Answered

Using the Python Numpy module and given the 4x4 array, which line of code slices out the second and third rows?

```python
myArray = numpy.arange(16, dtype=int).reshape(4, 4)
```

A. `myArray[1:3, :]`
B. `myArray[:, 1:3]`
C. `myArray[1:2, :]`
D. `myArray[:, 2:3]`



Answer :

GinnyAnswer
To slice out the second and third rows from the given 4x4 array, you can follow these steps:

1. First, identify the given 4x4 array:

```
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]]
```

2. To slice out the second and third rows, you need to target the indices that correspond to these rows. In Python (using zero-based indexing), the second row corresponds to index 1 and the third row corresponds to index 2.

3. Use slicing to select these rows. In NumPy slicing syntax, you use the colon `:` to indicate the range of indices you want to select. The notation `1:3` means: start at index 1 (inclusive) and go up to index 3 (exclusive).

4. The full line of code to achieve this slicing is:

```python
sliced_array = myArray[1:3, :]
```

Here, `1:3` specifies the rows you want (second and third), and `:` indicates that you want all columns.

The resulting sliced array will be:

```
[[ 4 5 6 7]
[ 8 9 10 11]]
```

This new array contains only the second and third rows of the original 4x4 array.

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