Question 1

You are pulling data from various databases using Python to compile a large dataset for analysis. How would you ensure the data’s accuracy and reliability?

Options :

A : Use the most recent data available in all databases.

B : Write the Python script in a way that it runs faster to save computational resources.

C : Compare a random subset of data with source records to validate accuracy.

D : Perform exploratory data analysis (EDA) only after data cleaning is done.

Answer: C

Question 2

Which of the following NumPy methods would you use to apply a function element-wise on a 1-D array, while maintaining the shape of the original array?

Options :

A : np.reshape()

B : np.apply_along_axis()

C : np.ravel()

D : np.vectorize()

Answer: D

Question 3

Which of the following techniques should be avoided to ensure that your Python data scripting code is easily understandable and follows best practices?

Options :

A : Using descriptive variable names

B : Refactoring repetitive code into reusable functions

C : Documenting functions with docstrings

D : Using single-letter variable names for main variables

Answer: D

Question 4

You have developed a logistic regression model for a classification task. After training, you notice that both the training and validation errors are high. Which of the following might be the problem with your model?

Options :

A : The learning rate is too high.

B : The model is overfitting the data.

C : The model is too complex.

D : The model is underfitting the data.

Answer: D

Question 5

You are working on a project that requires real-time data collection from a WebSocket API. Which of the following Python libraries would be most appropriate for this task?

Options :

A : csv

B : websocket-client

C : urllib

D : scrapy

Answer: B

Higher Test Marks with Free Online PCED Exam Practice

Buying Options: