{
"cells": [
{
"cell_type": "markdown",
"id": "599ab589-6b5d-4429-9a6b-8ba816a7b227",
"metadata": {},
"source": [
"# Multi-line Labels in Facets\n",
"\n",
"\n",
"The 'newline' character (`\\n`) now works as a 'line break' in the facet titles. \n",
"Automatic line breaking is performed according to the text length limit specified with parameters `labWidth` in `facetWrap()` and `xLabWidth`/`yLabWidth` in `facetGrid()`.\n",
"\n",
"The margins around the facet titles are controlled by the `margin` parameter in `elementText()`. \n",
"Horizontal and vertical justifications - using `hjust` and `vjust` parameter in `elementText()`."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "c78e2aa3-1187-4203-b544-4e20989fcddb",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%useLatestDescriptors\n",
"%use lets-plot\n",
"%use dataframe"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "47d3905a-13b3-4c17-aa7a-1eaf46e57d7f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Lets-Plot Kotlin API v.4.7.1. Frontend: Notebook with dynamically loaded JS. Lets-Plot JS v.4.3.1."
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LetsPlot.getInfo()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "83b526d2-33ab-445f-813d-8e9cc94edb03",
"metadata": {},
"outputs": [],
"source": [
"val df = dataFrameOf(\"animal_type\", \"animal\", \"weight\", \"diet\")(\n",
" \"pet\", \"cat\", 5, \"carnivore\",\n",
" \"pet\", \"dog\", 10, \"carnivore\",\n",
" \"pet\", \"rabbit\", 2, \"herbivore\",\n",
" \"pet\", \"hamster\", 1, \"herbivore\",\n",
"\n",
" \"farm animal\", \"cow\", 500, \"herbivore\",\n",
" \"farm animal\", \"pig\", 100, \"carnivore\",\n",
" \"farm animal\", \"horse\", 700, \"herbivore\",\n",
")"
]
},
{
"cell_type": "markdown",
"id": "e0f1f949-c7ce-4e5f-af6e-ff49edbd0200",
"metadata": {},
"source": [
"### Facet Labels"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f50bf5aa-601b-4aba-b2ad-ef26104cbc0f",
"metadata": {},
"outputs": [],
"source": [
"val p = letsPlot(df.toMap()) { x = \"animal\"; y = \"weight\" } +\n",
" geomBar(stat = Stat.identity) +\n",
" themeBW() +\n",
" theme(panelGridMinor = elementBlank())"
]
},
{
"cell_type": "markdown",
"id": "3a94fa6c-2a6e-4e2c-9f6f-ebfe69f1798b",
"metadata": {},
"source": [
"#### Default"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c30e5c0d-9e18-4d33-ae01-79c3eeb2c9fe",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + facetWrap(facets = \"animal_type\", ncol = 2, scales = \"free\")"
]
},
{
"cell_type": "markdown",
"id": "2eb94675-7816-4856-8ac1-4d085ae24a81",
"metadata": {},
"source": [
"#### Wrap Labels using `labWidth`-parameters"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ae99612c-c1b0-43ac-8e53-da66d29184a4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + facetWrap(facets = \"animal_type\", ncol = 2, scales = \"free\", labWidth = 6)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "741e10bd-bd04-4ace-a409-04ba2c3a59bf",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + facetGrid(x = \"animal_type\", y = \"diet\", scales = \"free\", xLabWidth = 6)"
]
},
{
"cell_type": "markdown",
"id": "bbb9d350-f3c3-4d18-9827-f93657b60f60",
"metadata": {},
"source": [
"#### Line Breaks Using `\\n` in Facet Values"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "cb7b453d-7da4-4706-86f7-d952e9c38607",
"metadata": {},
"outputs": [],
"source": [
"val df2 = df.update { animal_type }.with { it.replace(' ', '\\n') }\n",
"\n",
"val p2 = letsPlot(df2.toMap()) { x = \"animal\"; y = \"weight\" } +\n",
" geomBar(stat = Stat.identity) +\n",
" themeBW() +\n",
" theme(panelGridMinor = elementBlank())"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "c6db2315-cc50-4e69-93aa-90f09fc4da65",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 + facetGrid(x = \"animal_type\", y = \"diet\", scales = \"free\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "dbeea0ea-3d60-49a6-a0de-2d3ace1051d7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 + facetWrap(facets = listOf(\"animal_type\", \"diet\"), ncol = 4, scales = \"free\")"
]
},
{
"cell_type": "markdown",
"id": "6c8bfdd8-cc93-4831-8d64-3eecc13c794b",
"metadata": {},
"source": [
"### Text Justifications"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "4d359ce4-1901-478a-bdd9-379b40984027",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 + facetWrap(facets = listOf(\"animal_type\", \"diet\"), ncol = 4, scales = \"free\") +\n",
" theme(stripText = elementText(hjust = 1, vjust = 1))"
]
},
{
"cell_type": "markdown",
"id": "7db2d0bc-bf84-4c7e-aaba-9a6c73ee9db6",
"metadata": {},
"source": [
"### Margins Around the Text Element"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "614f608a-aba4-4ecc-b961-81e715330ddf",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 + facetGrid(x = \"animal_type\", y = \"diet\", scales = \"free\") +\n",
" theme(stripText = elementText(margin = listOf(10, 30), hjust = 0, vjust = 1))"
]
}
],
"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",
"nbconvert_exporter": "",
"pygments_lexer": "kotlin",
"version": "1.9.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}