How to use pandas.rolling mean for 3D input array?

[Prv_Yadv]

For 1D I can use:

a=np.array([1,2,3,4])
b=pandas.Series(a).rolling(window=3,center=True).mean()

But the problem is, if I have array a, in 3D then using this method gives error

Exception: Data must be 1-dimensional
The code which I used is:

t[:,:,0]=(pd.Series(imgg[:,:,0:4]).rolling(window=[1,1,3],center=True).mean())

Here imgg is 3D numpy array.

What else I tried:

I also tried the old function rolling_mean i.e. pd.rolling_mean(a,4,center=True), but it is also not working, it gives error:

AssertionError: cannot support ndim > 2 for ndarray compat

[scidam]

It seems that you want to work with images (imgg variable and 3D array). Did you look at scikit-image package. This package includes functions to work with rolling windows in ND space, e.g. this.