python: numpy def purchases(transactions):     """     QUESTION 7     - A high-end store is trying to evaluate the total amount that customer's spend per transaction. They       want customers to spend anywhere between $130 and $150 on average.     - You need to determine whether the average number spent on each transaction per month is above, between, or       below the desired amount.     - Transactions is a numpy array containing a date, total amount earned each month, and total       number of transactions each month.     - Above: month's average amount spent per transaction > 150     - Within Range: 150 >= month's average amount spent per transaction >= 130     - Below: month's average amount spent per transaction < 130     - Return a numpy array with "Above", "Within Range" and "Below" for the average amount spent per transaction per month     - THIS MUST BE DONE IN ONE LINE     HINT: use np.where() and convert the type of each column to float     Args:         transactions (np.array)     Returns:         np.array     >> transactions = np.array([['01-31-2022', 5462101, 24752],         ['02-28-2022', 7081547.30, 34615],         ['03-31-2022', 3287654.57, 16588],         ['04-30-2022', 8725851.81, 45621],         ['05-31-2022', 6730748.72, 26741],         ['06-30-2022', 9562745.43, 76436],         ['07-31-2022', 8641735.21, 61448],         ['08-31-2022', 7641748.57, 52846],         ['09-30-2022', 7645277.02, 65457],         ['10-31-2022', 9416274.67, 65109],         ['11-30-2022', 9841378.97, 57254],         ['12-31-2022', 10654298.18, 98651]])     >> purchases(transactions)         ['Above' 'Above' 'Above' 'Above' 'Above' 'Below' 'Within Range'         'Within Range' 'Below' 'Within Range' 'Above' 'Below']         """         # transactions = np.array([['01-31-2022', 5462101, 24752],     #             ['02-28-2022', 7081547.30, 34615],     #             ['03-31-2022', 3287654.57, 16588],     #             ['04-30-2022', 8725851.81, 45621],     #             ['05-31-2022', 6730748.72, 26741],     #             ['06-30-2022', 9562745.43, 76436],     #             ['07-31-2022', 8641735.21, 61448],     #             ['08-31-2022', 7641748.57, 52846],     #             ['09-30-2022', 7645277.02, 65457],     #             ['10-31-2022', 9416274.67, 65109],     #             ['11-30-2022', 9841378.97, 57254],     #             ['12-31-2022', 10654298.18, 98651]])     # print(purchases(transactions))

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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python: numpy

def purchases(transactions):
    """
    QUESTION 7
    - A high-end store is trying to evaluate the total amount that customer's spend per transaction. They
      want customers to spend anywhere between $130 and $150 on average.
    - You need to determine whether the average number spent on each transaction per month is above, between, or
      below the desired amount.
    - Transactions is a numpy array containing a date, total amount earned each month, and total
      number of transactions each month.
    - Above: month's average amount spent per transaction > 150
    - Within Range: 150 >= month's average amount spent per transaction >= 130
    - Below: month's average amount spent per transaction < 130
    - Return a numpy array with "Above", "Within Range" and "Below" for the average amount spent per transaction per month
    - THIS MUST BE DONE IN ONE LINE
    HINT: use np.where() and convert the type of each column to float

    Args:
        transactions (np.array)
    Returns:
        np.array

    >> transactions = np.array([['01-31-2022', 5462101, 24752],
        ['02-28-2022', 7081547.30, 34615],
        ['03-31-2022', 3287654.57, 16588],
        ['04-30-2022', 8725851.81, 45621],
        ['05-31-2022', 6730748.72, 26741],
        ['06-30-2022', 9562745.43, 76436],
        ['07-31-2022', 8641735.21, 61448],
        ['08-31-2022', 7641748.57, 52846],
        ['09-30-2022', 7645277.02, 65457],
        ['10-31-2022', 9416274.67, 65109],
        ['11-30-2022', 9841378.97, 57254],
        ['12-31-2022', 10654298.18, 98651]])

    >> purchases(transactions)
        ['Above' 'Above' 'Above' 'Above' 'Above' 'Below' 'Within Range'
        'Within Range' 'Below' 'Within Range' 'Above' 'Below']

        """
        # transactions = np.array([['01-31-2022', 5462101, 24752],
    #             ['02-28-2022', 7081547.30, 34615],
    #             ['03-31-2022', 3287654.57, 16588],
    #             ['04-30-2022', 8725851.81, 45621],
    #             ['05-31-2022', 6730748.72, 26741],
    #             ['06-30-2022', 9562745.43, 76436],
    #             ['07-31-2022', 8641735.21, 61448],
    #             ['08-31-2022', 7641748.57, 52846],
    #             ['09-30-2022', 7645277.02, 65457],
    #             ['10-31-2022', 9416274.67, 65109],
    #             ['11-30-2022', 9841378.97, 57254],
    #             ['12-31-2022', 10654298.18, 98651]])
    # print(purchases(transactions))

Expert Solution
Algorithm
  1. Define a function "purchases" that takes in a numpy array "transactions" as input.
  2. Use np.where() to determine whether the average amount spent per transaction per month is "Above", "Within Range", or "Below".
  3. Convert the columns of the numpy array "transactions" to float using the astype() method.
  4. Calculate the average amount spent per transaction per month by dividing the total amount earned each month by the total number of transactions each month.
  5. Use np.where() to determine whether the average amount spent per transaction per month is "Above", "Within Range", or "Below" based on the desired range of $130 to $150.
  6. Return a numpy array with the results.
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