Answer:
Explanation:
The following code is written in Python. It asks the user for an input. Then cleans the input using regex to remove all commas, whitespace, and apostrophes as well as making it all lowercase. Then it reverses the phrase and saves it to a variable called reverse. Finally, it compares the two versions of the phrase, if they are equal it prints out that it is a palindrome, otherwise it prints that it is not a palindrome. The test case output can be seen in the attached picture below.
import re
phrase = input("Enter word or phrase: ")
phrase = re.sub("[,'\s]", '', phrase).lower()
reverse = phrase[::-1]
if phrase == reverse:
print("This word/phrase is a palindrome")
else:
print("This word/phrase is NOT a palindrome")
A already assigned variable cannot be assigned twice You can make the variable change over to a new one or call a whole new one to assign one without a value or It might be possible to do v=n (v is variable and n is number / value)
Answer:
i dont really like music so sorry i cant help i hope someone can help you with this.
Answer:
The given statement is False.
Explanation:
- Needs Met Rating of a result show us that how much the result is fulfilling the query of the user. The greater the needs met rating is, the greater the satisfaction of the user is.
- If a page has high quality then it can or can not be useful for the user.
- If the page has high quality as well as high needs met rating then it is best for the user.
- If the page has high quality and has low needs met rating that means it is not relevant to the query so not useful for the user.
- Thus, it is concluded that high quality pages in a task shouldn't all get the same needs met rating rating rather need met rating is dependent upon the relevancy and usefulness of the result to the need and query of the user.
Answer:
import numpy as np
def sample_median(n, P):
return np.median( np.random.choice ( np.arange (1, len(P) + 1 ), n, p = P ) )
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(5, [0.3,0.7])
print(sample_median(5, [0.3,0.7])
Explanation:
- Bring in the numpy library to use the median function provided by the numpy library.
- Define the sample_median function that takes in 2 parameters and returns the median with the help of built-in random, choice and arrange functions.
- Call the sample_median function by providing some values to test and then display the results.
Output:
4.5
4.0
2.0
1.0
