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| Section | Objectives |
|---|
| Topic 1: Data Analysis and Visualization | - Data visualization
- 1. Plot interpretation
- 2. Matplotlib basics
- Data cleaning and preprocessing
- 1. Data transformation techniques
- 2. Missing values handling
|
| Topic 2: Basic Statistics for Data Analysis | - Descriptive statistics
- 1. Variance and standard deviation
- 2. Mean, median, mode
|
| Topic 3: 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
|
| Topic 4: Python Programming Fundamentals | - Basic syntax and data types
- 1. Control flow basics
- 2. Variables and operators
|
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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q44-Q49):
NEW QUESTION # 44
You want to safely read the contents of a file named records.txtand store them in a list. Your requirements are:
- The file should be automatically closed after reading,
- The code should check whether the file exists before opening it, and
- It should handle missing file errors gracefully.
Which of the following is the most appropriate way to accomplish this task in Python? Select the best answer.
Answer: A
Explanation:
It uses a context manager to automatically close the file after reading and wraps the operation in a try-except block to gracefully handle a missing file error, assigning an empty list if the file is not found.
NEW QUESTION # 45
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 # 46
A teacher wants to compare the number of students in different school clubs:

Which type of chart would be most appropriate to show this comparison? Select the best answer.
- A. Line chart
- B. Bar chart
- C. Pie chart
- D. Bubble chart
Answer: B
Explanation:
A bar chart is best for comparing quantities across distinct categories, such as the number of students in each club, because it clearly shows differences in counts side by side.
NEW QUESTION # 47
A data analyst exports a cleaned dataset from Python and wants to share it with a colleague for easy use in Excel.
Which file format is best suited for this purpose? Select the best answer.
- A. SQL, because it directly converts tabular data into database tables that Excel can open.
- B. XML, because it automatically preserves spreadsheet formatting and charts.
- C. JSON, because it stores hierarchical data and is designed for visual presentation in Excel.
- D. CSV, because it stores tabular data in plain text and is compatible with spreadsheet applications.
Answer: D
Explanation:
CSV stores tabular data in a simple plain-text, comma-separated format that is widely supported by spreadsheet applications like Excel, making it ideal for sharing datasets for easy import and analysis.
NEW QUESTION # 48
You are reading a data.csvfile line by line. To prepare each line for formatting with f-strings, you need to remove extra whitespace and split the values by commas.
Which line should you insert to correctly clean and parse the input?
- A. fields = line.split().strip(', ')
- B. fields = line.replace(', ', '|').split('|')
- C. fields = line.strip().split(', ')
- D. fields = line.split(', ').trim()
Answer: C
Explanation:
Stripping removes leading and trailing whitespace from the line, and then splitting on the comma- space delimiter correctly separates the values into a list for further formatting.
NEW QUESTION # 49
......
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