DATA STRUCTURES AND ALGORITHMS SESSION 3 PPT.pptx

Arrays – 1D & 2D, Sparse Matrix, Transposed Matrix, Magic Square

1. Arrays – 1D & 2D, Sparse Matrix, Transposed Matrix, Magic Square

2. Where do we use grids or tables in real life?

3. What happens when most of the table is empty?

4. Brief overview of array use in programming and how they represent tabular data efficiently.

5. 1. What is a one-dimensional array? A. A list of rows and columns B. A single list of elements C. A list of dictionaries D. A tree structure

6. 2. Which of the following is a valid way to access the second element in a list? A. list(2) B. list[2] C. list[1] D. list.2

7. 3. What is a sparse matrix? A. A matrix with only string values B. A matrix with many zero values C. A matrix with no rows D. A matrix that is sorted

8. 4. What does transposing a matrix mean? A. Reversing elements B. Removing all zero values C. Switching rows with columns D. Adding all rows together

9. 5. A magic square has... A. Same numbers in each row B. Equal sum of all rows, columns, and diagonals C. All elements being prime D. A random arrangement of values

10. One-Dimensional Arrays  Define 1D array in Python.  Create, access, update, and iterate using loops.

11. Two-Dimensional Arrays  Introduction to 2D arrays using nested lists.  Access rows/columns, update elements.

12. Sparse Matrix  Define sparse matrix.  Introduce dictionary representation of non-zero elements.

13. Transposed Matrix  Explain how rows become columns.

14. Magic Squares  Define magic square (sums of all rows, columns, diagonals equal).  Simple check for 3x3 magic square.