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Python Institute PCED-30-02 Exam Syllabus Topics:

Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:

Question 1

A data analyst exports a cleaned dataset from Python and wants to share it with a colleague for easy use in Excel.
Which file format is best suited for this purpose? Select the best answer.

A. JSON, because it stores hierarchical data and is designed for visual presentation in Excel.
B. XML, because it automatically preserves spreadsheet formatting and charts.
C. SQL, because it directly converts tabular data into database tables that Excel can open.
D. CSV, because it stores tabular data in plain text and is compatible with spreadsheet applications.

Question 2

You are creating a presentation slide to communicate findings about student stress levels across four categories over a six-month period. You include the following line graph in your presentation:

Your goal is to help your audience clearly understand trends in stress levels over time.
What is the highest problem with this visual presentation? Select the best answer.

A. The chart should be in 3D format to show depth and highlight differences more clearly.
B. The font used in the chart is hard to read; using larger, uppercase text would improve clarity.
C. The graph doesn't explain what each stress level means or show exact values for each month, which limits interpretation.
D. The lines are too light and similar in color, making it difficult to distinguish between trends.
E. The months should be replaced with week numbers to provide more detailed insight.

Question 3

You are working with city names entered by users. These names may contain inconsistent capitalization and unwanted spaces.
To standardize the data, you want to:
- Remove any leading or trailing whitespace, and
- Capitalize the first letter of each word (e.g., convert "new york" to "New York").
For example:
" New york " → "New York"
"lOS ANGELES" → "Los Angeles"
You are given a variable citythat contains the raw input.
Which line of code correctly updates the value of cleaned_cityto apply the required transformation? Select the best answer.

A. cleaned_city = city.strip().capitalize()
B. cleaned_city = city.strip().title()
C. cleaned_city = city.upper().strip()
D. cleaned_city = city.upper().replace(" ", "")

Question 4

You are writing a function to validate battery voltage readings. The rules are:
- If the reading is "MISSING"or None, return "Missing".
- If the value is below 2.5or above 4.2, return "Outlier".
Otherwise, return "Normal".
Which version correctly implements this logic using the most robust conditional and nested structures? Select the best answer.

A.

B.

C.

D.

Question 5

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, 181, 10)
target_temps = np.linspace(35.0, 37.0, 5)
B. timestamps = np.linspace(0, 181, 10)
target_temps = np.arange(35.0, 37.0, 0.5)
import numpy a3 np
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

Solutions: