Free Python Institute PCED-30-02 Exam Dumps Questions & Answers

Consider the following Python code:

What will be printed when the code above is executed?
40

• A.[10, 20, 30, 40]
  1
  [1, 2, 4, 5, 6]
  50
• B.[20, 30, 40]
  1
  [1, 2, 4, 5, 6]
• C.[10, 20, 30, 40]
  0
  [1, 2, 3, 4, 5, 6]
  50
• D.[20, 30, 40]
  1
  [1, 2, 4, 5, 6]
  50

How do the analysis and visualization stages of the data lifecycle typically work together?

• A.Analysis identifies patterns and insights in processed data, which are then communicated through visualizations for informed decision-making.
• B.Analysis retrieves raw inputs from dashboards, while visualization uses that input to clean the data.
• C.Analysis produces charts and graphs, while visualization interprets the data to detect outliers.
• D.Analysis summarizes archived data, and visualization transforms it into structured tables for storage.

A Python loop uses range(5, 0, -2) to iterate backward. The programmer expects a decreasing sequence. Which values will actually be generated when this loop runs?

• A.5, 4, 3, 2, 1
• B.5, 3
• C.5, 3, 1
• D.4, 2, 0

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

A healthcare provider analyzes patient records to determine that appointment cancellations spike during weather alerts and flu season.
What type of analytics is this?

• A.Prescriptive analytics - it automates patient rescheduling based on cancellation patterns.
• B.Diagnostic analytics - it identifies reasons behind patterns in patient behavior.
• C.Descriptive analytics - it reports appointment numbers across past seasons.
• D.Predictive analytics - it uses weather and illness trends to forecast future cancellations.