<h3>Sorting</h3>
The term “sorting” is used to refer to the process of arranging the data in <u>ascending or descending order</u>.
Example: Statistical data collected can be sorted alphabetically or numerically based on the value of the data.
<h3>Filtering</h3>
The process of data filtering involves selecting a <u>smaller part of your data set to view or analyze</u>. This is done by using that subset to view or analyze your data set as a whole.
Example: A complete set of data is kept, but only a portion of that set is used in the calculation, so the whole set is not used.
<em>Hope this helps :)</em>
The OS shell allows access to the operating system services
Answer:
Option A is correct.
Explanation:
A janitor that collects data through reviewing reports on a business counsel's desk could be a tippee for insider trading activities.
Probably, the justification for insider trading remains wrong being that it offers each insider the undue benefit on and around the marketplace, gets the insider's preferences beyond them for which they assume the trustee responsibility, as well as enables the insider to unfairly manipulate the cost of the inventory of a business.
So, the following are the reason the other options are not correct according to the given scenario.
Answer:
See explaination for the code
Explanation:
def wordsOfFrequency(words, freq):
d = {}
res = []
for i in range(len(words)):
if(words[i].lower() in d):
d[words[i].lower()] = d[words[i].lower()] + 1
else:
d[words[i].lower()] = 1
for word in words:
if d[word.lower()]==freq:
res.append(word)
return res
Note:
First a dictionary is created to keep the count of the lowercase form of each word.
Then, using another for loop, each word count is matched with the freq, if it matches, the word is appended to the result list res.
Finally the res list is appended.