Question 1

When using Python's requests library to collect data from a website through HTTP requests, which status code indicates that the requested resource has been moved permanently?

Options :

A : 403

B : 404

C : 200

D : 301

Answer: D

Question 2

You have a DataFrame with a 'date' column in string format ('YYYY-MM-DD'). How would you convert this column to Pandas datetime format?

Options :

A : df['date'].convert_to('datetime')

B : df['date'].astype('datetime64')

C : df['date'] = df['date'].parse('%Y-%m-%d')

D : pd.to_datetime(df['date'], format='%Y-%m-%d')

Answer: D

Question 3

You are evaluating a logistic regression model using the ROC curve. Which of the following is true regarding the Area Under the Curve (AUC)?

Options :

A : A model with an AUC of 0 performs better than one with an AUC of 1

B : A higher AUC indicates that the model has higher bias

C : A model with an AUC closer to 1 performs better than one closer to 0

D : A model with an AUC of 0.5 is an excellent model

Answer: C

Question 4

You are building a data pipeline that requires you to load data from an API, transform it, and then save it to a database. Which of the following is the best approach to structure your script for maintainability and reusability?

Options :

A : Use global variables to hold the data as it moves through the pipeline.

B : Implement all operations as nested loops inside a main loop.

C : Write the entire workflow in a single function.

D : Separate the loading, transforming, and saving operations into individual functions.

Answer: D

Question 5

While transforming extracted data to fit operational needs, which of the following operations is least likely to be performed?

Options :

A : Data enrichment

B : Data normalization

C : Data archiving

D : Data type conversion

E : Data cleansing

Answer: C

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