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| Section | Weight | Objectives |
|---|
| Statistical Methods and Modeling | | |
| SQL and Data Management | | |
| Exploratory Data Analysis | | |
| Data Visualization and Communication | | |
| Data Acquisition and Pre-Processing | 29.2% | |
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q100-Q105):
NEW QUESTION # 100
Which method is used after grouping a DataFrame to compute the average value for each group in a specific column?
- A. groupby().mean()
- B. groupby().count()
- C. groupby().max()
- D. groupby().aggregate()
Answer: A
NEW QUESTION # 101
Which characteristics are typically associated with unstructured data formats?
(Choose two)
- A. Requires parsing or transformation before analysis
- B. Highly tabular and query-friendly
- C. Lacks predefined data schema
- D. Stored using fixed-width fields and records
Answer: A,C
NEW QUESTION # 102
Which of the following practices improves clarity when combining visualizations and textual explanations in a report?
- A. Include concise textual summaries that highlight the chart's message
- B. Avoid summarizing the data verbally
- C. Repeat all numerical data in both the chart and text
- D. Use visualizations alone without titles or captions
Answer: A
NEW QUESTION # 103
What is the most efficient way to handle missing values in a Pandas DataFrame when preparing a dataset for analysis that must maintain original index structure and avoid row deletions?
- A. Use fillna() with a constant value
- B. Use drop() to remove null rows
- C. Use dropna() with axis=1
- D. Apply interpolate() method
Answer: A
NEW QUESTION # 104
Which method in a Python class is responsible for initializing the object's attributes at the time of creation?
- A. __getattr__()
- B. __str__()
- C. __main__()
- D. __init__()
Answer: D
NEW QUESTION # 105
......
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