{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This page is available as an executable or viewable Jupyter Notebook:\n",
"
\n",
"\n",
" ![](\"https://mybinder.org/badge_logo.svg\")
\n",
"\n",
"\n",
" ![](\"https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.png\"\n",)
\n",
"\n",
"
\n",
"
"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%useLatestDescriptors\n",
"%use lets-plot"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"// Create a random density plot and save it in a variable \"p\".\n",
"val rand = java.util.Random(123)\n",
"val n = 400\n",
"val data = mapOf (\n",
" \"rating\" to List(n/2) { rand.nextGaussian() } + List(n/2) { rand.nextGaussian() * 1.5 + 1.5 },\n",
" \"cond\" to List(n/2) { \"A\" } + List(n/2) { \"B\" }\n",
")\n",
"\n",
"var p = lets_plot(data) +\n",
" geom_density { x = \"rating\"; color = \"cond\" } + ggsize(500, 250) "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import java.io.File"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Export PNG to file"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"/Users/Igor/Work_misc/jupyter/lets-plot-kotlin/examples/jupyter-notebooks/lets-plot-images/density.png"
]
},
"execution_count": 4,
"metadata": {
"new_classpath": []
},
"output_type": "execute_result"
}
],
"source": [
"ggsave(p, \"density.png\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"![](\"lets-plot-images/density.png\")
"
]
},
"execution_count": 5,
"metadata": {
"new_classpath": []
},
"output_type": "execute_result"
}
],
"source": [
"HTML(\"![](\\\"lets-plot-images/density.png\\\")
\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Export SVG to file"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"/Users/Igor/Work_misc/jupyter/lets-plot-kotlin/examples/jupyter-notebooks/lets-plot-images/density.svg"
]
},
"execution_count": 6,
"metadata": {
"new_classpath": []
},
"output_type": "execute_result"
}
],
"source": [
"ggsave(p, \"density.svg\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
""
]
},
"execution_count": 7,
"metadata": {
"new_classpath": []
},
"output_type": "execute_result"
}
],
"source": [
"HTML(File(\"lets-plot-images/density.svg\").readText())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Export HTML to file"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"/Users/Igor/Work_misc/jupyter/lets-plot-kotlin/examples/jupyter-notebooks/lets-plot-images/density.html"
]
},
"execution_count": 8,
"metadata": {
"new_classpath": []
},
"output_type": "execute_result"
}
],
"source": [
"ggsave(p, \"density.html\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" "
]
},
"execution_count": 9,
"metadata": {
"new_classpath": []
},
"output_type": "execute_result"
}
],
"source": [
"HTML(File(\"lets-plot-images/density.html\").readText())"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Kotlin",
"language": "kotlin",
"name": "kotlin"
},
"language_info": {
"codemirror_mode": "text/x-kotlin",
"file_extension": ".kt",
"mimetype": "text/x-kotlin",
"name": "kotlin",
"pygments_lexer": "kotlin",
"version": "1.5.0-dev-1206"
}
},
"nbformat": 4,
"nbformat_minor": 4
}