Equivalent R's arima function in Python

Question

I tried a time series forecast with Python using statsmodel's arima function and it gave me a different result from the r's arima function. I used the same hyper-parameters.

R's version:

fit <- arima(data[1:9000,3], order = c(3,0,3), seasonal = list(order = c(0,0,0)))
predd = forecast(fit,h=1000)
pred = cbind(data[9001:10000,3], predd$mean)

Python's version:

series = df[0:9000].copy()
model = ARIMA(series, order=(3, 0, 3))
model_fitted = model.fit()
predictions = model_fitted.predict(start=len(series), end=len(df)-1)

Attached are the plots results Plots of the R's and Python's arima

What am I doing wrong?

Is there any other Python package/function arima that I can use other than statsmodel for a univariate time series?

Any insight or guidance would be greatly appreciated. Thank you so much in advance.

Answer 1

Summary : I do not know how you created the first image you showed as "R's version", but when I run the R code you gave and plot the results, they look identical to the Python results to me and do not look like the "R's version" graph you included. My best guess is that somehow you were plotting in-sample predictions when you created that image showing R's results.

See below for details.

Details :

I started by downloading the dataset "dataset.txt" from the link you gave, https://gist.github.com/DouddaS/5043a340ff7d7b35b255b4f8f74fc534

Now, if I run the following R code:

library(forecast)
y <- read.csv('dataset.txt')
fit <- arima(y[1:9000, 1], order = c(3,0,3), seasonal = list(order = c(0,0,0)))
predd = forecast(fit,h=1000)
pred = cbind(y[9001:10000,1], predd$mean)
autoplot(pred)

This gives the following plot:

And when I run the following Python code:

y = pd.read_csv('dataset.txt')
model = sm.tsa.arima.ARIMA(y.iloc[:9000, 0], order=(3, 0, 3))
model_fitted = model.fit()
pred = model_fitted.predict(start=len(series), end=len(y)-1)
predd = pd.concat([y.iloc[9000:, 0], pred], axis=1)
predd.plot()

Then I get the following plot:

These look basically identical to me, and R's version looks nothing like the image that was posted in the question.