# Select Percentile works on the Percentiles, I create a list of percentile that
# provides the progressive number of features from 2 to 20:
n_comp=list(100*i/42 for i in range(2,21))
# iteration loop
for n in n_comp:
    comp=n
    select_sp=SelectPercentile(percentile=comp)
    X_r2 = select_sp.fit(Xtrain_scaled,ytrain).transform(Xtrain_scaled)
    X_r2_val = select_sp.transform(Xval_scaled)
    lr.fit(X_r2, ytrain)
    knn.fit(X_r2, ytrain)
    lin_svc.fit(X_r2, ytrain)
    results_logreg_sp[comp]={'LogReg Num. features':X_r2.shape[1],
                             'Training Score':lr.score(X_r2, ytrain),
                             'Valuation Score':lr.score(X_r2_val, yval)}
    results_knn_sp[comp]={'KNN Num. features':X_r2.shape[1],
                          'Training Score':knn.score(X_r2, ytrain),
                          'Valuation Score':knn.score(X_r2_val, yval)}
    results_LinSVC_sp[comp]={'Lin SVC Num. features':X_r2.shape[1],
                             'Training Score':lin_svc.score(X_r2, ytrain),
                             'Valuation Score':lin_svc.score(X_r2_val, yval)}
# Display the dataframes:
res_logreg_sp=pd.DataFrame(results_logreg_sp).T.set_index('LogReg Num. features')
res_knn_sp=pd.DataFrame(results_knn_sp).T.set_index('KNN Num. features')
res_LinSVC_sp=pd.DataFrame(results_LinSVC_sp).T.set_index('Lin SVC Num. features')
display_side_by_side(res_logreg_sp,res_knn_sp,res_LinSVC_sp)