Programmer Analyst Trainee

Step 1: I began by understanding the requirement — to fetch the first and last names of users whose first name begins with the letter 'K'.

Step 2: I identified the relevant table and columns involved (first_name, last_name).

Step 3: I used the LIKE operator with 'K%' to filter names starting with 'K', which is efficient for pattern matching in SQL.

Step 4: I then wrote the SELECT query using the condition and tested it. The output was as expected, and the interviewer was satisfied with the use of pattern-based filtering.

Step 1: I identified the two necessary data tables: operators and transactions, which are linked through the common field Operator_ID.

Step 2: I performed an INNER JOIN between these tables to merge their records based on matching Operator_ID values.

Step 3: I filtered the results to include only those operators whose performance score was 4.5 or higher.

Step 4: I excluded any transactions marked as "Failed" by adding a condition to omit those statuses.

Step 5: Finally, I selected the required attributes — registration ID, vehicle code, performance score, and transaction ID. Upon execution, the query returned the expected results, confirming the correctness of both the filtering and join logic.

Step 1: I began by checking if the input string input1 is empty. If it is, there are no possible mappings, so the function returns 0.

Step 2: I initialized a counter variable count to keep track of the total number of valid single-digit and two-digit mappings.

Step 3: I iterated over each character in the string to count valid single-digit mappings.
A digit from '1' to '9' corresponds to a valid alphabet character (A to I), so for each such character, I incremented count by 1.

Step 4: I then used a loop to extract every possible two-digit substring from the input.
For each pair of consecutive digits, I converted the substring to an integer and checked whether its value lies between 10 and 26 (inclusive), as these map to valid letters (J to Z).
If the condition was satisfied, I incremented count by 1.

Step 5: Finally, I returned the total count of valid single-digit and two-digit combinations.

Step 1: Initialize two variables:

max_level to track the highest excitement level achieved (start at 0)

min_level to track the lowest excitement level achieved (start at 0)
Also, initialize current_level to 0 to track the excitement level as we process the array.

Step 2: Iterate through each integer num in the array B.

Step 3: For each num, check if it lies within the interval [X, Y].

If X <= num <= Y, increase current_level by 1.

Otherwise, decrease current_level by 1.

Step 4: After updating current_level, update max_level and min_level if current_level is higher than max_level or lower than min_level, respectively.

Step 5: After processing all numbers, the values in max_level and min_level represent the maximum and minimum excitement levels Alex experienced.

Step 6: Return the result as a string "max_level min_level".

Step 1: Understand that Python provides a built-in function max() that returns the larger of two values.

Step 2: Use max(a, b), where a and b are the two input numbers.

Step 3: This expression returns the greater value in a single line.

Step 1: Identify that the inner query will calculate the average salary per department.

Step 2: The outer query selects employee names where their salary exceeds their department's average.

Step 3: Use a nested query in the WHERE clause to compare each employee's salary with the department average.

Step 1: Know that Python strings support slicing.

Step 2: Use slicing with [::-1] to reverse the string.

Step 3: This returns the reversed string in one line.