The CPU could cycle the bits 2000000000 a second. That means theoretically it could process 16 gigabytes of data a second.
Answer:
Option b is correct
Explanation:
For example, setting user config. Per user on a Microsoft computer
Go to config. Setting in the group management policy
Locate admin template, click group policy and enable the loop back policy.
This policy helps the computer to use set of GPO for users who log on to computers affected by this policy and this application is supported only in environment with active directory.
Ted is most likely to work in New York or France
Answer:
#section 1
def maxTemp(filename):
import pathlib
f = pathlib.Path(filename)
f.exists()
if f.exists():
f = open(filename, "r")
#section 2
next(f)
res = [int(sub.split(',')[1]) for sub in f]
maxdata = (res[0])
for i in range(len(res)-1):
if maxdata < res[i]:
maxdata = res[i]
index = res.index(maxdata)
f.close()
#section 3
li = []
a = open(filename, "r")
for line in a:
line = line.strip()
li.append(line)
a.close()
return (li[index+1])
else:
return -1
print(maxTemp("new.csv"))
Explanation:
#section 1:
The function maxTemp is defined. We import pathlib in other to check if the file exists, if it does we carry on with opening the file and if it doesn't the program returns -1.
#section 2:
We start splitting the sub-lists from the second line i.e <em>next(f)</em>. For each line we take the second index element and convert it to an integer.
<em>res = [int(sub.split(',')[1]) for sub in f]
</em>
The maximum number is gotten by using the if statement to compare all elements in the list. The index of the maximum item in the list is collected.
the file is then closed.
#section 3 :
The file is re-opened and all the lines are striped and passed into a new list and the index recovered from section 2, is used to get the day with the highest temperature and the line is returned.