[Edit] Python: NumPy - .mean() #6477
Conversation
mamtawardhani
added
enhancement
| ## Best Practices | ||
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| 1. **Choose the appropriate axis**: When working with multi-dimensional arrays, carefully select the axis parameter to ensure calculations are performed along the intended dimension. | ||
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| 2. **Consider data type precision**: For scientific calculations requiring high precision, use the default `float64` or explicitly specify it. For less critical applications where memory efficiency is important, consider using `float32`. | ||
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| 3. **Use keepdims for dimensional consistency**: Set `keepdims=True` when maintaining the same number of dimensions in the output as in the input is necessary, which can be useful for broadcasting operations. |
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This section can be removed. It's making the entry big.
| ## FAQs | ||
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| <details> | ||
| <summary>1. What's the difference between `np.mean()` and `np.average()`?</summary> |
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Can you add backlinks to np.mean and np.average?
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| ## Example | ||
| ## Example 3: Data Analysis with Real-world Data |
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Remove example 3 as well. We already have two examples and a codebyte.
Radhika-okhade
added
status: review 1️⃣ completed
status: waiting for author
and removed
status: under review
Co-authored-by: Radhika-okhade <[email protected]>
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Thank you for contributing to Codecademy docs @mamtawardhani. The entry looks good to be merged. |
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👋 @mamtawardhani 🎉 Your contribution(s) can be seen here: https://www.codecademy.com/resources/docs/numpy/built-in-functions/mean Please note it may take a little while for changes to become visible. |
Description
[Edit] Python: NumPy - .mean()
Issue Solved
Closes #6443
Type of Change
Checklist
mainbranch.Issues Solvedsection.