問題描述

如何按第一列的降序排列如下數(shù)組：

dl1 = numpy.array([[ 0.02598003,1.], [ 0.00730082,2.], [ 0.05471569,3.], [ 0.02599167,4.], [ 0.0544947 ,5.], [ 0.00753346,6.]])

網(wǎng)上其他地方說直接dl1.sort()會默認(rèn)按第一列排序，但好像不行

問題解答

sorted(dl1, key=lambda x: x[0])回答2：

>>> a=np.array([[ 0.02598003,1.], [ 0.00730082,2.], [ 0.05471569,3.], [ 0.02599167,4.], [ 0.0544947 ,5.], [ 0.00753346,6.]])>>> a.sort(0)>>> aarray([[ 0.00730082, 1.], [ 0.00753346, 2.], [ 0.02598003, 3.], [ 0.02599167, 4.], [ 0.0544947 , 5.], [ 0.05471569, 6.]])>>>

np.sort 是把各維分別排序的

如果你是要二維組的聯(lián)合排序，要用np.argsort方法

>>> a=np.array([[ 0.02598003,1.], [ 0.00730082,2.], [ 0.05471569,3.], [ 0.02599167,4.], [ 0.0544947 ,5.], [ 0.00753346,6.]])>>> a[a.argsort(0)[:,0]]array([[ 0.00730082, 2.], [ 0.00753346, 6.], [ 0.02598003, 1.], [ 0.02599167, 4.], [ 0.0544947 , 5.], [ 0.05471569, 3.]])>>>

如果數(shù)據(jù)很多的話，用python內(nèi)部的 sorted會降低效率

In [1]: lst= [[0.00730082, 2.0], ...: [0.05471569, 3.0], ...: [0.02599167, 4.0], ...: [0.0544947, 5.0], ...: [0.00753346, 6.0]] ...:In [2]: sorted(lst, key=lambda x: x[0])Out[2]:[[0.00730082, 2.0], [0.00753346, 6.0], [0.02599167, 4.0], [0.0544947, 5.0], [0.05471569, 3.0]]回答4：

dl1.sort(axis=0)

ndarray.sort的關(guān)鍵字參數(shù)axis就是用來按照某列排序

axis : int, optional

Axis along which to sort. Default is -1, which means sort along the last axis.