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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "parameters-cell",
"metadata": {
"tags": ["parameters"]
},
"outputs": [],
"source": [
"import json\n",
"\n",
"with open('/tmp/input.txt', 'r') as f:\n",
" fruits = f.read().splitlines()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "price-lookup",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"# Example fruit price dictionary\n",
"fruit_prices = {\n",
" 'apple': 1.2,\n",
" 'banana': 0.5,\n",
" 'orange': 0.8,\n",
" 'grape': 2.5,\n",
" 'mango': 1.8\n",
"}\n",
"\n",
"# Look up prices\n",
"prices = [(fruit, fruit_prices.get(fruit, 'N/A')) for fruit in fruits]\n",
"df = pd.DataFrame(prices, columns=['Fruit', 'Price'])\n",
"\n",
"# Convert to CSV\n",
"csv_output = df.to_csv('/tmp/output.csv',index=False)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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