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| import pandas as pd | |
| import altair as alt | |
| from datetime import datetime, timedelta | |
| import numpy as np | |
| from prophet import Prophet | |
| import os | |
| filtered_df = pd.read_csv('data/filtered_df.csv') | |
| test_df = pd.read_csv('air_quality_data.csv') | |
| test_df.drop(columns=['PM10','O3','NO2','SO2','CO'],inplace=True) | |
| test_df.rename(columns={'Timestamp':'index','PM2.5':'pm25'},inplace=True) | |
| test_df['index'] = pd.to_datetime(test_df['index']).dt.date | |
| combined_df = pd.concat([filtered_df, test_df], ignore_index=True) | |
| combined_df.rename(columns={'index': 'ds', 'pm25': 'y'}, inplace=True) | |
| model = Prophet(interval_width=0.80, yearly_seasonality=True) | |
| model.fit(combined_df) | |
| future = model.make_future_dataframe(periods=15) | |
| forecast_future = model.predict(future) | |
| csv_filepath = '/home/runner/work/air-quality/air-quality/future_forecast.csv' | |
| forecast_future.to_csv(csv_filepath,index=False) | |