I have been doing a project on Time Series data and one of the items was to test for AutoCorrelation and found the charts in a different color than what I expected. I also don't see the shaded part that allows one to know the values for the order when doing ARIMA What would have caused this? Is it the data, the code, or anything else? The code is from statsmodels.graphics.tsaplots import plot_acf plot_acf(df['Column'])

I made time-series data stationary and plotter ACF & PCF, while PCF looks fine, I do not know how to interpretate ACF, as it looks like this - I could not say it geometrical. For PACF - it is Significant till 1 lag

The airline passengers dataset is available here, but it also comes with in R. I'm working with python, and I import the following (besides the usual like pandas and numpy.) from statsmodels.tsa.stattools import pacf,acf from statsmodels.graphics import tsaplots from statsmodels.tsa.stattools import adfuller,kpss from statsmodels.tsa.statespace.sarimax import SARIMAX from scipy import stats I'm applied the log, and then 1-period difference for detrending , and then 12-period for 'deseasonality'. Then I drop the nan, with df_log_dif_dif12.dropna(inplace=True). I obtain the following numpy array: array([[ …