sella / app.py
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Update app.py
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from statsmodels.tsa.statespace.varmax import VARMAX
import matplotlib.pyplot as plt
import statsmodels.api as sm
import pandas as pd
import numpy as np
import warnings
warnings.filterwarnings('ignore')
import streamlit as st
import joblib
fitted_model = joblib.load('modelling_all.sav')
predict=fitted_model.get_prediction(start=1401,end=1430, dynamic=True)
predictions=predict.predicted_mean
predictions['Harga Bawang']=predictions['Harga Bawang'].round()
predictions.columns=['Prediction Harga Bawang',
'Prediction T2M',
'Prediction RH2M',
'Prediction WS10M_RANGE',
'Prediction PRECTOTCORR']
predictions=predictions.abs()
predictions