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NumPy: Sorting and Searching Exercises, Practice, Solution

NumPy Sorting and Searching [9 exercises with solution]

[An editor is available at the bottom of the page to write and execute the scripts.]

1. Write a NumPy program to sort a given array of shape 2 along the first axis, last axis and on flattened array. Go to the editor
Expected Output:
Original array:
[[10 40]
[30 20]]
Sort the array along the first axis:
[[10 20]
[30 40]]
Sort the array along the last axis:
[[10 40]
[20 30]]
Sort the flattened array:
[10 20 30 40]
Click me to see the sample solution

2. Write a NumPy program to create a structured array from given student name, height, class and their data types. Now sort the array on height. Go to the editor
Sample Output:
Original array:
[(b'James', 5, 48.5 ) (b'Nail', 6, 52.5 ) (b'Paul', 5, 42.1 )
(b'Pit', 5, 40.11)]
Sort by height
[(b'Pit', 5, 40.11) (b'Paul', 5, 42.1 ) (b'James', 5, 48.5 )
(b'Nail', 6, 52.5 )]
Click me to see the sample solution

3. Write a NumPy program to create a structured array from given student name, height, class and their data types. Now sort by class, then height if class are equal. Go to the editor
Expected Output:
Original array:
[(b'James', 5, 48.5 ) (b'Nail', 6, 52.5 ) (b'Paul', 5, 42.1 ) (b'Pit', 5, 40.11)]
Sort by age, then height if class are equal:
[(b'Pit', 5, 40.11) (b'Paul', 5, 42.1 ) (b'James', 5, 48.5 ) (b'Nail', 6, 52.5 )]
Click me to see the sample solution

4. Write a NumPy program to sort the student id with increasing height of the students from given students id and height. Print the integer indices that describes the sort order by multiple columns and the sorted data. Go to the editor
Expected Output:
Sorted indices:
[4 0 5 3 6 1 2]
Sorted data:
1682 38.0
1023 40.0
5241 40.0
1671 41.0
4532 42.0
5202 42.0
6230 45.0

Click me to see the sample solution

5. Write a NumPy program to get the indices of the sorted elements of a given array. Go to the editor
Expected Output:
Original array:
[1023 5202 6230 1671 1682 5241 4532]
Indices of the sorted elements of a given array:
[0 3 4 6 1 5 2]
Click me to see the sample solution

6. Write a NumPy program to sort a given complex array using the real part first, then the imaginary part. Go to the editor
Note: "busday" default of Monday through Friday being valid days.
Sample Output:
Original array:
[(1+2j), (3-1j), (3-2j), (4-3j), (3+5j)]
Sorted a given complex array using the real part first, then the imaginary part.
[1.+2.j 3.-2.j 3.-1.j 3.+5.j 4.-3.j]
Click me to see the sample solution

7. Write a NumPy program to partition a given array in a specified position and move all the smaller elements values to the left of the partition, and the remaining values to the right, in arbitrary order (based on random choice). Go to the editor
Sample output:
Original array:
[ 70 50 20 30 -11 60 50 40]
After partitioning on 4 the position:
[-11 30 20 40 50 50 60 70]
Click me to see the sample solution

8. Write a NumPy program to sort the specified number of elements from beginning of a given array. Go to the editor
Sample output:
Original array:
[0.39536213 0.11779404 0.32612381 0.16327394 0.98837963 0.25510787 0.01398678 0.15188239 0.12057667 0.67278699]
Sorted first 5 elements:
[0.01398678 0.11779404 0.12057667 0.15188239 0.16327394 0.25510787 0.39536213 0.98837963 0.32612381 0.67278699]
Click me to see the sample solution

9. Write a NumPy program to sort an given array by the nth column. Go to the editor
Original array:
[[1 5 0]
[3 2 5]
[8 7 6]]
Sort the said array by the nth column:
[[3 2 5]
[1 5 0]
[8 7 6]]
Click me to see the sample solution

Python-Numpy Code Editor:

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Python: Tips of the Day

Find the index of an item in a list?

Given a list ["foo", "bar", "baz"] and an item in the list "bar", how do I get its index (1) in Python?

>>> ["foo", "bar", "baz"].index("bar")
1

Caveats follow

Note that while this is perhaps the cleanest way to answer the question as asked, index is a rather weak component of the list API, and I can't remember the last time I used it in anger. It's been pointed out to me in the comments that because this answer is heavily referenced, it should be made more complete. Some caveats about list.index follow. It is probably worth initially taking a look at the documentation for it:

list.index(x[, start[, end]])

Linear time-complexity in list length

An index call checks every element of the list in order, until it finds a match. If your list is long, and you don't know roughly where in the list it occurs, this search could become a bottleneck. In that case, you should consider a different data structure. Note that if you know roughly where to find the match, you can give index a hint. For instance, in this snippet, l.index(999_999, 999_990, 1_000_000) is roughly five orders of magnitude faster than straight l.index(999_999), because the former only has to search 10 entries, while the latter searches a million:

>>> import timeit
>>> timeit.timeit('l.index(999_999)', setup='l = list(range(0, 1_000_000))', number=1000)
9.356267921015387
>>> timeit.timeit('l.index(999_999, 999_990, 1_000_000)', setup='l = list(range(0, 1_000_000))', number=1000)
0.0004404920036904514

Only returns the index of the first match to its argument

A call to index searches through the list in order until it finds a match, and stops there. If you expect to need indices of more matches, you should use a list comprehension, or generator expression.

>>> [1, 1].index(1)
0
>>> [i for i, e in enumerate([1, 2, 1]) if e == 1]
[0, 2]
>>> g = (i for i, e in enumerate([1, 2, 1]) if e == 1)
>>> next(g)
0
>>> next(g)
2

Most places where I once would have used index, I now use a list comprehension or generator expression because they're more generalizable. So if you're considering reaching for index, take a look at these excellent Python features.

Throws if element not present in list

A call to index results in a ValueError if the item's not present.

>>> [1, 1].index(2)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: 2 is not in list

If the item might not be present in the list, you should either

  • Check for it first with item in my_list (clean, readable approach), or
  • Wrap the index call in a try/except block which catches ValueError (probably faster, at least when the list to search is long, and the item is usually present.)

Ref: https://bit.ly/2ALwXwe