Hi, I am trying to run my K-fold cross-validation and this happened

'numpy.ndarray' object has no attribute 'iloc'

from sklearn import model_selection

kFold = model_selection.KFold(n_splits=5, shuffle=True)

#use the split function of kfold to split the housing data set
for trainIndex, testIndex in kFold.split(df):
    print("Fold: ",i)
    print(trainIndex.shape)
    print(trainIndex)
    i += 1

lRegPara = [0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1]

final_results = []
i=0

for trainIndex, testIndex in kFold.split(df):


    # split the train test further
    trainX, validX, trainY, validY = train_test_split(np.array(X.iloc[trainIndex]),
                                                                      np.array(Y.iloc[trainIndex]), 
                                                                      test_size=0.20, random_state=99)

    # optimise the linear regression
    lResults = []


    for regPara in lRegPara:

        polyLassoReg = Lasso(alpha=regPara, normalize=True)

        polyFitTrainX = polyreg.fit_transform(trainX)

        polyLassoReg.fit(polyFitTrainX, trainY)

        polyFitValidX = polyreg.fit_transform(validX)

        predictKY = polyLassoReg.predict(polyFitValidX)

        mse = mean_squared_error(predictKY, validY)

        lResults.append(mse)

    final_results.append(lResults)

    plt.plot(lRegPara, lResults)

Why? I have been getting this error 'numpy.ndarray' object has no attribute 'iloc'. I have search everywhere but there are no similar problem. I tried function 'loc' in numpy and the result still the same.

https://imgur.com/gallery/yAdAjdx

Hello,

Linked is the screenshot of the two error messages I keep recieving as well as the code leading up to it. I'm trying to run an uplift on a classification tree. Any help is appreciated, I am still fairly new to python. Thank you!!