Free Python Institute PCED-30-01 Practice Exam Questions and Answers 2026

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Total 382 Questions | Updated On: Apr 03, 2026

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Question 1

You are developing a web application with Flask and need to collect user-generated data through web forms. What is the most appropriate way to securely collect this data in Python?

A : Use Python-s input() function to collect data from users.

B : Use Flask-s request.form and sanitize the inputs before storing them.

C : Use JavaScript to collect the form data and send it to Python using cookies.

D : Directly insert form data into a SQL database without modification.

Answer: B

Question 2

When using Python to collect data from an API, which of the following statements about OAuth (Open Authorization) is true?

A : OAuth is only used for basic username and password authentication.

B : OAuth is a protocol used to convert JSON data to XML data.

C : OAuth encrypts the data payload for each API request.

D : OAuth allows users to approve applications to act on their behalf without sharing their password.

Answer: D

Question 3

Suppose you have a DataFrame df with columns Name, Age, Gender, and Salary. Which of the following code snippets will filter the DataFrame to include only rows where Age is more than 25 and Salary is less than 50000, and also sort the resulting DataFrame by Name?

A : df[(df['Age'] > 25) & (df['Salary'] < 50000)].sort_values('Name')

B : df.query('Age > 25 and Salary < 50000').sort('Name')

C : df.sort_values('Name').where(df['Age'] > 25 & df['Salary'] < 50000)

D : df.filter('Age' > 25 & 'Salary' < 50000).sort_values(by='Name')

Answer: A

Question 4

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 5

You are working with a dataset that has a mix of numerical and textual data. Your job is to synthesize this information into a more digestible form. What technique could you use to handle both types of data effectively for downstream analysis?

A : Run a Principal Component Analysis (PCA) on the entire dataset.

B : Implement a Decision Tree algorithm to identify the most important features.

C : Use k-Nearest Neighbors (k-NN) to classify data points.

D : Utilize Natural Language Processing (NLP) for textual data and Min-Max scaling for numerical data.

Answer: D

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Total 382 Questions | Updated On: Apr 03, 2026

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