{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "major-scott",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from lets_plot import *\n",
"\n",
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "parallel-constraint",
"metadata": {},
"outputs": [],
"source": [
"from ipywidgets import widgets\n",
"from IPython.display import display\n",
"\n",
"flavors = [\"default\", \"darcula\", \"solarized_light\", \"solarized_dark\",\"high_contrast_light\", \"high_contrast_dark\"]\n",
"\n",
"dropdown_flavors = widgets.Dropdown(options = flavors, description = \"Theme flavor:\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "foster-potter",
"metadata": {},
"outputs": [],
"source": [
"from IPython.display import Javascript, display\n",
"\n",
"def run_all(ev):\n",
" display(Javascript('IPython.notebook.execute_cells_below()'))\n",
"\n",
"button = widgets.Button(description=\"Run all with flavor\")\n",
"button.on_click(run_all)\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "adjacent-jaguar",
"metadata": {},
"outputs": [],
"source": [
"def withFlavor():\n",
" if (dropdown_flavors.value == \"darcula\"):\n",
" return flavor_darcula()\n",
" if (dropdown_flavors.value == \"solarized_light\"):\n",
" return flavor_solarized_light()\n",
" if (dropdown_flavors.value == \"solarized_dark\"):\n",
" return flavor_solarized_dark()\n",
" if (dropdown_flavors.value == \"high_contrast_light\"):\n",
" return flavor_high_contrast_light()\n",
" if (dropdown_flavors.value == \"high_contrast_dark\"):\n",
" return flavor_high_contrast_dark()\n",
" return theme()\n",
"\n",
"def show(p):\n",
" return p + ggsize(450, 300) + withFlavor()"
]
},
{
"cell_type": "markdown",
"id": "completed-andrews",
"metadata": {},
"source": [
"### Data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "devoted-pioneer",
"metadata": {},
"outputs": [],
"source": [
"mpg_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv')\n",
"\n",
"class_df = mpg_df.groupby('class').hwy.agg(['min', 'median', 'max', 'count']).reset_index()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "requested-imagination",
"metadata": {},
"outputs": [],
"source": [
"from scipy.stats import multivariate_normal\n",
"def generate_random_data(size=50, mean=[0, 0], cov=[[1, .5], [.5, 1]], seed=42):\n",
" np.random.seed(seed)\n",
" x = np.linspace(-1, 1, size)\n",
" y = np.linspace(-1, 1, size)\n",
" X, Y = np.meshgrid(x, y)\n",
" Z = multivariate_normal(mean, cov).pdf(np.dstack((X, Y)))\n",
" return pd.DataFrame({'x': X.flatten(), 'y': Y.flatten(), 'z': Z.flatten()})\n",
"\n",
"random_df = generate_random_data()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "undefined-horizon",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The geodata is provided by © OpenStreetMap contributors and is made available here under the Open Database License (ODbL).\n"
]
}
],
"source": [
"midwest_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/midwest.csv')\n",
"pop_df = midwest_df.groupby('state').poptotal.sum().to_frame('population').reset_index()\n",
"\n",
"from lets_plot.geo_data import *\n",
"states_df = geocode('state', pop_df.state, scope='US').get_boundaries(9)"
]
},
{
"cell_type": "markdown",
"id": "satisfactory-algeria",
"metadata": {},
"source": [
"### ↓ Run all with selected flavor ↓"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "southeast-angle",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "5c4d777f62d04534a931654c24a2a376",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Dropdown(description='Theme flavor:', options=('default', 'darcula', 'solarized_light', 'solarized_dark', 'hig…"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "efc76bdbff6041afb84ad2460f6253ad",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Button(description='Run all with flavor', style=ButtonStyle())"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"display(dropdown_flavors)\n",
"display(button)"
]
},
{
"cell_type": "markdown",
"id": "apart-relation",
"metadata": {},
"source": [
"### Geoms"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "downtown-minneapolis",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# POINT\n",
"\n",
"show(\n",
" ggplot(mpg_df, aes('cty', 'hwy')) + geom_point()\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "lyric-palestine",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# POINT + shape\n",
"\n",
"show(\n",
" ggplot(mpg_df, aes('cty', 'hwy')) + geom_point(shape=22)\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "adjusted-command",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# JITTER\n",
"\n",
"show( ggplot(mpg_df, aes('fl', 'drv')) + geom_jitter() )"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "gross-spell",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# PATH\n",
"\n",
"t = np.linspace(0, 2 * np.pi, 100)\n",
"show(\n",
" ggplot({'x': t * np.sin(t), 'y': t * np.cos(t)}, aes(x='x', y='y')) + geom_path()\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "unnecessary-premiere",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# LINE\n",
"\n",
"x = np.linspace(-4 * np.pi, 4 * np.pi, 100)\n",
"y = np.sin(x)\n",
"\n",
"show( ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_line() )"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "pending-investor",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# SEGMENT\n",
"\n",
"show( ggplot() + geom_segment(x=0, y=0, xend=1, yend=1, arrow=arrow()) )"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "rural-example",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# ABLINE\n",
"\n",
"show( ggplot() + geom_abline(slope=.5))"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "angry-education",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# HLINE\n",
"\n",
"show( ggplot() + geom_hline(yintercept=0) )"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "baking-structure",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# VLINE \n",
"\n",
"show( ggplot() + geom_vline(xintercept=0) )"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "sexual-exploration",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# CONTOUR\n",
"\n",
"show( ggplot(random_df, aes('x', 'y')) + geom_contour(aes(z='z')) )"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "plain-mathematics",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# DENSITY2D\n",
"\n",
"show( ggplot(mpg_df, aes('cty', 'hwy')) + geom_density2d() )"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "public-theme",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# FREQPOLY\n",
"\n",
"show( ggplot(mpg_df, aes(x='hwy')) + geom_freqpoly() )"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "aboriginal-plaza",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# STEP\n",
"\n",
"show( ggplot(mpg_df, aes(x='hwy')) + geom_step(aes(y='..count..'), stat='bin') )"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "second-fleet",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# DENSITY\n",
"\n",
"show( ggplot(mpg_df, aes(x='hwy')) + geom_density() )"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "manufactured-tennessee",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# SMOOTH\n",
"\n",
"np.random.seed(42)\n",
"n = 50\n",
"x = np.arange(n)\n",
"y = x + np.random.normal(scale=10, size=n)\n",
"show(\n",
" ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_smooth() \n",
")"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "forty-hello",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# LOLLIPOP\n",
"\n",
"show(\n",
" ggplot({\n",
" 'x': [-3, -2, -1, 0, 1, 2, 3],\n",
" 'y': [2, 3, -2, 3, -1, 0, 4],\n",
" }, aes('x', 'y')) + geom_lollipop()\n",
") "
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "numeric-conversion",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# DOT_PLOT\n",
"\n",
"show( ggplot(mpg_df, aes(x='hwy')) + geom_dotplot() )"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "convenient-millennium",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Y_DOT_PLOT\n",
"\n",
"show(\n",
" ggplot(mpg_df, aes('class', 'hwy')) + geom_ydotplot()\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "fatty-technician",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# BAR\n",
"\n",
"show( ggplot(mpg_df, aes('hwy')) + geom_bar() )"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "underlying-pocket",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# HISTOGRAM\n",
"\n",
"show( ggplot(mpg_df, aes(x='hwy')) + geom_histogram() )"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "speaking-crisis",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# PIE\n",
"\n",
"show(\n",
" ggplot({'name': ['a', 'b', 'c'], 'value': [40, 90, 10]}) + \n",
" geom_pie(aes(slice='value'), stat='identity')\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "million-recorder",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# BIN_2D\n",
"\n",
"show( ggplot(mpg_df, aes('cty', 'hwy')) + geom_bin2d() )"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "mysterious-castle",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# TILE\n",
"\n",
"show( ggplot(mpg_df, aes('cty', 'hwy')) + geom_tile() )"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "located-horse",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# RASTER\n",
"\n",
"show( ggplot(random_df, aes('x', 'y')) + geom_raster() )"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "infectious-submission",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# ERROR_BAR\n",
"\n",
"show(\n",
" ggplot(class_df, aes(x='class')) + geom_errorbar(aes(ymin='min', ymax='max'))\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "built-morris",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# CROSSBAR\n",
"\n",
"show(\n",
" ggplot(class_df, aes(x='class')) + geom_crossbar(aes(ymin='min', middle='median', ymax='max'))\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "valid-universal",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# LINERANGE\n",
"\n",
"show( ggplot(class_df, aes(x='class')) + geom_linerange(aes(ymin='min', ymax='max')) )"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "proper-workstation",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# POINTRANGE \n",
"\n",
"show(\n",
" ggplot(class_df, aes(x='class')) + geom_pointrange(aes(ymin='min', y='median', ymax='max')) \n",
")"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "advance-favorite",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# BOXPLOT\n",
"\n",
"show( ggplot(mpg_df, aes('class', 'hwy')) + geom_boxplot() )"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "liquid-kenya",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# VIOLIN \n",
"\n",
"show( ggplot(mpg_df, aes('class', 'hwy')) + geom_violin() )"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "massive-integration",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# AREA_RIDGE\n",
"\n",
"show( ggplot(mpg_df, aes('hwy', 'class')) + geom_area_ridges() )"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "polished-highway",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# AREA\n",
"\n",
"show( ggplot(mpg_df, aes(x='hwy')) + geom_area(stat='bin') )"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "classified-content",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# CONTOURF\n",
"\n",
"show( ggplot(random_df, aes('x', 'y')) + geom_contourf(aes(z='z')) )"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "executed-sculpture",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# POLYGON\n",
"\n",
"show( ggplot() + geom_polygon(data=states_df) )"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "lonely-allah",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# RECT\n",
"\n",
"show( ggplot() + geom_rect(xmin=-1, xmax=1, ymin=-1, ymax=1) )"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "complex-category",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# RIBBON\n",
"\n",
"n = 10\n",
"np.random.seed(42)\n",
"x = np.arange(n)\n",
"ymin = np.random.randint(-5, 0, size=n)\n",
"ymax = np.random.randint(1, 6, size=n)\n",
"show(\n",
" ggplot({'x': x, 'ymin': ymin, 'ymax': ymax}, aes(x='x')) + geom_ribbon(aes(ymin='ymin', ymax='ymax'))\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "failing-julian",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# DENSITY2DF\n",
"\n",
"show( ggplot(mpg_df, aes('cty', 'hwy')) + geom_density2df() )"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "designing-litigation",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# MAP\n",
"\n",
"show( ggplot() + geom_map(data=states_df) )"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "recovered-attraction",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# TEXT\n",
"\n",
"show( ggplot() + geom_text(x=0, y=0, label='Lorem ipsum'))\n",
"#ggplot(mpg_df, aes('cty', 'hwy')) + geom_text(aes(label='fl'))"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "boring-deficit",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# LABEL\n",
"\n",
"show( ggplot() + geom_label(x=0, y=0, label='Lorem ipsum') )\n",
"#ggplot(mpg_df, aes('cty', 'hwy')) + geom_label(aes(label='fl'))"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "equipped-connection",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# QQ\n",
"\n",
"show( ggplot(mpg_df, aes(sample='hwy')) + geom_qq() )"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "caring-feature",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# QQ2\n",
"\n",
"show( ggplot(mpg_df, aes(x='cty', y='hwy')) + geom_qq2() )"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "educational-rover",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# QQ_LINE\n",
"\n",
"show( ggplot(mpg_df, aes(sample='hwy')) + geom_qq_line() )"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "august-tennessee",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# QQ2_LINE\n",
"\n",
"show( ggplot(mpg_df, aes(x='cty', y='hwy')) + geom_qq2_line() )"
]
}
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