python中的列表及numpy数组排序

一、列表排序 

# python中对列表排序有sort、sorted两种方法，其中sort是列表内置方法，其帮助文档如下：
In [1]: help(sorted)
Help on built-in function sorted in module builtins:
sorted(iterable, /, *, key=None, reverse=False)
    Return a new list containing all items from the iterable in ascending order.

    A custom key function can be supplied to customize the sort order, and the
    reverse flag can be set to request the result in descending order.

In [2]: help(list.sort)
Help on method_descriptor:
sort(...)
    L.sort(key=None, reverse=False) -> None -- stable sort *IN PLACE*

# 一维列表排序
a = [2,1,4,3,5]
a.sort()         #[1, 2, 3, 4, 5]
a.sort(reverse=True) #[5, 4, 3, 2, 1]
# sorted()用法同sort(),不同点在于sorted()方法不影响原列表元素的顺序
a = [2,1,4,3,5]
b = sorted(a) # b: [1, 2, 3, 4, 5]
a             # a: [2, 1, 4, 3, 5]

# 二维列表排序
# 二维列表排序，可以设置sort()和sorted()方法的key关键字，通过lambda函数指定排序关键字
a = [[1,'b',5],[3,'c',3],[5,'a',4],[4,'d',1],[2,'f',2]]
a.sort(key=(lambda x:x[0])) # [[1, 'b', 5], [2, 'f', 2], [3, 'c', 3], [4, 'd', 1], [5, 'a', 4]]
a.sort(key=(lambda x:x[1])) # [[5, 'a', 4], [1, 'b', 5], [3, 'c', 3], [4, 'd', 1], [2, 'f', 2]]
a.sort(key=(lambda x:x[0]),reverse=True) # reverse=True 按照x[0]降序排列 [[5, 'a', 4], [4, 'd', 1], [3, 'c', 3], [2, 'f', 2], [1, 'b', 5]]

二、numpy数组排序

1. numpy.sort()

# numpy.sort()
In [3]: help(np.sort)
Help on function sort in module numpy.core.fromnumeric:

sort(a, axis=-1, kind='quicksort', order=None)
    Return a sorted copy of an array.

    Parameters
    ----------
    a : array_like
        Array to be sorted.
    axis : int or None, optional
        Axis along which to sort. If None, the array is flattened before
        sorting. The default is -1, which sorts along the last axis.
    kind : {'quicksort', 'mergesort', 'heapsort'}, optional
        Sorting algorithm. Default is 'quicksort'.
    order : str or list of str, optional
        When `a` is an array with fields defined, this argument specifies
        which fields to compare first, second, etc.  A single field can
        be specified as a string, and not all fields need be specified,
        but unspecified fields will still be used, in the order in which
        they come up in the dtype, to break ties.

    Returns
    -------
    sorted_array : ndarray
        Array of the same type and shape as `a`.

In [4]: a
Out[1]:
array([['1', 'b', '5'],
       ['3', 'c', '3'],
       ['5', 'a', '4'],
       ['4', 'd', '1'],
       ['2', 'f', '2']], dtype='<U11')

In [5]: np.sort(a,axis=0)  # axis=0 按列跨行排序
Out[2]:
array([['1', 'a', '1'],
       ['2', 'b', '2'],
       ['3', 'c', '3'],
       ['4', 'd', '4'],
       ['5', 'f', '5']], dtype='<U11')

In [6]: np.sort(a,axis=1)  # axis=1 按行跨列排序
Out[3]:
array([['1', '5', 'b'],
       ['3', '3', 'c'],
       ['4', '5', 'a'],
       ['1', '4', 'd'],
       ['2', '2', 'f']], dtype='<U11')

2. numpy.msort()

# numpy.msort() 与numpy.sort()基本相同，只是没有axis参数，相当于numpy.sort()在axis=0时的特殊情况
In [7]: np.msort(a)
Out[4]:
array([['1', 'a', '1'],
       ['2', 'b', '2'],
       ['3', 'c', '3'],
       ['4', 'd', '4'],
       ['5', 'f', '5']], dtype='<U1')

numpy中还有ndarray.sort()、argsort()、lexsort()以及复数排序sort_complex()方法，用到后再学习记录，待续……