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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Working with Data Using Python Libraries | 30% | - Pandas Library
|
| Python Programming for Data Analysis | 30% | - File Operations
|
| Data Analysis Fundamentals | 20% | - Introduction to Data Analysis
|
| Applied Data Analysis Projects | 20% | - Exploratory Data Analysis (EDA)
|
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
1. What is the main reason to remove duplicate records before performing analysis?
A) It helps increase sample size
B) It reduces redundancy that can skew statistical metrics
C) It ensures training data is intentionally overfitted
D) It avoids converting data to JSON format
2. Which SQL clause is most appropriate when you need to filter records that meet a specific condition during data retrieval in an analytics pipeline?
A) GROUP BY
B) ORDER BY
C) HAVING
D) WHERE
3. What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?
A) Parquet stores data in plain text, making it human-readable
B) Parquet files can only be used with Excel
C) Parquet supports schema evolution and columnar storage
D) Parquet offers row-based compression
4. Which actions are valid techniques for handling erroneous categorical values in a dataset?
(Choose two)
A) Converting all values to integers
B) Normalizing using min-max scaling
C) Removing rows with invalid labels
D) Replacing inconsistent labels with a standardized value
5. What result will the following Pandas expression return: df['Age'].notnull().all()?
A) Returns the number of NULL values in 'Age'
B) Returns True if all values in 'Age' are not NULL
C) Returns True if all values in 'Age' are NULL
D) Returns True if at least one value in 'Age' is not NULL
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: C,D | Question # 5 Answer: B |



