{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: ☑
{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: ☑
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
need help with Q4
![{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:
☑](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fab56eaca-4a90-4df6-a2b9-f2e00974aeba%2F5306f975-a63e-4d8e-838b-312202006258%2Fyqqwcnb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:{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:
☑
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