Datasets:
File size: 3,129 Bytes
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from datasets import load_dataset\n",
"\n",
"dataset = load_dataset(\"divyasharma0795/AppleVisionPro_Tweets\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"HuggingFaceDataset(id=1769458624638619691, tweetText=\"Mordecai I can't sell nft for 10 dollars, how does this nft business work? #bloodbath #AppleVisionPro #DeadpoolAndWolverine #RegularShow @JGQuintel link: https://t.co/Bq3dzV4wgR https://t.co/rbrerIFcIs\", tweetURL='https://twitter.com/harndefty/status/1769458624638619691', tweetAuthor='Harndefty 🐔🍗', handle='@harndefty', replyCount=0, quoteCount=0, retweetCount=0, likeCount=0, views='26', bookmarkCount=0, createdAt='2024-03-17 13:19:45')\n"
]
}
],
"source": [
"from dataclasses import dataclass\n",
"from typing import List\n",
"from datasets import load_dataset\n",
"\n",
"\n",
"@dataclass\n",
"class HuggingFaceDataset:\n",
" id: int\n",
" tweetText: str\n",
" tweetURL: str\n",
" tweetAuthor: str\n",
" handle: str\n",
" replyCount: int\n",
" quoteCount: int\n",
" retweetCount: int\n",
" likeCount: int\n",
" views: int\n",
" bookmarkCount: int\n",
" createdAt: str\n",
"\n",
"\n",
"def load_custom_dataset(dataset_name):\n",
" dataset = load_dataset(dataset_name)\n",
"\n",
" # Extract relevant information and create a list of HuggingFaceDataset instances\n",
" custom_dataset = [\n",
" HuggingFaceDataset(\n",
" id=row[\"id\"],\n",
" tweetText=row[\"tweetText\"],\n",
" tweetURL=row[\"tweetURL\"],\n",
" tweetAuthor=row[\"tweetAuthor\"],\n",
" handle=row[\"handle\"],\n",
" replyCount=row[\"replyCount\"],\n",
" quoteCount=row[\"quoteCount\"],\n",
" retweetCount=row[\"retweetCount\"],\n",
" likeCount=row[\"likeCount\"],\n",
" views=row[\"views\"],\n",
" bookmarkCount=row[\"bookmarkCount\"],\n",
" createdAt=row[\"createdAt\"],\n",
" )\n",
" for row in dataset[\"train\"]\n",
" ]\n",
"\n",
" return custom_dataset\n",
"\n",
"\n",
"# Usage\n",
"custom_dataset = load_custom_dataset(\"divyasharma0795/AppleVisionPro_Tweets\")\n",
"print(custom_dataset[0]) # Print the first instance"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"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": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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