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freeCodeCamp/curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-algebra-and-size.md
miyaliu666 3ea2fe4f77 feat(i18n,curriculum): add Bilibili ids for Chinese (#43564) 
Co-authored-by: Kristofer Koishigawa <scissorsneedfoodtoo@gmail.com>
Co-authored-by: Oliver Eyton-Williams <ojeytonwilliams@gmail.com>
2021-10-01 09:54:12 +05:30

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id, title, challengeType, videoId, bilibiliIds, dashedName
id title challengeType videoId bilibiliIds dashedName
5e9a093a74c4063ca6f7c157 Numpy Algebra and Size 11 XAT97YLOKD8
aid bvid cid
250621433 BV1hv41137uM 409013128
numpy-algebra-and-size

--description--

Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.

More resources:

--question--

--text--

What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?

--answers--

Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.

NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.

NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.

Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.

--video-solution--

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