Use numpy.concatenate(list1 , list2) or numpy.append()

Look into the thread at Concatenate a NumPy array to another NumPy array.

It would be helpful if you could post the full stack trace, so that we can see which line your error occurs at. In general, the more information you can provide in a question, the better.

In this case, it looks like your full_model_pipeline may somehow become a numpy array. Since you have a one-element pipeline, you could try changing

full_model_pipeline = Pipeline(steps =[
                        ('full_pipeline',full_pipeline),
                        ('model',LinearRegression())
                    ])

full_model_pipeline.fit(X_train,y_train)

to

model = LinearRegression()
model.fit(X_train, y_train)

You are converting ids into an array after the first iteration. When running it, you should have only one item in the array as is. I would move the line ids = np.array(ids) to outside the for loop. See below:

path = [os.path.join("data", f) for f in os.listdir("data")]
faces = []
ids = []

for image in path :
    img = Image.open(image).convert('L')
    nimg = np.array(img, 'uint8')
    id = int(os.path.split(image)[1].split(".")[1])
    faces.append(nimg)
    ids.append(id)

ids = np.array(ids)
clf = cv2.face.EigenFaceRecognizer_create()
clf.train(faces, ids)
clf.write("classifier.yml")

If you wanted to truly have it be an array, you would have to use the following styled code, but a list should also be fine until the end.

ids = np.array(ids)
ids = np.append(ids, [id])