print variances when plotting evaluation variance benchmark

plot.py

@@ -17,13 +17,18 @@ def plot_bench(data_path):
     df = pd.read_csv(data_path, sep=";",
                      names=bench_headers, index_col=[0,1,2])
     for method_label in df.index.levels[0]:
-        cur_df = df.loc[method_label]
-        plot = df[['mean']].loc['pubeval'].unstack().T.plot.box()
+        df_prime = df[['mean']].loc[method_label].unstack().T
+        plot = df_prime.plot.box()
         plot.set_title("Evaluation variance, {}".format(method_label))
         plot.set_xlabel("Sample count")
         plot.set_ylabel("Mean score")
         plt.show(plot.figure)
-        del cur_df, plot
+
+        # for later use:
+        variances = df_prime.var()
+        print(variances)
+
+        del df_prime, plot, variances
 
 def dataframes(model_name):
     def df_timestamp_to_datetime(df):