In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.read_csv('data/src/sample_multi.csv', index_col=[0, 1, 2])
print(df)


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0          98     90
                C1          44      9
        B1      C2          39     17
                C3          75     71
A1      B2      C0           1     89
                C1          54     60
        B3      C2          47      6
                C3          16      5
A2      B0      C0          75     22
                C1          19      4
        B1      C2          25     52
                C3          57     40
A3      B2      C0          64     54
                C1          27     96
        B3      C2         100     77
                C3          22     50

In [3]:

    

print(df.index)


    

    




MultiIndex(levels=[['A0', 'A1', 'A2', 'A3'], ['B0', 'B1', 'B2', 'B3'], ['C0', 'C1', 'C2', 'C3']],
           labels=[[0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3], [0, 0, 1, 1, 2, 2, 3, 3, 0, 0, 1, 1, 2, 2, 3, 3], [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3]],
           names=['level_1', 'level_2', 'level_3'])

In [4]:

    

print(df.loc['A0', 'val_1'])


    

    




level_2  level_3
B0       C0         98
         C1         44
B1       C2         39
         C3         75
Name: val_1, dtype: int64

In [5]:

    

print(df.loc['A0', :])


    

    




                 val_1  val_2
level_2 level_3              
B0      C0          98     90
        C1          44      9
B1      C2          39     17
        C3          75     71

In [6]:

    

print(df.loc['A0'])


    

    




                 val_1  val_2
level_2 level_3              
B0      C0          98     90
        C1          44      9
B1      C2          39     17
        C3          75     71

In [7]:

    

print(df.loc['A0':'A2', :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0          98     90
                C1          44      9
        B1      C2          39     17
                C3          75     71
A1      B2      C0           1     89
                C1          54     60
        B3      C2          47      6
                C3          16      5
A2      B0      C0          75     22
                C1          19      4
        B1      C2          25     52
                C3          57     40

In [8]:

    

print(df.loc[['A0', 'A2'], :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0          98     90
                C1          44      9
        B1      C2          39     17
                C3          75     71
A2      B0      C0          75     22
                C1          19      4
        B1      C2          25     52
                C3          57     40

In [9]:

    

print(df.loc[('A0', 'B1'), :])


    

    




         val_1  val_2
level_3              
C2          39     17
C3          75     71

In [10]:

    

print(df.loc[('A0', 'B1', 'C2'), :])


    

    




val_1    39
val_2    17
Name: (A0, B1, C2), dtype: int64

In [11]:

    

print(df.loc[(['A0', 'A1'], ['B0', 'B3']), :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0          98     90
                C1          44      9
A1      B3      C2          47      6
                C3          16      5

In [12]:

    

# print(df.loc[(:, 'B1'), :])
# SyntaxError: invalid syntax


    

In [13]:

    

# print(df.loc[('A1':'A3', 'B2'), :])
# SyntaxError: invalid syntax


    

In [14]:

    

print(df.loc[(slice(None), 'B1'), :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B1      C2          39     17
                C3          75     71
A2      B1      C2          25     52
                C3          57     40

In [15]:

    

print(df.loc[(slice('A1', 'A3'), 'B2'), :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A1      B2      C0           1     89
                C1          54     60
A3      B2      C0          64     54
                C1          27     96

In [16]:

    

print(df.loc[(slice('A1', 'A3'), ['B0', 'B2'], 'C1'), :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A1      B2      C1          54     60
A2      B0      C1          19      4
A3      B2      C1          27     96

In [17]:

    

print(df.loc[pd.IndexSlice[:, 'B1'], :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B1      C2          39     17
                C3          75     71
A2      B1      C2          25     52
                C3          57     40

In [18]:

    

print(df.loc[pd.IndexSlice['A1':'A3', 'B2'], :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A1      B2      C0           1     89
                C1          54     60
A3      B2      C0          64     54
                C1          27     96

In [19]:

    

print(df.loc[pd.IndexSlice['A1':'A3', ['B0', 'B2'], 'C1'], :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A1      B2      C1          54     60
A2      B0      C1          19      4
A3      B2      C1          27     96

In [20]:

    

print(df.xs('B1', level='level_2'))


    

    




                 val_1  val_2
level_1 level_3              
A0      C2          39     17
        C3          75     71
A2      C2          25     52
        C3          57     40

In [21]:

    

print(df.xs('C1', level=2))


    

    




                 val_1  val_2
level_1 level_2              
A0      B0          44      9
A1      B2          54     60
A2      B0          19      4
A3      B2          27     96

In [22]:

    

print(df.xs(['B1', 'C2'], level=['level_2', 'level_3']))


    

    




         val_1  val_2
level_1              
A0          39     17
A2          25     52

In [23]:

    

print(df.xs(pd.IndexSlice['A1':'A3'], level='level_1'))


    

    




                 val_1  val_2
level_2 level_3              
B2      C0           1     89
        C1          54     60
B3      C2          47      6
        C3          16      5
B0      C0          75     22
        C1          19      4
B1      C2          25     52
        C3          57     40
B2      C0          64     54
        C1          27     96
B3      C2         100     77
        C3          22     50

In [24]:

    

print(df.xs(slice('A1', 'A3'), level='level_1'))


    

    




                 val_1  val_2
level_2 level_3              
B2      C0           1     89
        C1          54     60
B3      C2          47      6
        C3          16      5
B0      C0          75     22
        C1          19      4
B1      C2          25     52
        C3          57     40
B2      C0          64     54
        C1          27     96
B3      C2         100     77
        C3          22     50

In [25]:

    

# print(df.xs(['B1', 'B2'], level='level_2'))
# KeyError: ('B1', 'B2')


    

In [26]:

    

print(df.loc[pd.IndexSlice[:, ['B1', 'B2']], :])


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B1      C2          39     17
                C3          75     71
A1      B2      C0           1     89
                C1          54     60
A2      B1      C2          25     52
                C3          57     40
A3      B2      C0          64     54
                C1          27     96

In [27]:

    

df.loc[(['A0', 'A1'], ['B0', 'B3']), :] = -100


    

In [28]:

    

print(df)


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0        -100   -100
                C1        -100   -100
        B1      C2          39     17
                C3          75     71
A1      B2      C0           1     89
                C1          54     60
        B3      C2        -100   -100
                C3        -100   -100
A2      B0      C0          75     22
                C1          19      4
        B1      C2          25     52
                C3          57     40
A3      B2      C0          64     54
                C1          27     96
        B3      C2         100     77
                C3          22     50

In [29]:

    

df.loc[(['A0', 'A1'], ['B0', 'B3']), :] = [-200, -300]


    

In [30]:

    

print(df)


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0        -200   -300
                C1        -200   -300
        B1      C2          39     17
                C3          75     71
A1      B2      C0           1     89
                C1          54     60
        B3      C2        -200   -300
                C3        -200   -300
A2      B0      C0          75     22
                C1          19      4
        B1      C2          25     52
                C3          57     40
A3      B2      C0          64     54
                C1          27     96
        B3      C2         100     77
                C3          22     50

In [31]:

    

df.loc[(['A0', 'A1'], ['B0', 'B3']), :] = [[-1, -2], [-3, -4], [-5, -6], [-7, -8]]


    

In [32]:

    

print(df)


    

    




                         val_1  val_2
level_1 level_2 level_3              
A0      B0      C0          -1     -2
                C1          -3     -4
        B1      C2          39     17
                C3          75     71
A1      B2      C0           1     89
                C1          54     60
        B3      C2          -5     -6
                C3          -7     -8
A2      B0      C0          75     22
                C1          19      4
        B1      C2          25     52
                C3          57     40
A3      B2      C0          64     54
                C1          27     96
        B3      C2         100     77
                C3          22     50

In [33]:

    

# df.xs(['B1', 'C2'], level=['level_2', 'level_3']) = 0
# SyntaxError: can't assign to function call