Some sorting methods of numpy array are discussed

A simple introduction

NumPy is an open source array computation extension of Python. This tool can be used to store and process large matrices much more efficiently than Python's own nested list structure (nested list structure), which can also be used to represent matrices (matrix).

Create an array

Create a 1-dimensional array:

data = np.array([1,3,4,8])　

View array dimensions

data.shape

View array types

data.dtype

Gets or modifies array elements by index

data[1] 获取元素
data[1] = 'a' 修改元素　

Create a 2-dimensional array

data = np.array([[1,2,3],[4,5,6]]) Both elements are lists < br > data = ES45en.arange (10) like python's range1, range returns a list and arange returns an array of type array < br > 3.data2 = data.reshape (2,5) returns a 2*5 array. It is not a copy of the array but a reference

Creating a special array

data = np.zeros((2,2)) 创建2*2全为0的2维数组
data = np.ones((2,3,3,)) 创建全为1的3维数组
data = np.eye(4) 创建4*4的对角数组，对角元素为1，其它都为0


An array of conversion

data = np.arange(16).reshape(4,4) 将0-16的移位数组转换为4*4的数组　

The sorting way

Description: often need to sort array or list, python provides several sort functions, the following characteristics;

2-dimensional array a:

1 4
3 1

1. ndarray.sort(axis=-1,kind='quicksort',order=None)

Usage: ES86en. sort

Parameter description:

axis: Sort along the direction of the array, 0 for rows, 1 for columns

kind: Sorting algorithm, provides fast sorting, mixed sorting, heap sorting

order: Not the order. I will analyze this later

Effect: sort the array a, then change a

Such as:

>>a.sort(axis=1)
>>print a

1 4
1 3

2, numpy.sort(a,axis=-1,kind='quicksort',order=None)

Usage: numpy.sort(a)

Parameter description:

a: Array to sort, other same as 1

Effect: sort the array a, returning 1 sorted array (same dimension as a), a unchanged

Such as:

>>print numpy.sort(a,axis=1)
1 4
1 3
>>print a
1 4
3 1

3, numpy. argsort (a, axis = 1, kind = 'quicksort', order = None)

Usage: ES138en. argsort(a)

Parameter description: same as 2

Effect: sort the array a, returning 1 sorted index, a unchanged

Such as:

>>print numpy.argsort(a,axis=1)
0 1
1 0

4, data.shape0

Built-in sort function for list, dictionaries, etc

iterable: Iterative type;

cmp: Function for comparison, what to compare is determined by key, with default value, 1 item in iteration set;

key: Use an attribute and function of the list element as the key, with default value, and iterate over 1 item in the collection;

reverse: Collation.reverse=True or reverse=False, default False (from small to large).

Return value: is a sorted iteratable type, like iterable1;

b, for example, is a dictionary

b:

{'a':2,'c':1,'b':3}

Sort b:

>>c=sorted(b.iteritems(),key=operator.itemgetter(1),reverse=False)
>>print c[('c', 1), ('a', 2), ('b', 3)]

You can see: 1 list is returned

conclusion

The above is all about the sorting methods of numpy array in this paper, I hope to help you. Interested friends can continue to refer to other related topics in this site, if there is any deficiency, welcome to comment out. Thank you for your support!