Slicing rows and columns in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does slicing rows and columns mean in a numpy array?

It means selecting specific parts of the array by choosing certain rows and columns using index ranges or lists.

beginner

How do you select the first 3 rows and first 2 columns of a numpy array named arr?

Use arr[:3, :2]. The first part :3 selects rows 0, 1, 2 and :2 selects columns 0 and 1.

intermediate

What does arr[1:4, 2] select from a numpy array?

It selects rows 1, 2, and 3 from column 2, returning a 1D array of those values.

beginner

How can you select all rows but only the last column of a numpy array arr?

Use arr[:, -1]. The colon means all rows, and -1 means the last column.

intermediate

What happens if you use arr[::2, ::3] on a numpy array?

It selects every 2nd row and every 3rd column, starting from the first row and column.

Which numpy slice selects rows 2 to 4 and columns 1 to 3 from array arr?

A arr[1:3, 2:4]

B arr[1:4, 2:5]

C arr[2:5, 1:4]

D arr[2:4, 1:3]

Slicing in numpy includes the start index but excludes the end index. So rows 2 to 4 means 2:5 and columns 1 to 3 means 1:4.

What does arr[:, 0] return?

A Last row, first column

B First row, all columns

C First row, first column

D All rows, first column

The colon means all rows, and 0 means the first column.

How do you select every other row and every other column from arr?

A arr[::2, ::2]

B arr[1::2, 1::2]

C arr[::1, ::1]

D arr[2::2, 2::2]

The step value 2 in slicing means every other element starting from index 0.

What is the shape of the result of arr[1:3, 2:5] if arr has shape (5, 6)?

A (2, 3)

B (2, 4)

C (3, 4)

D (3, 3)

Rows 1 to 2 (1:3) gives 2 rows, columns 2 to 4 (2:5) gives 3 columns, so shape is (2, 3).

Which slice selects the last two rows and all columns from arr?

A arr[:, -2:]

B arr[-2:, :]

C arr[:2, :]

D arr[-1:, :]

Negative indices count from the end. -2: means last two rows, and colon means all columns.

Explain how to slice a numpy array to select specific rows and columns.

Think about how you pick parts of a table by row and column numbers.

Describe what arr[::2, 1:5:2] does on a numpy array.

Focus on the meaning of the double colons and step values.