{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "regulated-engineering",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from lets_plot import *\n",
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "right-pathology",
"metadata": {},
"outputs": [],
"source": [
"w, h = 600, 400"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "parliamentary-landscape",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# default theme\n",
"p = (\n",
" ggplot({'x': list(range(5)), 'y': list(range(5))}, aes('x', 'y')) +\n",
" geom_point(aes(size='y', fill=\"y\"),tooltips=layer_tooltips().title(\"TITLE\").line('label|value')) +\n",
" labs(title='The plot title', \n",
" subtitle=\"The plot subtitle\",\n",
" caption=\"The plot caption\",\n",
" x='X axis label', \n",
" y='Y axis label', \n",
" fill='Fill legend title',\n",
" size='Size legend title'\n",
" )\n",
")\n",
"p"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "coupled-extension",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# theme functions\n",
"bunch = GGBunch()\n",
"bunch.add_plot(p + ggtitle(\"theme_grey()\") + theme_grey(), 0, 0, w, h)\n",
"bunch.add_plot(p + ggtitle(\"theme_none()\") + theme_none(), w, 0, w, h)\n",
"bunch.show()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "applicable-seating",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"e_line = element_line(color='light_green', size=3)\n",
"e_rect = element_rect(color='#2c7fb8', fill='#edf8b1', size=2)\n",
"e_text = element_text(color='#f1a354', face='italic')\n",
"\n",
"# tooltips\n",
"\n",
"bunch = GGBunch()\n",
"\n",
"bunch.add_plot(p + theme(axis_tooltip=e_rect) +\n",
" ggtitle(\"axis_tooltip = e_rect\", subtitle=\"axis tooltip -> fill + text/border color + stroke width\"),\n",
" 0, 0)\n",
"\n",
"bunch.add_plot(p + theme(axis_tooltip=e_line) +\n",
" ggtitle(\"axis_tooltip = e_line\", subtitle=\"axis tooltip -> text/border color + stroke width\"),\n",
" w, 0)\n",
"\n",
"bunch.add_plot(p + theme(axis_tooltip=e_text) +\n",
" ggtitle(\"axis_tooltip = e_text\", subtitle=\"axis tooltip -> text/border color\"),\n",
" 0, h*1.1)\n",
"\n",
"bunch.add_plot(p + theme(axis_tooltip_text=e_text) +\n",
" ggtitle(\"axis_tooltip_text = e_text\", subtitle=\"axis tooltip -> text color + font face\"),\n",
" w, h*1.1)\n",
"\n",
"bunch.add_plot(p + theme(tooltip_text=e_text) +\n",
" ggtitle(\"tooltip_text = e_text\", subtitle=\"all tooltip -> text color + font face\"),\n",
" 0, h*2.2)\n",
"\n",
"bunch.add_plot(p + theme(tooltip=e_rect, tooltip_text=e_text) +\n",
" ggtitle(\"+ tooltip=e_rect\", subtitle=\"-> tooltip rect\"),\n",
" w, h*2.2)\n",
"\n",
"bunch.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "fossil-monday",
"metadata": {},
"outputs": [],
"source": [
"# Theme options \n",
"theme_opts = theme(\n",
" plot_title=element_text('red', face='bold_italic'),\n",
" plot_subtitle=element_text('pink', face='normal'),\n",
" plot_caption=element_text('gray', face='italic'),\n",
" \n",
" legend_title=element_text('#cc8f00'),\n",
" legend_text=element_text('orange', face='italic'),\n",
" \n",
" axis_title_x=element_text('dark_green'),\n",
" axis_text_x=element_text('#00b300'),\n",
" axis_tooltip_text_x=element_text(color='light_green'),\n",
"\n",
" axis_title_y=element_text('dark_blue'),\n",
" axis_text_y=element_text(color='#9e9eff'),\n",
" axis_tooltip_text_y=element_text(color='light_blue'),\n",
"\n",
" tooltip=element_rect(color='#54278f', fill='#fcfbfd'),\n",
" tooltip_text=element_text(color='#54278f', face='italic') \n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "exempt-diagnosis",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 = p + theme_opts\n",
"p2"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "norman-bunch",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p2 + coord_flip() "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "packed-trainer",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 9,
"id": "express-highland",
"metadata": {},
"outputs": [],
"source": [
"data = dict(\n",
" supp = ['OJ', 'OJ', 'OJ', 'VC', 'VC', 'VC'],\n",
" dose = [0.5, 1.0, 2.0, 0.5, 1.0, 2.0],\n",
" length = [13.23, 22.70, 26.06, 7.98, 16.77, 26.14],\n",
" len_min = [11.83, 21.2, 24.50, 4.24, 15.26, 23.35],\n",
" len_max = [15.63, 24.9, 27.11, 10.72, 19.28, 28.93]\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "varying-biology",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# bars\n",
"bar_labels=labs(\n",
" title=\"Tooth length per dose\",\n",
" subtitle=\"geom_bar\", \n",
" caption=\"The ToothGrowth dataset\",\n",
" x = \"Dosage levels (mg)\",\n",
" y =\"Tooth length\", \n",
" color=\"Supplements\",\n",
" fill=\"Supplements\"\n",
")\n",
"bar_theme = theme(\n",
" title=element_text('#3f007d'),\n",
"\n",
" plot_subtitle=element_text(face='bold_italic'),\n",
" plot_caption=element_text(face='italic'),\n",
"\n",
" legend_title=element_text('#d95f0e'),\n",
" legend_text=element_text('#fe9929', face='italic'),\n",
"\n",
" axis_title=element_text(face='bold'),\n",
" axis_tooltip_text=element_text(color='light_pink'),\n",
" \n",
" axis_title_x=element_text('#a50f15'),\n",
" axis_text_x=element_text('pink'),\n",
"\n",
" axis_title_y=element_text('dark_green'),\n",
" axis_text_y=element_text('#a1d99b'),\n",
"\n",
" tooltip_text=element_text(color='#54278f', face='italic')\n",
")\n",
"\n",
"\n",
"bar = (\n",
" ggplot(data) + \n",
" geom_bar(aes(x='dose', color='supp', y='length', fill='supp'), stat='identity', position='dodge') + \n",
" bar_labels +\n",
" bar_theme\n",
")\n",
"bar"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "frozen-spencer",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# coord flip\n",
"bar + coord_flip()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "accredited-reducing",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# orientation \"y\"\n",
"(\n",
" ggplot(data) +\n",
" geom_bar(aes(x='length', color='supp', y='dose', fill='supp'), \n",
" stat='identity', position='dodge', orientation=\"y\") +\n",
" bar_labels +\n",
" bar_theme\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "established-watch",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Outlier Tooltips\n",
"\n",
"crossbar = (\n",
" ggplot(data, aes(x='dose', color='supp')) +\n",
" geom_crossbar(aes(ymin='len_min', ymax='len_max', middle='length'), fatten=5) +\n",
" labs(title='geom_crossbar') +\n",
" theme(\n",
" plot_title=element_text('#990000', face='bold_italic'),\n",
"\n",
" legend_title=element_text('#cc8f00'),\n",
" legend_text=element_text('orange', face='italic'),\n",
" \n",
" axis_title=element_text('#9b2d30'),\n",
" axis_text=element_text('pink'),\n",
" axis_tooltip=element_rect(color='pink', fill='#6c4675', size = 2.0),\n",
" axis_tooltip_text=element_text(color='pink'),\n",
"\n",
" tooltip=element_rect(color='dark_blue', fill='#fff5ee'),\n",
" tooltip_text=element_text(color='dark_blue', face='italic')\n",
" )\n",
")\n",
"\n",
"crossbar "
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "satellite-tomato",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# facets\n",
"\n",
"crossbar + facet_grid('supp') + theme(strip_text=element_text(color='#990000', face='bold'))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "daily-coordination",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# GGbunch with different theme options\n",
"\n",
"bars_bunch = GGBunch()\n",
"bars_bunch.add_plot(bar, 0, 0)\n",
"bars_bunch.add_plot(crossbar, 0, h*1.1)\n",
"bars_bunch"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "quantitative-earth",
"metadata": {},
"outputs": [],
"source": [
"# Save to SVG\n",
"#ggsave(bars_bunch, \"bars_bunch.svg\")\n",
"\n",
"\n",
"#from IPython.display import SVG\n",
"#display(SVG(filename=\"lets-plot-images/bars_bunch.svg\"))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}