# fit the grid with data
grid.fit(X, y)
# view the results as a pandas DataFrame
import pandas as pd
pd.DataFrame(grid.cv_results_)[['mean_test_score', 'std_test_score', 'params']]
# Output

mean_test_score std_test_score  params
0   0.960000    0.053333    {'n_neighbors': 1}
1   0.953333    0.052068    {'n_neighbors': 2}
2   0.966667    0.044721    {'n_neighbors': 3}
3   0.966667    0.044721    {'n_neighbors': 4}
4   0.966667    0.044721    {'n_neighbors': 5}
5   0.966667    0.044721    {'n_neighbors': 6}
6   0.966667    0.044721    {'n_neighbors': 7}
7   0.966667    0.044721    {'n_neighbors': 8}
8   0.973333    0.032660    {'n_neighbors': 9}
9   0.966667    0.044721    {'n_neighbors': 10}