Answer:
previousAddition instance variable
Explanation:
In order to accomplish this you would need to add a previousAddition instance variable. In this variable you would need to save the amount that was added at the end of the process. Therefore, if a mistake were to occur you can simply call the previousAddition variable which would have that amount and subtract it from the total. This would quickly reverse the mistake, and can be easily called from the undo() method.
Trojans, normal viruses, etc. Anything can and could hop on to the files you send depending on the websites and if you don't have a firewall.
Answer:
By reference ; by value
Explanation:
An array is defined as the arrangement of a certain item in a well orderly manner/ fashion.
Unless otherwise specified, entire arrays are usually passed by reference and individual array elements are passed by value which is the standard norm in the mode of operations.
To ensure that multiple backups of the server are available for restores you should Modify the frequency of the scheduled backup.
a. Modify the frequency of the scheduled backup.
<u>Explanation:</u>
To backup system normal and good practices schedule every day either different folder, which is further classified day of a week name. For example Sunday, Monday, Tuesday Wednesday, Thursday, Friday Saturday backup schedule will once a week.
Suppose Monday backup schedule run once a week at midnight of every Monday, same away Tuesday backup schedule run once a week at midnight of every Tuesday. If we schedule weekly one day folder end user will have 6 last days folder so that end user can restore the data any point of time.
Answer:
import pandas as pd
filename = input("Enter file name with the extension included: ")
data = {}
with open("filename", "r") as file:
content = file.readlines()
for line in content:
line_list = line.strip().split(" ")
data[line_list[0]] = line_list[1] * line_list[2]
del line_list
report = pd.DataFrame(list(data.items()), columns = ["lastname", "wages paid"])
print(report)
Explanation:
The python module prompts the user for the file name and opens the text file to extract the employee data with the python open function. It iterates over the file content and saves the last name and the wages paid to the employees ( the hours worked multiplied by the hourly rate) in the dictionary "data".
The dictionary is converted to a dataframe with the Pandas python package and displays the data in tabular format on the screen.
