Why might you choose a numpy array or pandas series over a list for handling large datasets?
EDA Python - 08-2Lists_2

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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Numpy arrays and pandas series are more efficient for large datasets.
Lists are immutable, making them safer for data analysis.
Numpy arrays and pandas series are easier to understand.
Lists are faster for large datasets.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What error might occur if you try to use a variable that hasn't been defined in Python?
IndexError
TypeError
SyntaxError
NameError
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How can you find the index of a specific value in a list?
Using the max() function
Using the min() function
Using the count() method
Using the index() method
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the significance of memory addresses when copying lists in Python?
They help in sorting lists.
They determine the speed of list operations.
They show if two lists point to the same memory location.
They indicate whether two lists are identical.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it important to create a copy of a list before performing data analysis?
To reduce memory usage.
To prevent changes to the original data.
To increase the speed of analysis.
To make the list immutable.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does the zip function do when applied to two lists?
It reverses the lists.
It sorts the lists.
It combines corresponding elements into pairs.
It adds the elements of the lists.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the plus operator affect two lists in Python?
It adds the numerical values of the lists.
It multiplies the elements of the lists.
It appends the second list to the first.
It subtracts the elements of the second list from the first.
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