Question

Write Python statements for performing the following tasks with a table of a rows and n columns. \- Initialize the table with zeroes. \- Fill all entries with ones. \- Fill elements alternately with zeroes and ones in a checkerboard pattern. \- Fill only the elements in the top and bottom row with zeroes. \- Fill only the elements in the left and right column with ones. \- Compute the sum of all elements. \- Print the table.

Short answer

Initialize and modify a 2D list with loops, and use `print` to display the table.

Step-by-step solution

Initialize the Table with Zeroes

Start by defining a 2D list in Python. Use nested list comprehension to create a table with `a` rows and `n` columns, initialized with zeroes. ```python # Define the size of the table a = 5 # number of rows n = 4 # number of columns # Initialize the table with zeroes table = [[0 for _ in range(n)] for _ in range(a)] ```

Fill the Table with Ones

Modify the table so that all entries are ones. Achieve this by iterating over each row and column, updating values to one. ```python for row in range(a): for col in range(n): table[row][col] = 1 ```

Fill in a Checkerboard Pattern

Create a checkerboard pattern of zeroes and ones. If the sum of row and column indices is even, set the element to zero; otherwise, set it to one. ```python for row in range(a): for col in range(n): if (row + col) % 2 == 0: table[row][col] = 0 else: table[row][col] = 1 ```

Fill Top and Bottom Rows with Zeroes

Update the top (first) and bottom (last) row elements to zeroes. ```python # Fill the top row with zeroes for col in range(n): table[0][col] = 0 # Fill the bottom row with zeroes for col in range(n): table[a-1][col] = 0 ```

Fill Left and Right Columns with Ones

Make sure that all elements in the first (left) and last (right) columns are set to one. ```python for row in range(a): table[row][0] = 1 table[row][n-1] = 1 ```

Compute the Sum of All Elements

Calculate and store the sum of all elements in the table. ```python sum_of_elements = sum(sum(row) for row in table) ```

Print the Table

Finally, print each row of the table for visualization. ```python for row in table: print(row) ```

Key concepts

2D Lists

In Python programming, a 2D list is essentially a list of lists. This allows us to efficiently handle and manipulate tables or grids. Imagine a piece of paper divided into rows and columns. Each cell can hold a data point, similar to how values are stored within a 2D list. Creating a 2D list involves initializing a list where each element is another list.

• Helpful for visualizing data as a matrix
• Allows access to each element using two indices: one for the row and one for the column
• The ability to store complex numbers and data in a structured format

A common use-case includes creating a table with a set number of rows and columns, initializing values for many operations, such as in the example of creating a table with zeroes.

Nested List Comprehension

Nested list comprehension provides a concise and readable way to generate 2D lists in Python. This technique leverages the capabilities of list comprehension by embedding one list comprehension within another.

• Simplifies code by reducing lines substantially
• Facilitates understanding by showcasing the structure of list initialization
• Often faster and more efficient compared to traditional loops

For instance, initializing a table with zeroes, as shown in step 1 of the solution, can be effectively achieved using nested list comprehension. Each sub-list represents a row filled with default values, and the process can handle multiple dimensions efficiently.

Iterative Statements

Iterative statements, or loops, are central to navigating and modifying 2D lists. They allow us to traverse each element in a 2D list systematically and perform actions like updating or calculating values. Common loops used include `for` and `while` loops.
Through iteration, tasks such as filling the table with ones, creating patterns, or computing sums, become manageable. With a dual index (row and column), loops check each position within the table.

• Enables repetitive tasks without manually coding each iteration
• Improves code efficiency and readability
• Supports dynamic changes to data as requirements evolve

Row and Column Manipulation

Row and column manipulation involves accessing and modifying specific areas of a 2D list. Whether altering entire rows or adjusting particular columns, these actions tailor data structure to fit desired operations. For example, replacing values in the top and bottom rows with zeroes or setting outermost columns to ones demonstrates row and column manipulation. This ability to precisely target and alter parts of a table supports flexibility and powerful data handling.

• Direct access to specific traits of a table
• Facilitates complex data operations like edge-specific patterns
• Integral for tasks requiring adjustments to specific segments

Table Operations

Table operations refer to processes that involve computing over the entire 2D list. They include sum calculations, traversing for printing, and more. This makes them an essential part of handling more complex data sets. Calculating the sum of all elements, as shown in the solution, requires iterating through each row and computing totals. Printing each row is essential for visualization and confirming table manipulations.

• Summation is useful for metric calculations or checks
• Printing aids debugging and ensures correct alterations
• Essential for summarizing and presenting the overall state of a data grid