# 1.nunpy.sort

Here is a brief introduction of this method on the official website

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

```

## Illustrate with examples

Parameter order

```import numpy as np
>>> dtype = [('Name', 'S10'), ('Height', float), ('Age', int)]
>>> values = [('Li', 1.8, 41), ('Wang', 1.9, 38),('Duan', 1.7, 38)]
>>> a = np.array(values, dtype=dtype)
>>> np.sort(a, order='Height')  # Sort by the attribute Height, and the parameter is a string
array([('Duan', 1.7, 38), ('Li', 1.8, 41),('Wang', 1.9, 38)],
dtype=[('Name', '|S10'), ('Height', '<f8'), ('Age', '<i4')])
>>> np.sort(a, order=['Age', 'Height'])
# Sort by attribute Age first. If Age is equal, then sort by Height. The parameter is list
array([('Duan', 1.7, 38), ('Wang', 1.9, 38),('Li', 1.8, 41)],
dtype=[('Name', '|S10'), ('Height', '<f8'), ('Age', '<i4')])

```

# 2.numpy. argsort

```numpy.argsort(a, axis=1, kind='quicksort', order=None)
Parameters:	a : array_like
Array to sort.
axis : int or None, optional
Axis along which to sort. The default is 1 (the last axis).
If None, the flattened array is used.
kind : {'quicksort', 'mergesort', 'heapsort'}, optional
Sorting algorithm.
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:	index_array : ndarray, int
Array of indices that sort a along the specified axis. If a
is one-dimensional, a[index_array] yields a sorted a.

```

# 3.nupy.lexsort

```numpy.argsort(a, axis=-1, kind='quicksort', order=None)
Parameters:		a : array_like
Array to sort.
axis : int or None, optional
Axis along which to sort. The default is -1 (the last
axis). If None, the flattened array is used.
kind : {'quicksort', 'mergesort', 'heapsort'}, optional
Sorting algorithm.
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:		index_array : ndarray, int
Array of indices that sort a along the specified axis. If
a is one-dimensional, a[index_array] yields a sorted a

```

# 4.numpy.searchsorted

```numpy.searchsorted(a, v, side='left', sorter=None)
Parameters:		a : 1-D array_like
Input array. If sorter is None, then it must be sorted in
ascending order, otherwise sorter must be an array of
indices that sort it.
v : array_like
Values to insert into a.
side : {'left', 'right'}, optional
If 'left', the index of the first suitable location found
is given. If 'right', return the last such index. If
there is no suitable index, return either 0 or N (where N
is the length of a).
sorter : 1-D array_like, optional
Optional array of integer indices that sort array a into
ascending order. They are typically the result of
argsort.
Returns:		indices : array of ints
Array of insertion points with the same shape as v

```

# 5.numpy.partition

```numpy.partition(a, kth, axis=-1, kind='introselect', order=None)
Parameters:		a : array_like
Array to be sorted.
kth : int or sequence of ints
Element index to partition by. The k-th value of the
element will be in its final sorted position and all
smaller elements will be moved before it and all equal or
greater elements behind it. The order all elements in the
partitions is undefined. If provided with a sequence of
k-th it will partition all elements indexed by k-th of
them into their sorted position at once.
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 : {'introselect'}, optional
Selection algorithm. Default is 'introselect'.
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. 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:		partitioned_array : ndarray
Array of the same type and shape as a

```

# 6.numpy.sorted

```sorted(iterable[, cmp[, key[, reverse]]])
The sorted() function sorts all the objects that can be iterated.
The difference between sort and sorted:
Sort is a method applied to list. sorted can sort all objects that can be iterated.
The sort method of list returns to operate on the existing list, while the sorted method of the built-in function returns a
A new list, not an operation based on the original one.
#sorted() can reverse sort with the parameter reverse=True
>>>list=[3,4,2,6,1]
>>>sorted(list)
[1, 2, 3, 4, 6]
>>>sorted(list, reverse=True)
[6, 4, 3, 2, 1]

```
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Keywords: Attribute

Added by Rayne on Tue, 04 Feb 2020 20:30:33 +0200