Introduction to Python for Data Science Flashcards
7 cards from real Data Science with Python Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Introduction to Python for Data Science flashcards as text
What command will enable you to obtain a stack trace while using the interactive Python debugger?
Answer: Where
Explanation: The command at the interactive Python debugger prompt that helps you in getting a stack trace while debugging a Python program is where or w.
Choosing the incorrect command to create and reshape a 60-integer array when the NumPy package has been imported as an object with the name np
Answer: myArray=np.arrange(60).reshape(8,7)
Explanation: The command myArray = np.arrange(60).reshape(8,7) is not a valid command for creating and reshaping a 60-integer array using NumPy.
Which activity does not fall under the data science lifecycle's Dissemination phase?
Answer: Creating and managing analysis scripts
Explanation: Creating and managing analysis scripts is not typically included in the Dissemination phase of the data science lifecycle.
What kind of data can be used to satisfy the needs of an application that has datasets that are not suited for an RDBMS yet require order and hierarchy
Answer: Semi-structured
Explanation: Semi-structured data is suitable to address the requirement for an application having datasets that are not suitable for a Relational Database Management System (RDBMS) but still require order and hierarchy.
What does Python's "capture" cell magic command not support?
Answer: It cannot be used to capture graphical cell output
Explanation: The statement "It cannot be used to capture graphical cell output" is invalid regarding the "capture" cell magic command in Python.
What does the Jupyter Notebook application not apply to?
Answer: Cell may only be run one at a time
Explanation: The statement "Cell may only be run one at a time" is not applicable to the Jupyter Notebook application.
What qualifies as not a property of an ndarray object?
Answer: length
A NumPy ndarray exposes attributes like shape, dtype, ndim, and size, but there is no 'length' attribute. To get the number of elements you use .size, and len() returns only the first-axis length — neither is a property called 'length'. So 'length' is the one that is not a valid ndarray attribute.
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