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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Objectives
Data Analysis and Visualization	- Data cleaning and preprocessing 1. Missing values handling 2. Data transformation techniques - Data visualization 1. Plot interpretation 2. Matplotlib basics
Data Handling and Processing with Python	- Data manipulation libraries 1. Pandas fundamentals 2. NumPy basics - Working with data structures 1. Iterating and transformations 2. Lists, tuples, dictionaries
Python Programming Fundamentals	- Basic syntax and data types 1. Control flow basics 2. Variables and operators
Basic Statistics for Data Analysis	- Descriptive statistics 1. Variance and standard deviation 2. Mean, median, mode

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q27-Q32):

NEW QUESTION # 27
A Python script evaluates the expression len(" "). The programmer assumes it might be zero because it looks empty. What will the actual result be?

A. 0
B. None
C. Error
D. 1

Answer: A

Explanation:
A space is still a valid character in a string. Therefore, the string contains one character, and len("
") returns 1 instead of 0.

NEW QUESTION # 28
Which of the following code snippets will output Truefor both printfunctions by correctly identifying the type of each variable and performing valid operations?

Answer: A

Explanation:
Adding an integer and a float produces a float result, so checking that the type of the sum is float evaluates to True. The variable holding 3.0 is a float, so the isinstance check for float also evaluates to True.

NEW QUESTION # 29
A program uses while False: followed by print statements inside the loop. The developer expects output. What will actually happen during execution?

A. No execution
B. Error
C. Prints once
D. Infinite loop

Answer: A

Explanation:
The condition False is evaluated before entering the loop. Since it is always false, the loop body is never executed, and no output is produced.

NEW QUESTION # 30
You have collected sales data and want to compute the average using the NumPy library.
Which option correctly shows how to install NumPy and use it in your code to perform this task?

A. To install NumPy:
pip install numpy as np
Then run this code:
import np
data = np.array([10, 20, 30])
print(np.mean(data))
B. To install NumPy:
from pip install numpy
Then run this code:
import numpy as np
data = np.array([10, 20, 30])
print(np.mean(data))
C. To install NumPy:
pip install numpy
Then run this code:
import numpy as np
data = numpy.arr([10, 20, 30])
print(numpy.mean(data))

Answer: B

Explanation:
NumPy is installed with pip install numpy, then imported with import numpy as np. After that, you can create an array and compute the mean using np.array(...) and np.mean(...).

NEW QUESTION # 31
You are analyzing survey results from students about their favorite colors. The list colorsstores individual responses:

You want to:
- find the number of unique colors mentioned using NumPy, and
- determine how often each color was chosen using Counter.
Which code snippet correctly performs both tasks? Select the best answer.
from numpy import unique

A. from collections import Counter
unique_colors = len(set(colors))
color_counts = np.unique(colors)
B. from collections import Counter
unique_colors = len(unique(colors))
color_counts = Counter(colors)
import numpy as np
C. from collections import Counter
unique_colors = np.unique(colors)
color_counts = Counter(set(colors))
import numpy as np
D. from collections import Counter
unique_colors = Counter(colors)
color_counts = sum(np.unique(colors))
import numpy as np

Answer: B

Explanation:
numpy.unique returns the distinct values in the list, and taking its length gives the number of unique colors. Counter(colors) correctly counts how many times each color appears in the responses.

NEW QUESTION # 32
......

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