PCAD-31-02 exam dumps

Python Institute PCAD-31-02 Value Package

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  • Exam Code: PCAD-31-02
  • Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)
  • No. of Questions: 146 Questions and Answers
  • Updated: Oct 08, 2026

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  • Total Questions: 146
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  • Total Questions: 146
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  • Total Questions: 146
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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
SQL and Data Management
Exploratory Data Analysis
Statistical Methods and Modeling
Data Acquisition and Pre-Processing29.2%
Data Visualization and Communication

Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:

Which practices are considered part of professional Python scripting standards?
(Choose two)

  • A. Avoiding error handling to keep code clean
  • B. Including in-line comments and docstrings
  • C. Avoiding use of modules and libraries
  • D. Using consistent indentation and naming conventions
Reveal Solution  Discussion  0

Correct Answer: B,D  🗳️

What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?

  • A. Parquet files can only be used with Excel
  • B. Parquet stores data in plain text, making it human-readable
  • C. Parquet supports schema evolution and columnar storage
  • D. Parquet offers row-based compression
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Which Python library is most commonly used to establish a connection to a SQLite database and perform SQL operations?

  • A. psycopg2
  • B. sqlalchemy
  • C. sqlite3
  • D. pymysql
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Which of the following would best validate the uniqueness of a primary key in a Pandas DataFrame?

  • A. df['id'].isnull().sum()
  • B. df['id'].nunique()
  • C. df['id'].duplicated().any()
  • D. df['id'].fillna()
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Which methods can be used to validate data types and structure in a Pandas DataFrame?
(Choose two)

  • A. df.info()
  • B. df.memory_usage()
  • C. df.to_csv()
  • D. df.dtypes
Reveal Solution  Discussion  0

Correct Answer: A,D  🗳️

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