Recall & Review
beginner
What is downsampling in data visualization?
Downsampling means reducing the number of data points shown in a plot to make it easier to see patterns and improve performance.
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beginner
Name two common downsampling strategies used in matplotlib.
Two common strategies are 'decimation' (picking every nth point) and 'aggregation' (averaging points in groups).
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beginner
How does decimation help in downsampling?
Decimation reduces data by selecting every nth point, which keeps the data simple but might miss details.
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intermediate
What is the benefit of aggregation over decimation?
Aggregation combines multiple points into one (like averaging), which keeps overall trends better than just picking points.
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beginner
Why is downsampling important when plotting large datasets with matplotlib?
Downsampling improves plot speed and clarity by reducing clutter and making the plot easier to understand.
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What does downsampling do in data visualization?
✗ Incorrect
Downsampling reduces data points to simplify the plot and improve performance.
Which downsampling method selects every nth data point?
✗ Incorrect
Decimation picks every nth point to reduce data size.
What is a key advantage of aggregation in downsampling?
✗ Incorrect
Aggregation combines points to keep trends visible.
Why might you downsample a large dataset before plotting?
✗ Incorrect
Downsampling helps the plot load faster and look clearer.
Which matplotlib feature can help with downsampling large datasets?
✗ Incorrect
LineCollection can be used with decimation to downsample lines efficiently.
Explain what downsampling is and why it is useful in matplotlib plots.
Think about what happens when you have too many points on a plot.
You got /4 concepts.
Describe the difference between decimation and aggregation as downsampling strategies.
One picks points, the other combines points.
You got /3 concepts.