{x} > Os ✓ Q3: Take the minimum values (numpy function) in each array of q3 and create an array of those values. Assign it to Q3. [8] Q3 = np.min(array2d, axis=1) print (Q3) [0.08846017 0.31306644 0.1107879 0.20012361] ( ) Start coding or generate with AI. Q ▾ Q4: Assign the mean (numpy function) of all the q3 array values to Q4. import numpy as 0.17810953074806235 B ✓ Os completed at 11:30 AM Create an array with the following values: 2, 3, np.nan (this should represent a missing value), and 5. Use a nump of the values in this array. Assign the sum to Q5 (you should expect a numerical value here). <> V Q5: ☑

What does it mean by "entries" in this context? I still do not understand why sorting is not needed. If we sort all the books according to the publisher name, wouldn't it be faster to count how many books are pulished by each publisher? The answer states we need a "counter", but when you go through the entries for each of the keys, don't we need to have 30 counters in total? (each counter is associated with one pulbisher. In other words, when a book pulisher matches with one of the keys, shouldn't it increment the counter variable associated with that pulisher?) Please clarify questions reagrding the answer

You guys are  giving me wrong answer every time. This is last warning Don't try to copy other's content or don't us any AI otherwise I'll definitely give multiple downvotes and will report your account

How would you find the middle number using a red-black BST? Like if you had a set of numbers: 1,5,7,11,19, how could you find and return the middle number 7 using a red-black BST?