Type Error; only integer scalar arrays can be converted to a scalar index

What is wrong with this script? I got stuck here. I need your contributions.

#split the targets into training/testing sets using LeaveOneOut

192 sets as training and 1 set as testing

data = LeaveOneOut()
data.get_n_splits (np_all)

results_hansen_d_pred_lasso =

for train_index, test_index in data.split(np_all):
#print ("TRAIN:", train_index, "TEST:", test_index)
np_all_train, np_all_test = np_all[train_index], np_all[test_index]
hansen_d_train, hansen_d_test = hansen_d[train_index], hansen_d[test_index]

#print(np_fps_train, np_fps_test, hansen_d_train, hansen_d_test)
# we can only use predic on data that is of the same dimensionality
# as the training data was. When we want to predict using new value 
# using just one row, that row has to be reshaped to be part of another array.
np_all_test_reshape = np.array(np_all_test)
np_all_test_reshape = np_all_test_reshape.reshape (1,-1)
alpha = 0.1
lasso = Lasso(alpha=alpha)
hansen_d_pred_lasso = lasso.fit(np_all_train, hansen_d_train).predict(np_all_test_reshape)


print (hansen_d_pred_lasso)


Are you getting an error message after running this script?

Please paste the associated error message below.

Type Error; only integer scalar arrays can be converted to a scalar index

The emphasis is on:
hansen_d_train, hansen_d_test = hansen_d[train_index], hansen_d[test_index]

This error will be hard for someone to reproduce looking at the code, w/o getting more context regarding the code you are running itself - is this the entire piece of code you are running?

Is ‘data’ here a pandas dataframe?

What is the definition of the LeaveOneOut() function?
What is "np_all’ here(how is it defined)?