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https://neuralnetlab.com/wp-content/plugins/dmca-badge/libraries/sidecar/classes/{"id":597,"date":"2021-10-22T20:44:55","date_gmt":"2021-10-22T20:44:55","guid":{"rendered":"https:\/\/neuralnetlab.com\/?p=597"},"modified":"2022-02-08T17:13:49","modified_gmt":"2022-02-08T17:13:49","slug":"numpy-argsort","status":"publish","type":"post","link":"https:\/\/neuralnetlab.com\/numpy-argsort\/","title":{"rendered":"Numpy Argsort with Example"},"content":{"rendered":"\n
Numpy Argsort, sounds a bit complicated, right? And neural network students made the function a lot more complicated than it should be. But they shouldn’t have. <\/p>\n\n\n\n
Simply NumPy argsort is a numpy sorting function. But there’s more to the story.<\/p>\n\n\n\n
When you run numpy.argsort()<\/strong> on your NumPy array it returns indices or indexes of the elements after sorting them for you. You simply get a sorted array with the indices of the sorted elements in it.<\/p>\n\n\n\n So, now we know that we can use the function for sorting arrays, we should also know that it is indirect in nature. And it specifies one axis at a time. If the axis is not specified, the code executes with a set of default algorithms.<\/p>\n\n\n\n To support the intended outcome of numpy argsort function, the resulting array maintains the exact shape of the original array, preserving the data along the sorted axis. We must use the axis parameter in conjunction with this technique. If there’s no specified axis is as a parameter, the default axis, which is the last axis is taken.<\/p>\n\n\n\n Let us take a look at the parameters of the Numpy Argsort function now. In other words, here are the few tweaks we can do before sorting our NumPy arrays and returning their indices.<\/p>\n\n\n\n Below is the full function example with all the parameters in it. So you can have a basic idea of numpy argsort functions.<\/p>\n\n\n\n Here, numpy argsort is responsible for an indirect sort. The sort is done along the given axis. As mentioned earlier, the sorting is done along the default axis, also known as the last axis. The sorting is done using the algorithm indicated by the kind<\/em> <\/strong>keyword. If not specified, kind<\/strong><\/em> algorithm is set to quicksort by default.<\/p>\n\n\n\n Above example Numpy Argsort function returns a sorted array of indices. The resulting sorted array has the same shape as “a” <\/strong>which index data along the last axis.<\/p>\n\n\n\n This is where you put your array name to be sorted.<\/p>\n\n\n\n The axis of the array along which to run the sorting operation. The default value for the axis is -1, which is also known as the last axis. If specified as None, the flattened array will be used.<\/p>\n\n\n\n A NumPy array can be sorted from a single column or row into multiple columns or rows using the args.sort () function. In 2D NumPy arrays, axis 0 is the downward direction in the rows, and axis 1 is the upward direction in the columns.<\/p>\n\n\n\nThe default nature of numpy argsort function<\/h3>\n\n\n\n
Numpy Argsort Parameters<\/h2>\n\n\n\n
numpy.argsort(a, axis=- 1, kind=None, order=None)<\/code><\/pre>\n\n\n\n
Quick introduction to each Numpy Argsort parameter<\/h3>\n\n\n\n
“a”: The array to be sorted<\/strong><\/h4>\n\n\n\n
“axis” parameter: int or None (optional)<\/strong><\/h4>\n\n\n\n
“kind” parameter: {\u2018quicksort\u2019, \u2018mergesort\u2019, \u2018heapsort\u2019, \u2018stable\u2019}, optional<\/strong><\/h4>\n\n\n\n