dataframeから、複数範囲を指定したいとき

df_train = pd.read_csv(TRAIN_CSV)
df_valid = pd.read_csv(VALID_CSV)

df_test0  = df_valid.iloc[           0:NB_CLASSES*1,:] #Bold 
df_test1  = df_valid.iloc[NB_CLASSES*1:NB_CLASSES*2,:] #Heavy 
df_test2  = df_valid.iloc[NB_CLASSES*2:NB_CLASSES*3,:] #Light 
df_test3  = df_valid.iloc[NB_CLASSES*3:NB_CLASSES*4,:] #Medium 
df_test4  = df_valid.iloc[NB_CLASSES*4:NB_CLASSES*5,:] #Regular 
df_test5  = df_valid.iloc[NB_CLASSES*5:NB_CLASSES*6,:] #Bold 
df_test6  = df_valid.iloc[NB_CLASSES*6:NB_CLASSES*7,:] #Heavy 
df_test7  = df_valid.iloc[NB_CLASSES*7:NB_CLASSES*8,:] #Light 
df_test8  = df_valid.iloc[NB_CLASSES*8:NB_CLASSES*9,:] #Medium 
df_test9  = df_valid.iloc[NB_CLASSES*9:NB_CLASSES*10,:]#Regular

#4 9
df_valid2 = df_valid.iloc[<b>pd.np.r_</b>[
    NB_CLASSES*4:NB_CLASSES*5,
    NB_CLASSES*9:NB_CLASSES*10]]

df_test2 = df_valid.iloc[<b>pd.np.r_</b>[
    NB_CLASSES*3:NB_CLASSES*5,
    NB_CLASSES*8:NB_CLASSES*10]]

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