Exam Name: PCED - Certified Entry-Level Data Analyst with Python
Certification Provider: Python Institute
Corresponding Certification: Python Institute PCED
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Python Institute PCED-30-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Python Basics for Data Analysis | 32.5% | - Data Structures
|
| Topic 2: Working with Data and Performing Simple Analyses | 32.5% | - Data Cleaning and Transformation
|
| Topic 3: Communicating Insights and Reporting | 12.5% | - Data Visualization
|
| Topic 4: Introduction to Data and Data Analysis Concepts | 22.5% | - Data Ethics and Privacy
|
Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:
You are reading a data.csvfile line by line. To prepare each line for formatting with f-strings, you need to remove extra whitespace and split the values by commas.
Which line should you insert to correctly clean and parse the input?
- A. fields = line.split(', ').trim()
- B. fields = line.strip().split(', ')
- C. fields = line.split().strip(', ')
- D. fields = line.replace(', ', '|').split('|')
Correct Answer: B 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
Below are six possible summaries for your presentation:
- Summary 1: "The data revealed a moderate positive correlation between age and recycling frequency. While 72% of students reported recycling paper regularly, only 39% reported recycling plastic."
- Summary 2: "Analysis showed notable differences in recycling habits by material type, with paper being most recycled and plastic least recycled."
- Summary 3: "Older kids recycled more than younger ones. Paper was the most recycled item- plastic got forgotten a lot."
- Summary 4: "Student responses showed positive environmental habits overall, though participation varied by waste type."
- Summary 5: "A lot of students said they recycle. Some didn't answer every question, so we couldn't figure out everything."
- Summary 6: "We asked more than 300 students about recycling. Most said they recycle paper, but way fewer recycle plastic." Which communication style is the best fit for Group A (data scientists) and Group B (12-year- olds), respectively? Select the best answer.
- A. Summary 4 for Group A, Summary 3 for Group B
- B. Summary 2 for Group A. Summary 6 for Group B
- C. Summary 1 for Group A, Summary 6 for Group B
- D. Summary 6 for Group A, Summary 3 for Group B
- E. Summary 6 for Group A, Summary 5 for Group B
- F. Summary 1 for Group A, Summary 3 for Group B
Correct Answer: F 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
Given the following string:
text = "Report2024Final"
Which of the following statements are entirely correct? (Choose two.)
- A. text[0:6].isalpha() returns True, and text.find("2024") returns 6
- B. text[6:8].isdigit()returns True, and text.endswith("Final")returns True
- C. text.capitalize()changes Finalto lowercase, and text.find ("L")returns True
- D. text.capitalize()changes Report2024Finalto REPORT2024FINAL, and text.find("2024")returns 6
- E. text[-6].isdigit() returns True, text.startswith("r") returns True
- F. text.isalpha()returns True, and text.find ("2024")returns True
Correct Answer: A,B,C 🗳️
Explanation: Only visible for Prep4away 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.linspace(0, 181, 10)
target_temps = np.arange(35.0, 37.0, 0.5)
import numpy a3 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.arange(0, 180, 10)
target_temps = np.linspace(35.0, 37.0, 4)
import numpy as np
Correct Answer: B 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
You are given two lists representing daily page views and sign-ups on a website:
views = [120, 130, 128, 700, 115, 123, 119, 680, 122]
signups = [12, 15, 13, 50, 11, 14, 10, 55, 13]
You want to:
- remove outliers (views > 600), and
- calculate correlation between the cleaned lists.
Which code accomplishes this correctly? Select the best answer.
- A.
- B.
- C.
- D.
Correct Answer: C 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
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