forked from drowl87/hextra_mirror
225 lines
87 KiB
Plaintext
225 lines
87 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### What is the Jupyter Notebook?\n",
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"\n",
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"The Jupyter Notebook is an **interactive computing environment** that enables users to author notebook documents that include:\n",
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"- Live code\n",
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"- Interactive widgets\n",
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"- Plots\n",
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"- Narrative text\n",
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"- Equations\n",
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"- Images\n",
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"- Video\n",
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"\n",
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"These documents provide a **complete and self-contained record of a computation** that can be converted to various formats and shared with others using email, version control systems (like Git/[GitHub](https://github.com)) or [nbviewer.jupyter.org](https://nbviewer.jupyter.org)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Data Visualization\n",
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"\n",
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"Below is an example of a simple data visualization using the Seaborn library."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Matplotlib is building the font cache; this may take a moment.\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"<seaborn.axisgrid.FacetGrid at 0x12830caa0>"
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 1105.12x500 with 2 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"# Import seaborn\n",
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"import seaborn as sns\n",
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"\n",
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"# Apply the default theme\n",
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"sns.set_theme()\n",
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"\n",
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"# Load an example dataset\n",
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"tips = sns.load_dataset(\"tips\")\n",
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"\n",
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"# Create a visualization\n",
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"sns.relplot(\n",
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" data=tips,\n",
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" x=\"total_bill\", y=\"tip\", col=\"time\",\n",
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" hue=\"smoker\", style=\"smoker\", size=\"size\",\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>total_bill</th>\n",
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" <th>tip</th>\n",
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" <th>sex</th>\n",
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" <th>smoker</th>\n",
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" <th>day</th>\n",
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" <th>time</th>\n",
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" <th>size</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>16.99</td>\n",
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" <td>1.01</td>\n",
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" <td>Female</td>\n",
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" <td>No</td>\n",
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" <td>Sun</td>\n",
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" <td>Dinner</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>10.34</td>\n",
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" <td>1.66</td>\n",
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" <td>Male</td>\n",
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" <td>No</td>\n",
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" <td>Sun</td>\n",
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" <td>Dinner</td>\n",
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" <td>3</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>21.01</td>\n",
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" <td>3.50</td>\n",
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" <td>Male</td>\n",
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" <td>No</td>\n",
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" <td>Sun</td>\n",
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" <td>Dinner</td>\n",
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" <td>3</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>23.68</td>\n",
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" <td>3.31</td>\n",
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" <td>Male</td>\n",
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" <td>No</td>\n",
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" <td>Sun</td>\n",
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" <td>Dinner</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>24.59</td>\n",
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" <td>3.61</td>\n",
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" <td>Female</td>\n",
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" <td>No</td>\n",
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" <td>Sun</td>\n",
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" <td>Dinner</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" total_bill tip sex smoker day time size\n",
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"0 16.99 1.01 Female No Sun Dinner 2\n",
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"1 10.34 1.66 Male No Sun Dinner 3\n",
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"2 21.01 3.50 Male No Sun Dinner 3\n",
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"3 23.68 3.31 Male No Sun Dinner 2\n",
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"4 24.59 3.61 Female No Sun Dinner 4"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tips.head()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Equations\n",
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"\n",
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"The following is an example of a simple equation using LaTeX.\n",
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"\n",
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"$$\n",
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"E = mc^2\n",
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"$$"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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