{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.541409Z",
"iopub.status.busy": "2024-04-17T07:34:53.541308Z",
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"shell.execute_reply": "2024-04-17T07:34:53.864864Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"\n",
"from lets_plot import *\n",
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.878940Z",
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"shell.execute_reply": "2024-04-17T07:34:53.880327Z"
}
},
"outputs": [],
"source": [
"np.random.seed(42)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.881864Z",
"iopub.status.busy": "2024-04-17T07:34:53.881708Z",
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"shell.execute_reply": "2024-04-17T07:34:53.883438Z"
}
},
"outputs": [],
"source": [
"x_a = np.random.normal(-0.5, 1, 100)\n",
"y_a = np.random.normal(0, 1, 100)\n",
"cat_a = ['A' for x in range(100)]\n",
"\n",
"x_b = np.random.normal(0.5, 1, 100)\n",
"y_b = np.random.normal(0, 1, 100)\n",
"cat_b = ['B' for x in range(100)]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.884745Z",
"iopub.status.busy": "2024-04-17T07:34:53.884559Z",
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"shell.execute_reply": "2024-04-17T07:34:53.886039Z"
}
},
"outputs": [],
"source": [
"data = {}\n",
"data['x'] = np.concatenate((x_a, x_b))\n",
"data['y'] = np.concatenate((y_a, y_b))\n",
"data['cat'] = np.concatenate((cat_a, cat_b))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.887081Z",
"iopub.status.busy": "2024-04-17T07:34:53.887005Z",
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"shell.execute_reply": "2024-04-17T07:34:53.919855Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p = ggplot(data, aes('x', fill='cat'))\n",
"p + geom_point(aes(y='y', color='cat'), size=3, alpha=0.8) + \\\n",
" ggtitle('Scatter plot')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.921243Z",
"iopub.status.busy": "2024-04-17T07:34:53.921155Z",
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"shell.execute_reply": "2024-04-17T07:34:53.923872Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_histogram() + \\\n",
" ggtitle('Default histogram')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.925130Z",
"iopub.status.busy": "2024-04-17T07:34:53.924958Z",
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"shell.execute_reply": "2024-04-17T07:34:53.927548Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_histogram(position='dodge') + \\\n",
" ggtitle('Interleaved histogram')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.928630Z",
"iopub.status.busy": "2024-04-17T07:34:53.928553Z",
"iopub.status.idle": "2024-04-17T07:34:53.931326Z",
"shell.execute_reply": "2024-04-17T07:34:53.931158Z"
},
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_histogram(alpha=0.5, position='identity') + \\\n",
" ggtitle('Overlaid semi transparent histogram')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:34:53.932213Z",
"iopub.status.busy": "2024-04-17T07:34:53.932133Z",
"iopub.status.idle": "2024-04-17T07:34:53.935038Z",
"shell.execute_reply": "2024-04-17T07:34:53.934867Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_histogram(bins=10, color='white', size=0.5) + \\\n",
" ggtitle('Histogram with bins=10')"
]
}
],
"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": "3.10.13"
}
},
"nbformat": 4,
"nbformat_minor": 1
}