Free Python Institute PCED Exam Questions

Become Python Institute Certified with updated PCED exam questions and correct answers

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Total 382 Questions | Updated On: Feb 11, 2026

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Question 1

Which of the following libraries in Python is not commonly used for web scraping to collect data?

A : Scrapy

B : Selenium

C : Pandas

D : BeautifulSoup

Answer: C

Question 2

You are implementing an ETL pipeline to fetch data from a JSON-based API and load it into a data lake. The API provides a pagination feature that shows 100 records per page. Which of the following Python libraries is most suitable for performing HTTP requests to extract data from this API?

A : requests

B : os

C : numpy

D : pandas

Answer: A

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?

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

You are a data analyst who needs to collect large volumes of data from a RESTful API that has pagination implemented. Which Python code snippet would be the most effective way to gather all the available data?

A : import requests page = 1while True: response = requests.get(f"https://api.example.com/data?page={page}") if response.status_code != 200: break data = response.json() # Process data page += 1

B : import requests response = requests.get("https://api.example.com/data")data = response.json()

C : import requests pages = [1, 2, 3, 4, 5]for page in pages: response = requests.get(f"https://api.example.com/data?page={page}") data = response.json() # Process data

D : import requests for page in range(1, 100): response = requests.get(f"https://api.example.com/data?page={page}") data = response.json() # Process data

Answer: A

Question 5

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?

A : np.reshape()

B : np.apply_along_axis()

C : np.ravel()

D : np.vectorize()

Answer: D

Page: 1 / 77

Total 382 Questions | Updated On: Feb 11, 2026

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