{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append(\"..\")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Imports"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from finnlp.data_sources.social_media.finnhub_sentiment import Finnhub_Sentiment"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Config"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"stock = \"AAPL\"\n",
"start_date = \"2023-01-16\"\n",
"end_date = \"2023-02-19\"\n",
"token = \"YOUR_FINNHUB_TOKEN\""
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### News_downloader"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"downloader = Finnhub_Sentiment({\"token\":token})"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "75c33d2d1c984dbd959c21fdbaa437f4",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/9 [00:00, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"downloader.download_sentiment(start_date,end_date,stock)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(477, 7)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"downloader.reddit.shape"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" atTime | \n",
" mention | \n",
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" negativeScore | \n",
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" negativeMention | \n",
" score | \n",
"
\n",
" \n",
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" 2023-01-16 00:00:00 | \n",
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" 2023-01-16 08:00:00 | \n",
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],
"text/plain": [
" atTime mention positiveScore negativeScore \\\n",
"55 2023-01-16 00:00:00 3 0.832384 -0.992166 \n",
"54 2023-01-16 01:00:00 1 0.000000 -0.738558 \n",
"53 2023-01-16 03:00:00 1 0.871529 0.000000 \n",
"52 2023-01-16 06:00:00 1 0.000000 -0.995663 \n",
"51 2023-01-16 08:00:00 1 0.000000 -0.999917 \n",
"\n",
" positiveMention negativeMention score \n",
"55 1 1 -0.087573 \n",
"54 0 1 -1.000000 \n",
"53 1 0 1.000000 \n",
"52 0 1 -1.000000 \n",
"51 0 1 -1.000000 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"downloader.reddit.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(571, 7)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"downloader.twitter.shape"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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\n",
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" atTime | \n",
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" negativeMention | \n",
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" \n",
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" 63 | \n",
" 2023-01-16 00:00:00 | \n",
" 185 | \n",
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" 56 | \n",
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" 2023-01-16 01:00:00 | \n",
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" 71 | \n",
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"text/plain": [
" atTime mention positiveScore negativeScore \\\n",
"63 2023-01-16 00:00:00 185 0.944244 -0.934446 \n",
"62 2023-01-16 01:00:00 175 0.957532 -0.934711 \n",
"61 2023-01-16 02:00:00 149 0.953763 -0.943735 \n",
"60 2023-01-16 03:00:00 176 0.952826 -0.941478 \n",
"59 2023-01-16 04:00:00 234 0.917571 -0.933355 \n",
"\n",
" positiveMention negativeMention score \n",
"63 104 56 0.304738 \n",
"62 82 74 0.063303 \n",
"61 67 71 -0.023705 \n",
"60 98 58 0.261998 \n",
"59 119 94 0.108952 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"downloader.twitter.head(5)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "finrl",
"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": "3.7.12"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "afd6dc03c9be451573fc2885de79a969af6a24a159f11a3ead741ab7a9ff405f"
}
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"nbformat_minor": 2
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