Sorting along axes in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does sorting along an axis mean in a NumPy array?

Sorting along an axis means arranging the elements in order (usually ascending) along a specific dimension (row or column) of a NumPy array, without changing the other dimensions.

beginner

How do you sort a 2D NumPy array along rows?

Use np.sort(array, axis=1). This sorts each row independently, arranging elements in ascending order within each row.

intermediate

What is the default axis used by np.sort() if none is specified?

The default axis is -1, which means sorting is done along the last axis of the array.

intermediate

How does sorting along axis=0 differ from axis=1 in a 2D array?

Sorting along axis=0 sorts each column independently (top to bottom), while axis=1 sorts each row independently (left to right).

advanced

Can you sort a 3D NumPy array along a specific axis? How?

Yes. Use np.sort(array, axis=n) where n is 0, 1, or 2. This sorts elements along that axis while keeping other axes intact.

What does np.sort(arr, axis=0) do on a 2D array?

A Sorts each row independently

B Sorts each column independently

C Sorts the entire array as a flat list

D Does not sort anything

Sorting with axis=0 sorts elements down each column independently.

If you want to sort each row of a 2D array, which axis should you use?

A axis=0

B axis=None

C axis=-1

D axis=1

axis=1 sorts along rows, sorting elements within each row.

What is the default axis for np.sort() if you don't specify it?

A axis=0

B axis=1

C axis=-1 (last axis)

D axis=None (flattened)

By default, np.sort sorts along the last axis (axis=-1).

Which function would you use to sort a NumPy array in-place along an axis?

A array.sort()

B np.argsort()

C np.sorted()

D np.sort()

array.sort() sorts the array in-place along the specified axis.

Sorting a 3D array along axis=2 means sorting along which dimension?

A The third dimension

B The second dimension

C The first dimension

D The flattened array

Axis=2 refers to the third dimension in a 3D array.

Explain how sorting along different axes affects a 2D NumPy array.

Think about rows vs columns and how sorting changes their order.

Describe how to sort a 3D NumPy array along a specific axis and why this might be useful.

Consider how multi-dimensional data can be organized slice by slice.

Practice

1. What does the axis parameter control in numpy.sort?

easy

A. It decides whether to sort rows or columns in an array.

B. It sets the sorting algorithm type.

C. It changes the data type of the array before sorting.

D. It specifies the order of sorting (ascending or descending).

Solution

1. Step 1: Understand the role of axis in sorting

   The axis parameter tells numpy which direction to sort: 0 means sort each column, 1 means sort each row.

2. Step 2: Differentiate from other parameters

   Sorting algorithm type and order are controlled by other parameters, not axis.

3. Final Answer:

   It decides whether to sort rows or columns in an array. -> Option A

4. Quick Check:

   axis controls direction = A [OK]

Hint: Remember axis=0 sorts columns, axis=1 sorts rows [OK]

Common Mistakes:

• Confusing axis with sorting order
• Thinking axis changes data type
• Assuming axis sets sorting algorithm

2. Which of the following is the correct syntax to sort a 2D numpy array arr along rows?

easy

A. numpy.sort(arr, axis=0)

B. numpy.sort(arr, axis=None)

C. numpy.sort(arr, axis=1)

D. numpy.sort(arr, axis=2)

Solution

1. Step 1: Identify axis for sorting rows

   In a 2D array, axis=1 means sorting each row individually.

2. Step 2: Check other options for validity

   Axis=0 sorts columns, axis=None flattens the array into 1D before sorting, axis=2 is invalid for 2D arrays.

3. Final Answer:

   numpy.sort(arr, axis=1) -> Option C

4. Quick Check:

   axis=1 sorts rows = B [OK]

Hint: Use axis=1 to sort rows in 2D arrays [OK]

Common Mistakes:

• Using axis=0 to sort rows
• Using invalid axis like 2 for 2D arrays
• Using axis=None which flattens the array

3. What is the output of the following code?

import numpy as np
arr = np.array([[3, 1, 2], [6, 4, 5]])
sorted_arr = np.sort(arr, axis=0)
print(sorted_arr)

medium

A. [[1 2 3]
[4 5 6]]

B. [[3 1 2]
[6 4 5]] sorted by columns

C. [[3 1 2]
[6 4 5]] (unchanged)

D. [[3 1 2]
[6 4 5]]

Solution

1. Step 1: Understand sorting along axis=0

   Sorting with axis=0 sorts each column independently in ascending order.

2. Step 2: Sort each column of the array

   Columns: [3,6] -> [3,6], [1,4] -> [1,4], [2,5] -> [2,5]. Since columns are already sorted, array remains the same.

3. Final Answer:

   [[3 1 2] [6 4 5]] sorted by columns -> Option B

4. Quick Check:

   axis=0 sorts columns = A [OK]

Hint: axis=0 sorts columns top to bottom [OK]

Common Mistakes:

• Assuming sorting rearranges rows
• Confusing axis=0 with axis=1
• Expecting full array sort instead of column-wise

4. The code below throws an error. What is the problem?

import numpy as np
arr = np.array([[1, 3], [2, 4]])
sorted_arr = np.sort(arr, axis=2)
print(sorted_arr)

medium

A. Axis 2 does not exist for a 2D array.

B. The array contains non-numeric data.

C. The sort function requires axis to be None.

D. The array must be 1D to sort.

Solution

1. Step 1: Check array dimensions

   The array is 2D with shape (2,2), so valid axes are 0 and 1 only.

2. Step 2: Validate axis parameter

   Using axis=2 is invalid and causes an IndexError because axis 2 does not exist.

3. Final Answer:

   Axis 2 does not exist for a 2D array. -> Option A

4. Quick Check:

   Axis must be within array dimensions = C [OK]

Hint: Axis must be less than array dimensions [OK]

Common Mistakes:

• Using axis out of range
• Assuming sort only works on 1D arrays
• Confusing axis with array shape

5. Given a 3D numpy array arr with shape (2, 2, 3), how would you sort the array along the last axis for each 2D slice?

hard

A. np.sort(arr, axis=-2)

B. np.sort(arr, axis=1)

C. np.sort(arr, axis=0)

D. np.sort(arr, axis=2)

Solution

1. Step 1: Identify the last axis in a 3D array

   For shape (2, 2, 3), axes are 0, 1, 2. The last axis is 2.

2. Step 2: Use axis=2 to sort along the last axis

   Sorting with axis=2 sorts each 2D slice along the last dimension (length 3).

3. Final Answer:

   np.sort(arr, axis=2) -> Option D

4. Quick Check:

   Last axis is 2, so axis=2 sorts last dimension [OK]

Hint: Use axis=-1 or axis=2 for last axis in 3D arrays [OK]

Common Mistakes:

• Using axis=0 or 1 instead of last axis
• Confusing negative axis indexing
• Not matching axis to array shape