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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import random\n",
"import os \n",
"import hopsworks"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Connected. Call `.close()` to terminate connection gracefully.\n",
"\n",
"Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/1160340\n",
"2024-11-20 03:57:50,799 WARNING: using legacy validation callback\n",
"Connected. Call `.close()` to terminate connection gracefully.\n",
"Finished: Reading data from Hopsworks, using Hopsworks Feature Query Service (1.82s) \n",
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 1589 entries, 0 to 1588\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 date 1589 non-null object \n",
" 1 pm25 1589 non-null float32\n",
" 2 country 1589 non-null object \n",
" 3 city 1589 non-null object \n",
" 4 street 1589 non-null object \n",
" 5 url 1589 non-null object \n",
"dtypes: float32(1), object(5)\n",
"memory usage: 68.4+ KB\n",
"None\n",
" date pm25 country city street \\\n",
"0 2024-02-23 18.0 Sweden Helsingborg Drottninggatan \n",
"1 2021-09-22 36.0 Sweden Helsingborg Drottninggatan \n",
"2 2022-09-25 55.0 Sweden Helsingborg Drottninggatan \n",
"3 2024-08-25 24.0 Sweden Helsingborg Drottninggatan \n",
"4 2023-01-06 18.0 Sweden Helsingborg Drottninggatan \n",
"\n",
" url \n",
"0 https://api.waqi.info/feed/@12519/ \n",
"1 https://api.waqi.info/feed/@12519/ \n",
"2 https://api.waqi.info/feed/@12519/ \n",
"3 https://api.waqi.info/feed/@12519/ \n",
"4 https://api.waqi.info/feed/@12519/ \n"
]
}
],
"source": [
"\n",
"from datetime import datetime, timedelta\n",
"now = datetime.now()\n",
"\n",
"api_key = os.getenv('HOPSWORKS_API_KEY')\n",
"project_name = os.getenv('HOPSWORKS_PROJECT')\n",
"\n",
"project = hopsworks.login(project=project_name, api_key_value=api_key)\n",
"fs = project.get_feature_store() \n",
"\n",
"air_quality_fg = fs.get_feature_group(\n",
" name='air_quality',\n",
" version=1,\n",
")\n",
"air_quality_df = air_quality_fg.read()\n",
"air_quality_df\n",
"\n",
"print(air_quality_df.info())\n",
"print(air_quality_df.head())"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"air_quality_df[['date', 'pm25']].to_pickle('air_quality_df.pkl')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"with gr.Blocks() as demo:\n",
" gr.Markdown(\"Helsingborg Air Quality Forecast\")\n",
" gr.LinePlot(air_quality_df, x=\"time\", y=\"price\")\n",
" gr.ScatterPlot(air_quality_df['pm25'], x=\"time\", y=\"price\", color=\"origin\")\n",
"\n",
"demo.launch() "
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"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": "3.12.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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