Axis in DataFrame

Optional parameter axis may appear in arithmetric between DataFrame and Series,the key point understanding the meaning of axis is match,by default the index of series shall match columns of DataFrame,broadcasting down the rows;And axis may also appear in max() or so function,by default, axis='index',meaning find the max one among index,and that is to find the max one of every column.

import pandas as pd

import numpy as np

frame=pd.DataFrame(np.random.randn(4,3),index=['Utah','Ohio','Texas','Oregon'],columns=list('bde'));frame

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	b	d	e
Utah	-0.311649	0.252285	-0.741715
Ohio	0.351583	1.287569	0.726872
Texas	0.605527	-0.186660	-0.993184
Oregon	1.577405	0.381833	1.607757

frame['b']

Utah     -0.311649
Ohio      0.351583
Texas     0.605527
Oregon    1.577405
Name: b, dtype: float64

series1=frame.iloc[0];series1

b   -0.311649
d    0.252285
e   -0.741715
Name: Utah, dtype: float64

frame.sub(series1,axis='columns') # By default,arithmetic between DataFrame and Series matches the index of Series on the DataFrame's columns,broadcasting down the rows.

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	b	d	e
Utah	0.000000	0.000000	0.000000
Ohio	0.663232	1.035284	1.468587
Texas	0.917176	-0.438944	-0.251470
Oregon	1.889054	0.129548	2.349471

frame.sub(series1,axis=1) # The same with above

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	b	d	e
Utah	0.000000	0.000000	0.000000
Ohio	0.663232	1.035284	1.468587
Texas	0.917176	-0.438944	-0.251470
Oregon	1.889054	0.129548	2.349471

series2=frame['d'];series2

Utah      0.252285
Ohio      1.287569
Texas    -0.186660
Oregon    0.381833
Name: d, dtype: float64

frame.sub(series2,axis='index') # Must set axis='index',so that broadcasts down on column.

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	b	d	e
Utah	-0.563934	0.0	-0.993999
Ohio	-0.935986	0.0	-0.560697
Texas	0.792186	0.0	-0.806525
Oregon	1.195572	0.0	1.225924

frame.max(axis='index') # max() default to set axis='index',meaning find the max one among 'index',not every max one of every index.

b    1.577405
d    1.287569
e    1.607757
dtype: float64