Sorting a python array/recarray by column

This is somewhat tricky:

data[data[:,0].argsort()]

# data[:,n] -- get entire column of index n
# argsort() -- get the indices that would sort it
# data[data[:,n].argsort()] -- get data array sorted by n-th column

I found this recipe here:

http://www.scipy.org/NumPy_for_Matlab_Users

http://mathesaurus.sourceforge.net/matlab-numpy.html

Use data[np.argsort(data[:, 0])] where the 0 is the column index on which to sort:

In [27]: import numpy as np

In [28]: data = np.array([[5,2], [4,1], [3,6]])

In [29]: col = 0

In [30]: data=data[np.argsort(data[:,col])]
Out[30]: 
array([[3, 6],
       [4, 1],
       [5, 2]])

you are looking for operator.itemgetter

>>> from operator import itemgetter, attrgetter

>>> sorted(student_tuples, key=itemgetter(2))
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

>>> sorted(student_objects, key=attrgetter('age'))
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

i.e.

In [7]: a
Out[7]: [[5, 2], [4, 1], [3, 6]]

In [8]: sorted(a, key=operator.itemgetter(0))
Out[8]: [[3, 6], [4, 1], [5, 2]]

To sort on the second column use itemgetter

>>> from operator import itemgetter
>>> data = [[5,2], [4,1], [3,6]]
>>> sorted(data)
[[3, 6], [4, 1], [5, 2]]
>>> sorted(data,key=itemgetter(1))
[[4, 1], [5, 2], [3, 6]]
>>>