I have a fairly simple question about how to sort an entire array/recarray by a given column. For example, given the array:
import numpy as np data = np.array([[5,2], [4,1], [3,6]]) I would like to sort data by the first column to return:
array([[3,6], [4,1], [5,2]]) 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]] 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:
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]] >>>