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| Section | Objectives |
|---|
| Data Handling and Processing with Python | - Data manipulation libraries
- 1. NumPy basics
- 2. Pandas fundamentals
- Working with data structures
- 1. Iterating and transformations
- 2. Lists, tuples, dictionaries
|
| Data Analysis and Visualization | - Data cleaning and preprocessing
- 1. Missing values handling
- 2. Data transformation techniques
- Data visualization
- 1. Plot interpretation
- 2. Matplotlib basics
|
| Python Programming Fundamentals | - Basic syntax and data types
- 1. Variables and operators
- 2. Control flow basics
|
| Basic Statistics for Data Analysis | - Descriptive statistics
- 1. Variance and standard deviation
- 2. Mean, median, mode
|
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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q34-Q39):
NEW QUESTION # 34
You are writing a function named process_data()to read and process numerical input from a file. The function must:
- read the file data.txt,
- attempt to convert the first line into an integer,
- handle file, conversion, or index-related exceptions,
- print the value only if no error occurs,
- and always print a final message after execution.
Which implementation correctly and robustly meets all these conditions? Select the best answer.
Answer: A
Explanation:
It wraps file reading and integer conversion in a try block, catches the relevant file, conversion, and indexing exceptions, prints the value only in the no-error path using an else block, and uses a finally block to always print the final message.
NEW QUESTION # 35
A health researcher uses wearable devices to record physical activity and sends a survey to randomly selected participants across age groups.
Why can this approach be effective? Select the best answer.
- A. It relies on observational methods, which are more accurate than surveys or sensors.
- B. It limits sampling to one demographic, ensuring high-quality data within a specific group.
- C. It uses unstructured interviews to validate automated tracking, improving bias detection.
- D. It combines automated data collection with representative sampling, reducing the risk of bias.
Answer: D
Explanation:
Combining automated wearable data with a randomly selected survey sample integrates objective measurements with representative participant input, which helps reduce bias and improves the reliability and generalizability of the findings.
NEW QUESTION # 36
You have a list of test scores, where each entry includes a student name and a score. Some students appear more than once. You want to compute the average score for each student and store the results in a dictionary. Here's the partial code block:

Which code correctly replaces the # MISSING CODE comment to calculate the average score for each student? Select the best answer.
Answer: B
Explanation:
It iterates through each record, extracts the name and score, and uses dictionary .get() to accumulate total scores and counts per student safely, initializing missing keys to zero. This correctly enables calculation of each student's average afterward.
NEW QUESTION # 37
Consider a Python program that assigns a string value "5" to a variable and then attempts to multiply it by an integer 3. The programmer expects numeric multiplication. What will actually happen when the code is executed?
Answer: C
Explanation:
In Python, multiplying a string by an integer repeats the string. Therefore, "5" * 3 produces "555", not a numeric result. This behavior differs from arithmetic multiplication and often confuses beginners.
NEW QUESTION # 38
What will be the output of the following code?

- A. 10 10
- B. 5 5
- C. 10 5
- D. 5 10
Answer: B
Explanation:
The function declares the variable as global and assigns it the value 5. When the function is called, it updates the global variable and returns 5, so both the returned value and the global variable printed afterward are 5.
NEW QUESTION # 39
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