Practice Time Series Visualization - 3.4 | 3. Advanced Data Visualization Techniques | Data Science Advance
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3.4 - Time Series Visualization

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a rolling window in time series analysis?

💡 Hint: Think about how we can smooth out data fluctuations.

Question 2

Easy

List the three components of seasonal decomposition.

💡 Hint: Remember the acronym T-S-R!

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the purpose of using rolling windows in time series?

  • To visualize all data points
  • To smooth out short-term fluctuations
  • To ignore long-term trends

💡 Hint: Think about why we might want to smooth data.

Question 2

Seasonal decomposition separates time series into which of the following components?

  • Trend and seasonality
  • Inputs and outputs
  • Data and noise

💡 Hint: Remember the key acronym for seasonal decomposition.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset with daily temperatures over a year, apply seasonal decomposition. Discuss how the trends vary and identify the major seasonal effects.

💡 Hint: Focus on each component's contribution and how they manifest in the time series.

Question 2

Create an interactive time series plot that shows the financial performance of a company over five years, including seasonal effects and general trends.

💡 Hint: Incorporate dynamic elements that highlight seasonal trends.

Challenge and get performance evaluation