new_data['Date'] = pd.to_datetime(new_data.Date,format='%Y-%m-%d')
new_data.index = new_data['Date']
#preparing data
new_data.rename(columns={'Close': 'y', 'Date': 'ds'}, inplace=True)
#train and validation
train = new_data[:987]
valid = new_data[987:]
#fit the model
model = Prophet()
model.fit(train)
#predictions
close_prices = model.make_future_dataframe(periods=len(valid))
forecast = model.predict(close_prices)
#rmse
forecast_valid = forecast['yhat'][987:]
rms=np.sqrt(np.mean(np.power((np.array(valid['y'])-np.array(forecast_valid)),2)))
rms
#plot
valid['Predictions'] = 0
valid['Predictions'] = forecast_valid.values
plt.plot(train['y'])
plt.plot(valid[['y', 'Predictions']])
