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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Visualization and Communication | ||
| Topic 2: SQL and Data Management | ||
| Topic 3: Statistical Methods and Modeling | ||
| Topic 4: Exploratory Data Analysis | ||
| Topic 5: Data Acquisition and Pre-Processing | 29.2% |
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
What is the purpose of using df.loc[2:5, 'column1'] in a Pandas DataFrame?
- A. Returns rows 2 through 5 in 'column1'
- B. Returns rows 2 to 4 in 'column1'
- C. Returns the entire DataFrame
- D. Returns a new DataFrame excluding 'column1'
Correct Answer: A 🗳️
Why is it important to manage object identity correctly in complex data analysis pipelines?
- A. It avoids redundant copies and preserves shared state when required
- B. It prevents reloading modules unnecessarily
- C. It guarantees consistent hashing of string values
- D. It ensures type casting is consistently applied
Correct Answer: A 🗳️
Which refinements are typically used to enhance clarity and presentation quality in visualizations?
(Choose two)
- A. Avoiding color entirely
- B. Adding descriptive axis labels
- C. Customizing tick labels
- D. Disabling grid lines in all cases
Correct Answer: B,C 🗳️
Which techniques can be used to select a subset of rows and columns from a DataFrame using labels?
(Choose two)
- A. df.loc[2:7, ['col1', 'col2']]
- B. df.iloc[0:5, 'col2']
- C. df.loc[:, 'col1']
- D. df['col1', 'col2']
Correct Answer: A,C 🗳️
What is the primary reason to use .head() and .tail() methods in pandas when exploring datasets?
- A. To preview the first and last few rows of data
- B. To delete missing values
- C. To create visualizations
- D. To rename columns
Correct Answer: A 🗳️
