Database System Concepts
Database System Concepts
7th Edition
ISBN: 9780078022159
Author: Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher: McGraw-Hill Education
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Python Returning function
function name: is_prime
- parameters: a number n
- returns: True if n is prime
- behavior: Check the values in the range [2, n) and return False if n is divible by any of them.
function name: bound_0_to_100
-
- parameters:a number grade
- returns: the grade with a minimum of 0 and a maximum of 100
- behavior: In addition to exceeding 100, sometimes a grade will be so spectacularly bad that it falls below 0. In that case we want to normalize it to 0 so all grades fall into the range [0, 100]. ex: bound_0_to_100(75) returns 75, bound_0_to_100(103) returns 100, and bound_0_to_100(-5) returns 0
function name: bigger
-
-
- parameters: two values a and b
- returns: whichever of the two is greatest
- behavior: ex: bigger(3, 9) returns 9
-
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- Module main() // Local variables Constant Integer SIZE = 18 Declare Integer numbers[SIZE] = 5658845, 4520125, 7895122, 8777541, 8451277, 1302850, 8080152, 4562555, 5552012, 5050552, 7825877, 1250255, 1005231, 6545231, 3852085, 7576651, 7881200, 4581002 Declare Integer inputNumber, found = 0 // Get number Display "Enter number to validate: " Input inputNumber // Validate number For index = 0 to SIZE – 1 If inputNumber == numbers[index] Then Set found = 1 Set index = SIZE End If End For // Show if valid If found == 1 Then Display "Number is valid." Else Display "Number is not valid." End If End Module Flowchart pleasearrow_forwardpython code Merge following two Python dictionaries into one. dict1 = {'One': 1, 'Eleven': 11, 'Twelve': 12} dict2 = {'Twelve': 12, 'Twenty': 20, 'Thirty': 30} Expected Output: {'One': 1, 'Eleven': 11, 'Twelve': 12, 'Twenty': 20, 'Thirty': 30}arrow_forwardc++ code Screenshot and code is mustarrow_forward
- A(n) on its own but can be used with other software products. _is a small application that cannot runarrow_forwardIn Python, grades_dict = {'Wally': [87,96,70], 'Eva': [100,87,90], 'Sam': [94,77,90], 'Katie': [100,81,82], 'Bob': [83, 65, 85]} write your own describe function that produces thesame 8 statistical results, for each one of the columns, that the built-in describe() function does.Note 1: Use the sample standard deviation formula (that is, the denominator is: N-1)Note 2: Your algorithm should work for any number of columns not just for 5Note 3: You can use the np.percentile() for the 25% and 75% percentile as well as the sort()built-in functionsarrow_forwardPYTHON PLEASE EXPLAIN STEP BY STEPS AND THE OUTPUT School_sum calls the class_sum function: def class_sum(num): return num * 3 def school_sum(m): return class_sum(m) + 3 print(school_sum(5)) print(school_sum(8)) print(school_sum(15)arrow_forward
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