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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_all123.sav') | |
predict=fitted_model.get_prediction(start=1401,end=1430, dynamic=True) | |
predictions=predict.predicted_mean | |
predictions | |
predictions['Harga Bawang']=predictions['Harga Bawang'].round() | |
predictions.columns=['Prediction Harga Bawang', | |
'Prediction T2M', | |
'Prediction WS10M_RANGE', | |
'Prediction PRECTOTCORR'] | |
predictions=predictions.abs() | |
predictions | |