85 lines
2.4 KiB
Plaintext
85 lines
2.4 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "imports",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"from pyprojroot import here"
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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": null,
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"id": "load",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = pd.read_csv(here() / 'data/base/data.csv')"
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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": null,
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"id": "plot",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Calculate mean Bell parameter by country\n",
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"country_stats = data.groupby('Country').agg({\n",
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" 'Bell Parameter (S)': 'mean',\n",
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" 'Study ID': 'count'\n",
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"}).rename(columns={'Study ID': 'Count'}).sort_values('Bell Parameter (S)', ascending=False)\n",
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"\n",
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"fig, ax = plt.subplots(figsize=(14, 8))\n",
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"\n",
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"# Horizontal bar chart\n",
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"countries = country_stats.index[:20] # Top 20\n",
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"values = country_stats['Bell Parameter (S)'][:20]\n",
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"counts = country_stats['Count'][:20]\n",
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"\n",
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"bars = ax.barh(range(len(countries)), values, color='steelblue', edgecolor='black')\n",
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"\n",
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"# Color bars by value\n",
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"for i, (bar, val) in enumerate(zip(bars, values)):\n",
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" if val > 2.8:\n",
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" bar.set_color('#27ae60')\n",
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" elif val > 2.7:\n",
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" bar.set_color('#3498db')\n",
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" else:\n",
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" bar.set_color('#e67e22')\n",
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"\n",
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"# Add classical limit line\n",
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"ax.axvline(x=2.0, color='red', linestyle='--', linewidth=2, alpha=0.7, label='Classical limit')\n",
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"\n",
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"# Add counts as text\n",
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"for i, (val, count) in enumerate(zip(values, counts)):\n",
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" ax.text(val + 0.01, i, f'n={int(count)}', va='center', fontsize=9)\n",
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"\n",
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"ax.set_yticks(range(len(countries)))\n",
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"ax.set_yticklabels(countries)\n",
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"ax.set_xlabel('Mean Bell Parameter (S)', fontsize=12)\n",
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"ax.set_title('Mean Bell Parameter by Country (Top 20)', fontsize=14)\n",
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"ax.legend()\n",
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"ax.grid(True, alpha=0.3, axis='x')\n",
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"\n",
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"plt.tight_layout()\n",
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"plt.savefig(here() / 'output/plots/world_map.png', dpi=300, bbox_inches='tight')"
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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": "Python 3",
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"language": "python",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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