pandas
MultiIndexでの異なる軸の断面
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.xsを使用した断面の選択
In [1]:
import pandas as pd
import numpy as np
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
idx_row = pd.MultiIndex.from_arrays(arrays, names=['Row_First', 'Row_Second'])
idx_col = pd.MultiIndex.from_product([['A','B'], ['i', 'ii']], names=['Col_First','Col_Second'])
df = pd.DataFrame(np.random.randn(8,4), index=idx_row, columns=idx_col)
Out[1]:
Col_First A B
Col_Second i ii i ii
Row_First Row_Second
bar one -0.452982 -1.872641 0.248450 -0.319433
two -0.460388 -0.136089 -0.408048 0.998774
baz one 0.358206 -0.319344 -2.052081 -0.424957
two -0.823811 -0.302336 1.158968 0.272881
foo one -0.098048 -0.799666 0.969043 -0.595635
two -0.358485 0.412011 -0.667167 1.010457
qux one 1.176911 1.578676 0.350719 0.093351
two 0.241956 1.082138 -0.516898 -0.196605
.xsはlevel （上記のレベルまたは整数のいずれか）と、 axis ：0（行）、1（列）を受け取ります。
.xsはpandas.Seriesとpandas.DataFrame両方で利用できます。
行の選択：
In [2]: df.xs('two', level='Row_Second', axis=0)
Out[2]:
Col_First A B
Col_Second i ii i ii
Row_First
bar -0.460388 -0.136089 -0.408048 0.998774
baz -0.823811 -0.302336 1.158968 0.272881
foo -0.358485 0.412011 -0.667167 1.010457
qux 0.241956 1.082138 -0.516898 -0.196605
列の選択：
In [3]: df.xs('ii', level=1, axis=1)
Out[3]:
Col_First A B
Row_First Row_Second
bar one -1.872641 -0.319433
two -0.136089 0.998774
baz one -0.319344 -0.424957
two -0.302336 0.272881
foo one -0.799666 -0.595635
two 0.412011 1.010457
qux one 1.578676 0.093351
two 1.082138 -0.196605
.xsは選択のためだけに機能し、割り当てはできません（取得中、設定なし）：¨
In [4]: df.xs('ii', level='Col_Second', axis=1) = 0
File "<ipython-input-10-92e0785187ba>", line 1
df.xs('ii', level='Col_Second', axis=1) = 0
^
SyntaxError: can't assign to function call
.locとスライサーの使用
.xsメソッドとは異なり、これにより値を割り当てることができます。スライサーを使用した索引付けは、バージョン0.14.0以降で使用できます。
In [1]:
import pandas as pd
import numpy as np
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
idx_row = pd.MultiIndex.from_arrays(arrays, names=['Row_First', 'Row_Second'])
idx_col = pd.MultiIndex.from_product([['A','B'], ['i', 'ii']], names=['Col_First','Col_Second'])
df = pd.DataFrame(np.random.randn(8,4), index=idx_row, columns=idx_col)
Out[1]:
Col_First A B
Col_Second i ii i ii
Row_First Row_Second
bar one -0.452982 -1.872641 0.248450 -0.319433
two -0.460388 -0.136089 -0.408048 0.998774
baz one 0.358206 -0.319344 -2.052081 -0.424957
two -0.823811 -0.302336 1.158968 0.272881
foo one -0.098048 -0.799666 0.969043 -0.595635
two -0.358485 0.412011 -0.667167 1.010457
qux one 1.176911 1.578676 0.350719 0.093351
two 0.241956 1.082138 -0.516898 -0.196605
行の選択 ：
In [2]: df.loc[(slice(None),'two'),:]
Out[2]:
Col_First A B
Col_Second i ii i ii
Row_First Row_Second
bar two -0.460388 -0.136089 -0.408048 0.998774
baz two -0.823811 -0.302336 1.158968 0.272881
foo two -0.358485 0.412011 -0.667167 1.010457
qux two 0.241956 1.082138 -0.516898 -0.196605
列の選択：
In [3]: df.loc[:,(slice(None),'ii')]
Out[3]:
Col_First A B
Col_Second ii ii
Row_First Row_Second
bar one -1.872641 -0.319433
two -0.136089 0.998774
baz one -0.319344 -0.424957
two -0.302336 0.272881
foo one -0.799666 -0.595635
two 0.412011 1.010457
qux one 1.578676 0.093351
two 1.082138 -0.196605
両方の軸の選択 ：
In [4]: df.loc[(slice(None),'two'),(slice(None),'ii')]
Out[4]:
Col_First A B
Col_Second ii ii
Row_First Row_Second
bar two -0.136089 0.998774
baz two -0.302336 0.272881
foo two 0.412011 1.010457
qux two 1.082138 -0.196605
代入は動作し.xs （ .xsとは異なり.xs ）：
In [5]: df.loc[(slice(None),'two'),(slice(None),'ii')]=0
df
Out[5]:
Col_First A B
Col_Second i ii i ii
Row_First Row_Second
bar one -0.452982 -1.872641 0.248450 -0.319433
two -0.460388 0.000000 -0.408048 0.000000
baz one 0.358206 -0.319344 -2.052081 -0.424957
two -0.823811 0.000000 1.158968 0.000000
foo one -0.098048 -0.799666 0.969043 -0.595635
two -0.358485 0.000000 -0.667167 0.000000
qux one 1.176911 1.578676 0.350719 0.093351
two 0.241956 0.000000 -0.516898 0.000000
Modified text is an extract of the original Stack Overflow Documentation
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