{
"cells": [
{
"cell_type": "markdown",
"id": "7652c120-54fa-4c12-bbb2-8dd7a8aeb9b9",
"metadata": {},
"source": [
"# Band Geometry"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "7b8e17a3-5669-4609-b8eb-22fe78fc96fc",
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime\n",
"\n",
"import pandas as pd\n",
"\n",
"from lets_plot import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e5a21782-05b6-4072-83dd-142980bc0916",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4b511a3d-cc20-45c9-9aa9-8feb555d54ca",
"metadata": {},
"outputs": [],
"source": [
"def get_dt(year, month=1, day=1):\n",
" return int(round(1_000 * datetime(year, month, day).timestamp()))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "672f2175-e227-4950-b444-946211dd557e",
"metadata": {},
"outputs": [],
"source": [
"presidential_df = pd.read_csv(\"data/presidential.csv\", parse_dates=[\"start\", \"end\"])\n",
"economics_df = pd.read_csv(\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/economics.csv\", parse_dates=[\"date\"])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "50a763a1-3244-4e3e-9743-dc9a0674914d",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"breaks = [2.5, 5, 10]\n",
"\n",
"ggplot() + \\\n",
" geom_band(aes(xmin=\"start\", xmax=\"end\", fill=\"party\"), data=presidential_df, \\\n",
" size=0, alpha=.4) + \\\n",
" geom_label(aes(\"start\", label=\"name\", color=\"party\"), \n",
" data=presidential_df, \n",
" y=4000, alpha=0.6, \n",
" angle=90,\n",
" vjust=1, show_legend=False) + \\\n",
" geom_line(aes(\"date\", \"unemploy\"), data=economics_df) + \\\n",
" scale_y_continuous(\"Unemployment (x\\(10^3\\))\", trans='log10', \\\n",
" breaks=[b*10**3 for b in breaks], labels=[str(b) for b in breaks]) + \\\n",
" scale_fill_discrete(name=\"\") + \\\n",
" coord_cartesian(xlim=[get_dt(1966), get_dt(2016)]) + \\\n",
" xlab(\"Year\") + \\\n",
" guides(fill=guide_legend(override_aes={'alpha': 0.4, 'color': 'paper'})) + \\\n",
" ggsize(1000, 400) + \\\n",
" theme(legend_position='top')"
]
}
],
"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": "3.8.19"
}
},
"nbformat": 4,
"nbformat_minor": 5
}