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Python Institute PCAD-31-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Exploratory Data Analysis
Topic 2: Data Acquisition and Pre-Processing	29.2%
Topic 3: SQL and Data Management
Topic 4: Statistical Methods and Modeling
Topic 5: Data Visualization and Communication

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q60-Q65):

NEW QUESTION # 60
Which method is best suited to transform inconsistent entries such as "N/A", "missing", and empty strings into a standard missing value representation in a Pandas DataFrame?

A. df.replace()
B. df.rename()
C. df.sort_values()
D. df.dropna()

Answer: A

NEW QUESTION # 61
When analyzing a dataset of customer ages, you calculate the mean, median, and mode. What does it indicate if all three values are approximately equal?

A. The dataset contains outliers
B. The dataset is uniformly distributed
C. The dataset has a normal distribution
D. The dataset is positively skewed

Answer: C

NEW QUESTION # 62
Which of the following libraries is specifically optimized for high-performance numerical computation with multi-dimensional arrays in Python?

A. NumPy
B. matplotlib
C. pandas
D. seaborn

Answer: A

NEW QUESTION # 63
Why is it important to use a test dataset separate from the training dataset when evaluating a machine learning model?

A. To ensure the loss function is minimized
B. To evaluate the model's performance on unseen data
C. To reduce the number of iterations during training
D. To optimize the model's training accuracy

Answer: B

NEW QUESTION # 64
What distinguishes structured data from unstructured data in the context of data modeling and storage?

A. Structured data cannot be stored in databases
B. Unstructured data contains only numeric values
C. Structured data follows a consistent schema or format
D. Unstructured data cannot be stored or analyzed

Answer: C

NEW QUESTION # 65
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