how compute cohen kappa scores in a loop?

I have two different lists and each of which contain 390 other lists with predictions from two classifiers. I want to compute the agreement between the classifiers when predicting the labels. How can this be done? I tried unsuccessfully the below code:

from sklearn.metrics import cohen_kappa_score

svc_preds= clf_predictions_svc_pool.tolist()
sgd_preds = clf_predictions_sgd_pool.tolist()

k_scores=[]
for i in svc_preds:
  for j in sgd_preds:
    K = cohen_kappa_score(i, j)
    k_scores.append(K)

Can someone help me to achieve my goal? Thanks in advance