从每列中减去中位数

Question

I have a dataframe, df with numbers, like so:

1 1 1
2 1 1
2 1 3

I'd like to deduct the median from each column so that the median of each becomes 0.

-1 0 0
0 0 0
0 0 2

How do I do this in a pythandic way? I'm guessing it is possible without iterating over the values, computing the median and then deducting. I'd like to do it tersely, approximately like so:

from numpy import median
df -= median(df) #does not work, deducts median for whole dataframe

Answer 1

Just like this

df -= df.median(axis=0)

median of numpy computes median of overall data. To accomplish using numpy , try this code instead.

df -= median(df, axis=0)

for more detail, see the document: http://docs.scipy.org/doc/numpy/reference/generated/numpy.median.html

Answer 2

Some testing in ipython showed:

In [23]: A = numpy.arange(9)

In [24]: B = A.reshape((3,3))

In [25]: C = numpy.median(B,axis=0)

In [26]: D = B - C[None,:]

In [27]: B
Out[27]: 
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])

In [28]: D
Out[28]: 
array([[-3., -3., -3.],
       [ 0.,  0.,  0.],
       [ 3.,  3.,  3.]])
In [29]: C
Out[29]: array([ 3.,  4.,  5.])

So the next line gets the median along the columns

C = numpy.median(B,axis=0)

And the next line subtracts it from the matrix, column by column

D = B - C[None,:]