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Python Institute PCED-30-02 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Handling and Processing with Python | - Working with data structures
|
| Topic 2: Basic Statistics for Data Analysis | - Descriptive statistics
|
| Topic 3: Data Analysis and Visualization | - Data cleaning and preprocessing
|
| Topic 4: Python Programming Fundamentals | - Basic syntax and data types
|
Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:
The following chart shows how a student spends 24 hours in a day:
Which statements are most accurate? (Choose two.)
- A. Leisure accounts for a moderate portion of the student's daily schedule, larger than commuting but smaller than the time spent at school.
- B. Leisure and meals combined equal the time spent at school.
- C. School and homework together take up half of the day's time.
- D. Commuting is the second most time-consuming activity.
- E. Sleep and school take up the majority of time in a day.
- F. More time is spent commuting than on leisure.
Correct Answer: A,E 🗳️
Explanation: Only visible for RealVCE members. You can sign-up / login (it's free).
You are developing a temperature control module for a laboratory incubator. Your objectives are to:
- generate timestamps every 10 minutes over a 3-hour span (i.e., 0 to 180 minutes), and
- simulate five evenly spaced target temperatures between 35.0°C and 37.0°C for system calibration.
Which code snippet correctly produces both sequences using NumPy? Select the best answer.
import numpy as np
- A. timestamps = np.arange(0, 180, 10)
target_temps = np.linspace(35.0, 37.0, 4)
import numpy as np - B. timestamps = np.arange(0, 181, 10)
target_temps = np.linspace(35.0, 37.0, 5) - C. timestamps = np.linspace(0, 180, 10)
target_temps = np.arange(35.0, 37.0, 5)
import numpy as np - D. timestamps = np.linspace(0, 181, 10)
target_temps = np.arange(35.0, 37.0, 0.5)
import numpy a3 np
Correct Answer: B 🗳️
Explanation: Only visible for RealVCE members. You can sign-up / login (it's free).
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 = Counter(colors)
color_counts = sum(np.unique(colors))
import numpy as np - B. from collections import Counter
unique_colors = len(set(colors))
color_counts = np.unique(colors) - C. from collections import Counter
unique_colors = len(unique(colors))
color_counts = Counter(colors)
import numpy as np - D. from collections import Counter
unique_colors = np.unique(colors)
color_counts = Counter(set(colors))
import numpy as np
Correct Answer: C 🗳️
Explanation: Only visible for RealVCE members. You can sign-up / login (it's free).
A teacher wants to compare the number of students in different school clubs:
Which type of chart would be most appropriate to show this comparison? Select the best answer.
- A. Pie chart
- B. Line chart
- C. Bubble chart
- D. Bar chart
Correct Answer: D 🗳️
Explanation: Only visible for RealVCE members. You can sign-up / login (it's free).
What will be the output of the following code?
- A. 10 5
- B. 10 10
- C. 5 10
- D. 5 5
Correct Answer: D 🗳️
Explanation: Only visible for RealVCE members. You can sign-up / login (it's free).
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