Matplotlib - Performance and Large Data
You need to generate 100 large plots in a script without running out of memory. Which approach is best to manage memory efficiently?
You need to generate 100 large plots in a script without running out of memory. Which approach is best to manage memory efficiently?
hard📝 Application Q15 of 15
Step-by-Step Solution
Solution:
Step 1: Understand memory use when creating many figures
Creating many large figures without closing them uses too much memory and slows the system.Step 2: Best practice for memory management
Creating, saving, then closing each figure before the next frees memory and avoids overload.Final Answer:
Create each figure, plot data, save it, then call plt.close() before next -> Option AQuick Check:
Close each figure after saving to save memory [OK]
Quick Trick: Save and close each figure before next to avoid memory issues [OK]
Common Mistakes:
- Creating all figures before saving causes memory overload
- Not closing figures after plotting
- Plotting all data on one figure when separate plots needed
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