",
"},\n",
"\"axis_title_x\":{\n",
"\"margin\":{\n",
"\"t\":10.0\n",
"},\n",
"\"blank\":false\n",
"},\n",
"\"plot_subtitle\":{\n",
"\"margin\":{\n",
"\"b\":10.0\n",
"},\n",
"\"blank\":false\n",
"}\n",
"}\n",
"};\n",
" var plotContainer = document.getElementById(\"FA1eXe\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"// Change margins around plot title, subtitle, caption and axis titles\n",
"\n",
"p + theme(plotTitle = elementText(margin = margin(t=15)), \n",
" plotSubtitle = elementText(margin = margin(b=10)),\n",
" plotCaption = elementText(margin = margin(b=15)),\n",
" axisTitleX = elementText(margin = margin(t=10)), \n",
" axisTitleY = elementText(margin = margin(r=10, l=15)))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "median-badge",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" <div id=\"sqxyn8\"></div>\n",
" <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
" (function() {\n",
" var plotSpec={\n",
"\"ggtitle\":{\n",
"\"text\":\"Fuel efficiency\\nfor most popular models of car\",\n",
"\"subtitle\":\"Period 1999-2008\"\n",
"},\n",
"\"mapping\":{\n",
"\"x\":\"displ\",\n",
"\"y\":\"hwy\"\n",
"},\n",
"\"data\":{\n",
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"\"hwy\":[29.0,29.0,31.0,30.0,26.0,26.0,27.0,26.0,25.0,28.0,27.0,25.0,25.0,25.0,25.0,24.0,25.0,23.0,20.0,15.0,20.0,17.0,17.0,26.0,23.0,26.0,25.0,24.0,19.0,14.0,15.0,17.0,27.0,30.0,26.0,29.0,26.0,24.0,24.0,22.0,22.0,24.0,24.0,17.0,22.0,21.0,23.0,23.0,19.0,18.0,17.0,17.0,19.0,19.0,12.0,17.0,15.0,17.0,17.0,12.0,17.0,16.0,18.0,15.0,16.0,12.0,17.0,17.0,16.0,12.0,15.0,16.0,17.0,15.0,17.0,17.0,18.0,17.0,19.0,17.0,19.0,19.0,17.0,17.0,17.0,16.0,16.0,17.0,15.0,17.0,26.0,25.0,26.0,24.0,21.0,22.0,23.0,22.0,20.0,33.0,32.0,32.0,29.0,32.0,34.0,36.0,36.0,29.0,26.0,27.0,30.0,31.0,26.0,26.0,28.0,26.0,29.0,28.0,27.0,24.0,24.0,24.0,22.0,19.0,20.0,17.0,12.0,19.0,18.0,14.0,15.0,18.0,18.0,15.0,17.0,16.0,18.0,17.0,19.0,19.0,17.0,29.0,27.0,31.0,32.0,27.0,26.0,26.0,25.0,25.0,17.0,17.0,20.0,18.0,26.0,26.0,27.0,28.0,25.0,25.0,24.0,27.0,25.0,26.0,23.0,26.0,26.0,26.0,26.0,25.0,27.0,25.0,27.0,20.0,20.0,19.0,17.0,20.0,17.0,29.0,27.0,31.0,31.0,26.0,26.0,28.0,27.0,29.0,31.0,31.0,26.0,26.0,27.0,30.0,33.0,35.0,37.0,35.0,15.0,18.0,20.0,20.0,22.0,17.0,19.0,18.0,20.0,29.0,26.0,29.0,29.0,24.0,44.0,29.0,26.0,29.0,29.0,29.0,29.0,23.0,24.0,44.0,41.0,29.0,26.0,28.0,29.0,29.0,29.0,28.0,29.0,26.0,26.0,26.0]\n",
"},\n",
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"\"scales\":[{\n",
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"\"name\":\"Engine displacement\\n(litres)\"\n",
"},{\n",
"\"aesthetic\":\"y\",\n",
"\"name\":\"Highway\\nmiles per gallon\"\n",
"}],\n",
"\"layers\":[{\n",
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"},\n",
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"\"position\":\"identity\",\n",
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"}],\n",
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"\"text\":\"MPG Dataset\"\n",
"},\n",
"\"theme\":{\n",
"\"name\":\"classic\",\n",
"\"plot_background\":{\n",
"\"size\":1.0,\n",
"\"blank\":false\n",
"},\n",
"\"axis_text_y\":{\n",
"\"margin\":{\n",
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"\"l\":15.0\n",
"},\n",
"\"blank\":false\n",
"},\n",
"\"axis_text_x\":{\n",
"\"margin\":{\n",
"\"t\":10.0,\n",
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"},\n",
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"}\n",
"}\n",
"};\n",
" var plotContainer = document.getElementById(\"sqxyn8\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"// Change margins around axis tick labels\n",
"\n",
"p + theme(axisTextX = elementText(margin = margin(t=10, b=15)), \n",
" axisTextY = elementText(margin = margin(r=10, l=15)))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "cutting-justice",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" <div id=\"GZ3zwe\"></div>\n",
" <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
" (function() {\n",
" var plotSpec={\n",
"\"mapping\":{\n",
"\"x\":\"class\",\n",
"\"y\":\"hwy\"\n",
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"\"data\":{\n",
"},\n",
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"},{\n",
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"},\n",
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"}]\n",
"};\n",
" var plotContainer = document.getElementById(\"GZ3zwe\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"// axis labels at different levels\n",
"\n",
"val p2 = letsPlot(df.toMap()) { x = \"class\"; y = \"hwy\" } + geomBoxplot()\n",
"p2"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "lightweight-detroit",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"\"margin\":{\n",
"\"t\":10.0,\n",
"\"b\":10.0\n",
"},\n",
"\"blank\":false\n",
"}\n",
"}\n",
"};\n",
" var plotContainer = document.getElementById(\"4GLhJX\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 + theme(axisTextX = elementText(margin = margin(t=10, b=10)))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "alleged-effects",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" <div id=\"XewNoV\"></div>\n",
" <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
" (function() {\n",
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"\"x\":\"class\",\n",
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"},\n",
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"\"ggsize\":{\n",
"\"width\":550.0,\n",
"\"height\":400.0\n",
"},\n",
"\"kind\":\"plot\",\n",
"\"scales\":[],\n",
"\"layers\":[{\n",
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"\"..ymin..\":[23.0,23.0,14.0,21.0,15.0,23.0,20.0],\n",
"\"class\":[\"compact\",\"midsize\",\"suv\",\"minivan\",\"pickup\",\"2seater\",\"subcompact\"]\n",
"}\n",
"},{\n",
"\"mapping\":{\n",
"},\n",
"\"stat\":\"boxplot_outlier\",\n",
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"\"position\":\"dodge\",\n",
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"}\n",
"}]\n",
"};\n",
" var plotContainer = document.getElementById(\"XewNoV\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"// with rotation\n",
"\n",
"val p3 = p2 + ggsize(550, 400)\n",
"p3"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "scheduled-identity",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" <div id=\"sX03VP\"></div>\n",
" <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
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"}\n",
"}],\n",
"\"theme\":{\n",
"\"axis_text_x\":{\n",
"\"margin\":{\n",
"\"t\":10.0\n",
"},\n",
"\"blank\":false\n",
"}\n",
"}\n",
"};\n",
" var plotContainer = document.getElementById(\"sX03VP\");\n",
" window.letsPlotCall(function() {{\n",
" LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
" }});\n",
" })(); \n",
" </script>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p3 + theme(axisTextX = elementText(margin = margin(t=10)))"
]
}
],
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