{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "saving-matrix",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"\n",
"from lets_plot import *\n",
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "rough-following",
"metadata": {},
"outputs": [],
"source": [
"mpg = pd.read_csv(\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "social-andrews",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p = ggplot(mpg, aes('cty', 'hwy', color='drv')) + geom_point() + labs(color='Drive type') \n",
"p"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "dynamic-delivery",
"metadata": {},
"outputs": [],
"source": [
"hjust_left = element_text(hjust=0.0)\n",
"hjust_middle = element_text(hjust=0.5)\n",
"hjust_right = element_text(hjust=1.0)\n",
"\n",
"h = 420"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "inappropriate-accountability",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Horizontal justification for plot title, subtitle, caption, legend and axis titles\n",
"\n",
"def with_hjust(hjust):\n",
" return theme(title=hjust, axis_title=hjust, plot_caption=hjust, legend_title=hjust)\n",
"\n",
"p2 = p + labs(caption='The plot caption')\n",
"\n",
"bunch = GGBunch()\n",
"bunch.add_plot(p2 + with_hjust(hjust_left) + ggtitle(\"All titles with hjust = 0.0\"), 0, 0)\n",
"bunch.add_plot(p2 + with_hjust(hjust_middle) + ggtitle(\"All titles with hjust = 0.5\"), 0, h)\n",
"bunch.add_plot(p2 + with_hjust(hjust_right) + ggtitle(\"All titles with hjust = 1.0\"), 0, 2*h)\n",
"bunch.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "defensive-rover",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Vertical justification for legend title\n",
"\n",
"vjust_bottom = element_text(vjust=0.0)\n",
"vjust_center = element_text(vjust=0.5)\n",
"vjust_top = element_text(vjust=1.0)\n",
"\n",
"p3 = p + theme(legend_position='bottom') + scale_color_discrete(guide=guide_legend(ncol=1))\n",
"\n",
"def with_vjust(vjust):\n",
" return theme(legend_title=vjust)\n",
"\n",
"bunch = GGBunch()\n",
"bunch.add_plot(p3 + with_vjust(vjust_bottom) + ggtitle(\"Legend title with vjust = 0.0\"), 0, 0)\n",
"bunch.add_plot(p3 + with_vjust(vjust_center) + ggtitle(\"Legend title with vjust = 0.5\"), 0, h)\n",
"bunch.add_plot(p3 + with_vjust(vjust_top) + ggtitle(\"Legend title with vjust = 1.0\"), 0, 2*h)\n",
"bunch.show()"
]
}
],
"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": "3.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}