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Data Analysis and Visualization with Python / Module 8

Module 8 check

Module 8 Assessment: Time Analysis Check

Assessment ID: DAV-M08-QA01 Estimated active time: 30-40 minutes

Part A: Short answers

  1. Why should date parsing failures be checked?
  2. Why should time data be sorted?
  3. What is resampling?
  4. What does a rolling average do?
  5. Why can unequal time windows be misleading?

Part B: Code check

Write pandas code to:

  1. Parse event_date.
  2. Count missing parsed dates.
  3. Create a month field.
  4. Create a weekly total of minutes_spent.
  5. Add a four-week rolling average.

Rubric

LevelEvidence
PassDates are parsed and checked, summaries use appropriate periods, and limitations are stated.
ReviseCode creates a trend but date quality or comparison window is unclear.
Not yetCode treats date strings as reliable without parsing and checking.