python中的列表及numpy數組排序
阿新 • • 發佈:2019-01-11
fun one tom ont merge numpy for core uil
一、列表排序
# python中對列表排序有sort、sorted兩種方法,其中sort是列表內置方法,其幫助文檔如下:
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*
# 一維列表排序
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(),不同點在於sorted()方法不影響原列表元素的順序
a = [2,1,4,3,5]
b = sorted(a) # b: [1, 2, 3, 4, 5]
a # a: [2, 1, 4, 3, 5]
# 二維列表排序
# 二維列表排序,可以設置sort()和sorted()方法的key關鍵字,通過lambda函數指定排序關鍵字
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數組排序
# 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 arrayis 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‘)
numpy中還有ndarray.sort()、argsort()和lexsort()方法,用到後再學習記錄,待續……
python中的列表及numpy數組排序