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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q32-Q37):
NEW QUESTION # 32
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.strip().split(', ')
- B. fields = line.split(', ').trim()
- C. fields = line.replace(', ', '|').split('|')
- D. fields = line.split().strip(', ')
Answer: A
NEW QUESTION # 33
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, 180, 10)
target_temps = np.linspace(35.0, 37.0, 4)
import numpy as np - C. timestamps = np.arange(0, 181, 10)
target_temps = np.linspace(35.0, 37.0, 5) - D. timestamps = np.linspace(0, 180, 10)
target_temps = np.arange(35.0, 37.0, 5)
import numpy as np
Answer: C
Explanation:
np.arange(0, 181, 10) generates timestamps from 0 through 180 in 10-minute steps (end is excluded, so using 181 includes 180). np.linspace(35.0, 37.0, 5) generates five evenly spaced temperatures including both 35.0°C and 37.0°C.
NEW QUESTION # 34
A loop is designed using range(1, 6, 2) to iterate through numbers. The developer wants to know exactly which values will be generated during execution. Which sequence correctly represents the values produced?
- A. 1, 3
- B. 1, 2, 3, 4, 5
- C. 2, 4, 6
- D. 1, 3, 5
Answer: D
Explanation:
The range(start, stop, step) function generates numbers starting from 1, increasing by 2, and stopping before 6. Therefore, the resulting sequence is 1, 3, and 5.
NEW QUESTION # 35
Which task is traditionally or typically performed by a data analyst, and not by a data scientist or analytics specialist? Select the best answer.
- A. Recommending pricing strategies using predictive modeling and A/B testing.
- B. Developing machine learning algorithms to predict user behavior.
- C. Creating summary tables and charts to describe patterns in historical data.
- D. Designing a data pipeline to ingest and process real-time sensor data.
Answer: C
Explanation:
Creating summary tables and charts to describe patterns in historical data is a core responsibility of a data analyst, focusing on descriptive analytics and reporting rather than building predictive models, machine learning systems, or engineering data pipelines.
NEW QUESTION # 36
You are reviewing a report that compares the number of weekly client meetings and project completion rates across teams. The table below summarizes the data for each team:
Which statement best describes the data shown above? Select the best answer.
- A. The more meetings a team had, the more projects they finished, especially in high-performing teams like Omega and Delta."
- B. "Project completion numbers were nearly identical across all teams, averaging 3.25 per month."
- C. "Teams with 5-6 weekly meetings tended to complete more projects than those with very high or very low meeting counts."
- D. "Gamma and Omega were outliers that inflated the meeting average, but most teams finished about 3 projects per month."
Answer: C
Explanation:
Teams with moderate meeting counts around 5-6 per week (such as Alpha, Gamma, and Theta) completed among the highest numbers of projects, while teams with very high or very low meeting counts tended to complete fewer projects, indicating that moderate meeting frequency is associated with higher project completion.
NEW QUESTION # 37
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