Sure, here is a step-by-step solution to the problem:

1. Define the function `square_matrix_simple` that takes a matrix as input.
2. Create an empty list called `result_matrix` to store the squared values.
3. Iterate over each row in the matrix using a for loop.
4. Inside the loop, create an empty list called `row_result` to store the squared values of the current row.
5. Iterate over each element in the current row using another for loop.
6. Square the current element by multiplying it with itself and append the squared value to `row_result`.
7. After iterating over all elements in the row, append `row_result` to `result_matrix`.
8. After iterating over all rows in the matrix, return `result_matrix`.

Here is the code implementation:

```python
def square_matrix_simple(matrix):
result_matrix = []
for row in matrix:
row_result = []
for element in row:
squared_value = element ** 2
row_result.append(squared_value)
result_matrix.append(row_result)
return result_matrix
```

This function takes a matrix as input and returns a new matrix with the same size, where each value is the square of the corresponding value in the input matrix. The initial matrix is not modified, and no external modules are used.

Question

Sure, here is a step-by-step solution to the problem:

1. Define the function `square_matrix_simple` that takes a matrix as input.
2. Create an empty list called `result_matrix` to store the squared values.
3. Iterate over each row in the matrix using a for loop.
4. Inside the loop, create an empty list called `row_result` to store the squared values of the current row.
5. Iterate over each element in the current row using another for loop.
6. Square the current element by multiplying it with itself and append the squared value to `row_result`.
7. After iterating over all elements in the row, append `row_result` to `result_matrix`.
8. After iterating over all rows in the matrix, return `result_matrix`.

Here is the code implementation:

```python
def square_matrix_simple(matrix):
    result_matrix = []
    for row in matrix:
        row_result = []
        for element in row:
            squared_value = element ** 2
            row_result.append(squared_value)
        result_matrix.append(row_result)
    return result_matrix
```

This function takes a matrix as input and returns a new matrix with the same size, where each value is the square of the corresponding value in the input matrix. The initial matrix is not modified, and no external modules are used.

Knowee AI · Accepted Answer

Sure, here is a step-by-step solution to the problem:

1. Define the function `square_matrix_simple` that takes a matrix as input.
2. Create an empty list called `result_matrix` to store the squared values.
3. Iterate over each row in the matrix using a for loop.
4. Inside the loop, create an empty list called `row_result` to store the squared values of the current row.
5. Iterate over each element in the current row using another for loop.
6. Square the current element by multiplying it with itself and append the squared value to `row_result`.
7. After iterating over all elements in the row, append `row_result` to `result_matrix`.
8. After iterating over all rows in the matrix, return `result_matrix`.

Here is the code implementation:

```python
def square_matrix_simple(matrix):
    result_matrix = []
    for row in matrix:
        row_result = []
        for element in row:
            squared_value = element ** 2
            row_result.append(squared_value)
        result_matrix.append(row_result)
    return result_matrix
```

This function takes a matrix as input and returns a new matrix with the same size, where each value is the square of the corresponding value in the input matrix. The initial matrix is not modified, and no external modules are used.

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