{
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"cell_type": "code",
"execution_count": 1,
"metadata": {
"execution": {
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"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import random\n",
"from lets_plot import *\n",
"\n",
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:18.979651Z",
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"source": [
"# This example was found at: www.cookbook-r.com/Graphs/Scatterplots_(ggplot2)\n",
"random.seed(123)\n",
"data = dict(\n",
" cond=np.repeat(['A','B'], 10),\n",
" xvar=[i + random.normalvariate(0, 3) for i in range(0,20)],\n",
" yvar=[i + random.normalvariate(0, 3) for i in range(0,20)]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Basic scatter-plot"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:18.982248Z",
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"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p = ggplot(data, aes(x='xvar', y='yvar')) + ggsize(300, 250)\n",
"p + geom_point(shape=1) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Add regression line"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.013138Z",
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"shell.execute_reply": "2025-11-05T13:47:19.016075Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_point(shape=1) + geom_smooth(seed=42) "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.017226Z",
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"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Without standard error band.\n",
"p + geom_point(shape=1) + geom_smooth(se=False, seed=42) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Split dataset by the `cond` variable"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.020974Z",
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"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p1 = ggplot(data, aes(x='xvar', y='yvar', color='cond')) + ggsize(500, 250)\n",
"p1 + geom_point(shape=1) + geom_smooth(se=False, seed=42)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.025749Z",
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"shell.execute_reply": "2025-11-05T13:47:19.027926Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Map `shape` to the `cond` variable.\n",
"p2 = p1 + geom_point(aes(shape='cond'), size=5)\n",
"p2"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.028922Z",
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"shell.execute_reply": "2025-11-05T13:47:19.031060Z"
},
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Choose different shapes using `scale_shape_manual`:\n",
"# 1 - hollow circle \n",
"# 2 - hollow triangle\n",
"\n",
"p2 + scale_shape_manual(values=[1,2])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Handling overplotting"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.032066Z",
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"shell.execute_reply": "2025-11-05T13:47:19.033251Z"
}
},
"outputs": [],
"source": [
"# Create data containing overlapping points.\n",
"data['xrnd'] = [round(v / 5) * 5 for v in data['xvar']]\n",
"data['yrnd'] = [round(v / 5) * 5 for v in data['yvar']]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.034153Z",
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"shell.execute_reply": "2025-11-05T13:47:19.036558Z"
}
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{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p3 = ggplot(data, aes(x='xrnd', y='yrnd')) + ggsize(500, 250)\n",
"\n",
"# Use `alpha` to show overplotting.\n",
"p3 + geom_point(alpha=.3, size=5)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-05T13:47:19.037469Z",
"iopub.status.busy": "2025-11-05T13:47:19.037398Z",
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"shell.execute_reply": "2025-11-05T13:47:19.039724Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# `jitter` points to show overplotting in another way.\n",
"p3 + geom_point(shape=1, position=position_jitter(width=.2, height=.5, seed=42))"
]
}
],
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"display_name": "Python 3 (ipykernel)",
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