Python Institute PCAD-31-02 test insides dumps : Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)

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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

1. 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) Apply interpolate() method
B) Use drop() to remove null rows
C) Use dropna() with axis=1
D) Use fillna() with a constant value

2. When analyzing a sales dataset using Pandas, which of the following techniques help extract key insights by grouping and summarizing the data?
(Choose two)

A) Using rename() to change column headers
B) Using fillna() to replace missing product prices
C) Applying agg() to calculate multiple metrics like mean and max
D) Using groupby() to compute total sales per region

3. Which of the following statistical measures are considered measures of central tendency?
(Choose two)

A) Variance
B) Mode
C) Interquartile range
D) Mean

4. 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 the entire DataFrame
C) Returns a new DataFrame excluding 'column1'
D) Returns rows 2 to 4 in 'column1'

5. Which practices help ensure secure and effective execution of SQL queries in Python scripts?
(Choose all that apply)

A) Using string concatenation to insert variables into SQL
B) Employing parameterized statements for user-supplied data
C) Wrapping SQL commands in try-except blocks
D) Using string formatting to build SQL queries dynamically

Solutions: