{
"cells": [
{
"cell_type": "markdown",
"id": "2bb8845e-5844-4cfa-b008-6a6b482391d8",
"metadata": {},
"source": [
"# LaTeX Support\n",
"\n",
"Note that LaTeX formulas are not fully supported when exporting to PNG/PDF."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "eee2a2ae-760f-4a14-a2a1-722be25d5020",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"from lets_plot import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "cfc33c00-bca9-4b63-9b4a-e2712c7487c1",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"LetsPlot.setup_html()"
]
},
{
"cell_type": "markdown",
"id": "4ca63004-e567-44d1-9a10-62505a37f51d",
"metadata": {},
"source": [
"## Power Degree"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "60b010a9-860c-4ec8-9b51-b704978f3666",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data1 = {'x': list(range(-10, 11))}\n",
"ggplot() + \\\n",
" geom_function(aes(x='x'), data=data1, fun=lambda x: x**3 - 100 * x) + \\\n",
" ggtitle(\"Graph of the \\( y = x^3 - 100 x \\)\") + \\\n",
" theme(text=element_text(family=\"Times New Roman\"), \\\n",
" plot_title=element_text(size=20, face='bold'))"
]
},
{
"cell_type": "markdown",
"id": "a9c7e104-640a-4fa0-b922-a1c22747151a",
"metadata": {},
"source": [
"## Subscript"
]
},
{
"cell_type": "markdown",
"id": "ab9ead5c-deec-4794-9ef6-01e6454e75f9",
"metadata": {},
"source": [
"Dataset: [owid-co2-data.csv](https://github.com/owid/co2-data/blob/master/owid-co2-data.csv) © [Our World in Data](https://ourworldindata.org) ([Licensed under CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "de9c75ad-44f4-458c-a3e8-f64be58f185b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_df = pd.read_csv(\"https://raw.githubusercontent.com/owid/co2-data/refs/heads/master/owid-co2-data.csv\")\n",
"df = raw_df[raw_df[\"country\"].isin([\"World\", \"United States\", \"United Kingdom\", \"China\", \"India\"])]\n",
"\n",
"ggplot(df, aes(\"year\", \"co2_per_capita\", color=\"country\")) + \\\n",
" geom_line(tooltips=layer_tooltips().title(\"@year\\nin tonnes per person\").format(\"year\", \"d\")\n",
" .line(\"@country: @co2_per_capita\").format(\"@co2_per_capita\", \"{.1f} t\")) + \\\n",
" scale_x_continuous(name=\"\", format=\"d\") + \\\n",
" scale_y_continuous(name=\"\", format=\"{d} t\", expand=[0, 0]) + \\\n",
" ggtitle(\"\\( CO_2 \\) emissions\", \"[tonnes per capita]\") + \\\n",
" ggsize(1000, 400) + \\\n",
" theme(text=element_text(family=\"Playfair Display\"), \\\n",
" plot_title=element_text(size=20, face='bold'),\n",
" plot_subtitle=element_text(size=16))"
]
},
{
"cell_type": "markdown",
"id": "1d8a27a3-63f9-43bf-9e5c-092235068bd7",
"metadata": {},
"source": [
"## Greek Letters and Other Special Symbols"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c0cd2656-d5ec-41f2-b78c-be1ed3f53069",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + \\\n",
" geom_text(x=0, label=r\"\\( e^{i \\cdot \\pi} = -1 \\)\", \\\n",
" size=70, family=\"Computer Modern Math\", fontface='italic') + \\\n",
" theme_void()"
]
},
{
"cell_type": "markdown",
"id": "7be88175-d135-48f7-92f6-14a4e08a5df9",
"metadata": {},
"source": [
"## Place Your Formulas Anywhere!"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "9d234197-b825-44d9-aa2e-df4159b0fd2f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data2 = {\n",
" \"x\": [r\"\\( \\Omega_{\\rho + 1} \\)\"],\n",
" r\"\\(\\delta\\)\": [1],\n",
" \"f\": [r\"\\( A \\neq B^2 \\)\"],\n",
"}\n",
"\n",
"ggplot(data2) + \\\n",
" geom_bar(aes(\"x\", r\"\\(\\delta\\)\", fill=\"x\"), stat='identity', \\\n",
" labels=layer_labels().line(\"@f\"), \\\n",
" tooltips=layer_tooltips().line(\"@f\")) + \\\n",
" scale_fill_manual([\"#6a3d9a\"], name=r\"\\(\\Sigma\\)\") + \\\n",
" xlab(r\"\\(\\sigma\\)\") + \\\n",
" theme(label_text=element_text(size=20))"
]
}
],
"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": "3.9.20"
}
},
"nbformat": 4,
"nbformat_minor": 5
}