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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Exploratory Data Analysis | ||
| Topic 2: Statistical Methods and Modeling | ||
| Topic 3: Data Acquisition and Pre-Processing | 29.2% | |
| Topic 4: SQL and Data Management | ||
| Topic 5: Data Visualization and Communication |
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
1. When merging two Pandas DataFrames using a common key, which parameters are essential to ensure accurate and conflict-free results?
(Choose two)
A) on
B) ignore_index
C) suffixes
D) dropna
2. What is the primary reason to use .head() and .tail() methods in pandas when exploring datasets?
A) To delete missing values
B) To create visualizations
C) To preview the first and last few rows of data
D) To rename columns
3. What is the benefit of using the __name__ == "__main__" construct in Python scripts?
A) It allows access to all global variables
B) It defines the main function in Python
C) It prevents modules from being imported
D) It allows selective execution of code when run as a script
4. What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?
A) Parquet offers row-based compression
B) Parquet supports schema evolution and columnar storage
C) Parquet files can only be used with Excel
D) Parquet stores data in plain text, making it human-readable
5. Which technique would be most appropriate to handle missing numerical values in a dataset intended for machine learning?
A) Filling with random values
B) Dropping all columns
C) Imputation using mean or median
D) Replacing with NULL
Solutions:
| Question # 1 Answer: A,C | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: C |
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