How to plot mean_test score and mean_train score of GridSearchCV
You could visualize them as a heatmap. 

For example you could use the C values as the rows, the gamma values as the columns and the color intensity of each element in the heatmap array would correspond to the mean_test_score.

To implement this you first need to create a pandas.DataFrame like this:

$$
\begin{array}{c | c c c}
  &amp; C   &amp; gamma &amp; mean\_test\_score \\ \hline 
1 &amp; 0.1 &amp; 0.001 &amp; 0.798 \\
2 &amp; 1   &amp; 0.001 &amp; 0.813 \\
3 &amp; 1   &amp; 0.01  &amp; 0.801 \\
4 &amp; 10  &amp; 0.001 &amp; 0.787 \\
\end{array}
$$

To do this you need to store each run you make in a different line, which will contain all necessary hyper-parameters and the result. Then you will need to make a pivot table which will use C as the rows, gamma as the columns and mean_test_score as the values.

pivot = pd.pivot_table(df, values=df['mean_test_score'])


This pivot will be the array that will form your heatmap. Now you should select your aesthetic parameters (e.g. colormap) and proceed to make the heatmap.

sns.heatmap(pivot) # plus any other aesthetic parameters you wish