Question 1

When would you prefer to use t-SNE over PCA for visualizing high-dimensional data?

Options :

A : When you need to capture linear relationships in the data.

B : When computational efficiency is crucial.

C : When you want to visualize clusters or groups in the data.

D : When the dataset has fewer than three features.

Answer: C

Question 2

Your dataset consists of geographical data points for different species of birds. You want to visualize the distribution of these species on a geographical map. Which Python library would be most appropriate for this kind of visualization?

Options :

A : Plotly

B : Geopandas

C : Seaborn

D : Matplotlib

Answer: B

Question 3

You are given a JSON file containing social data about users' interactions on a website. The JSON object includes an array named likes that should contain integers representing the number of likes each post has received. Which of the following Python code snippets would be most appropriate to validate that all elements in the likes array are indeed integers?

Options :

A : import json

data = json.load(open('data.json'))

if len(data['likes']) > 0:

print("Data is valid")

else:

print("Data is invalid")

B : import json

data = json.load(open('data.json'))

if all(isinstance(x, int) for x in data['likes']):

print("Data is valid")

else:

print("Data is invalid")

C : import json

data = json.loads('data.json')

if isinstance(data['likes'], list):

print("Data is valid")

else:

print("Data is invalid")

D : import json

data = json.load(open('data.json'))

if 'likes' in data.keys():

print("Data is valid")

else:

print("Data is invalid")

Answer: B

Question 4

Which of the following methods is least likely to be effective when dealing with outliers in a dataset while using Python's Pandas library?

Options :

A : Imputation

B : Deleting the feature column

C : Capping

D : Transformation

Answer: B

Question 5

In Python, which of the following methods is not a common statistical approach to identify outliers within a dataset?

Options :

A : Interquartile Range (IQR)

B : Z-score

C : Tukey-s Fences

D : Mean Squared Error (MSE)

Answer: D